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Label-free sensing with semiconducting nanowires

A Dissertation Presented to the Faculty of the Graduate School

of Yale University

in Candidacy for the Degree of Doctor of Philosophy

by Eric Stern

Dissertation Director: Prof. Mark A. Reed

May 2007

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Abstract

Label-free sensing with semiconducting nanowires

Eric Stern

2007

Nanoscale electronic devices have the potential to achieve exquisite sensitivity as sensors

for the direct detection of molecular interactions, thereby decreasing diagnostics costs

and enabling previously impossible sensing in disparate field environments.

Semiconducting nanowire-field effect transistors (NW-FETs) hold particular promise,

though contemporary NW approaches are inadequate for realistic applications. We

present here a novel approach using complementary metal-oxide-semiconductor (CMOS)

technology that has not only achieved unprecedented sensitivity, but simultaneously

facilitates system-scale integration of nanosensors for the first time. This approach

enables a wide range of label-free biochemical and macromolecule sensing applications,

including cell type discrimination through the monitoring of live, stimulus-induced

cellular response, and specific protein and complementary DNA recognition assays. An

important achievement is the introduction of real-time, unlabeled detection capability,

allowing for fundamental studies of cellular activation, and specific macromolecule

interactions at concentrations (<femtomolar) orders of magnitude lower than other

commonly available techniques.

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© 2007 by Eric Stern All Rights Reserved.

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To Alan Stern, who taught me more about life, family, hard work—and in turn myself—over the

past four years than I ever thought I’d know

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Acknowledgements

There are more people than I can count who helped make this work possible. I owe a

huge debt of gratitude to my advisor, collaborators, and coworkers, as well as to my

family and friends (those categories are not mutually exclusive). And, of course, I am

indebted to the agencies sponsoring the graduate fellowships I was fortunate enough to be

awarded, the Department of Homeland Security and the National Science Foundation.

First and foremost I thank Prof. Mark Reed, my boss, for keeping me in his laboratory at

Yale for another four years and for being not only merely a truly exceptional mentor (and

bill-payer) but also a good, trusted friend. My last four years have been one of the most

spectacular periods of my life due primarily to the countless hours I spent in the Becton

Center under his tutelage. I have had a truly unbelievable experience working in his

laboratory and plan to maintain a close collaboration, at the very least, for a long time to

come.

I also thank all my committee members for their exceptional support for my work and for

their advice and friendship. From the outset of my project, Prof. Fred Sigworth raised a

number of critical concerns. Without accounting for his crucial observations, which

required countless conversations throughout the course of the work, the project quite

simply would not have worked. Also from the outset of my graduate career, I was

fortunate enough to have a second laboratory, Prof. David LaVan’s, opened to me. The

chemical reactions and surface characterizations I performed in this second home, as well

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as the conversations I had with Prof. LaVan, were critical at every step of my project.

Although my interactions with Prof. Tarek Fahmy began later in the course of my work,

this collaboration has proven to be the most fruitful of my life. Seemingly not a single

experiment has been performed by me in the last year (many, incidentally, in his

laboratory) without thorough discussions (generally after midnight) with Prof. Fahmy and

I look forward to many more such conversations in the future as a postdoctoral researcher

in his lab.

Many of the current and former Reed group members have not only helped incredibly

with my work but shaped me as a scientist as well. Professors Ilona Kretzschmar (City

College of New York) and Guosheng Cheng (Suzhou University) were not only

instrumental in teaching me to perform engineering research but also taught me the value

of collaboration. Without them, much of the work presented here could not have even

been started. James Klemic helped me through my work every step along the way not

only scientifically but also has a good friend. Professor Takhee Lee (Gwangju Institute

of Science and Technology) and Doctors Menno de Jong and Glenn Martin, though

present for only a brief period during my thesis work, taught me an incredible amount

about research and the required work ethic. Aleksandar Vacic, though only present at the

tail end of the work, was instrumental for the theoretical studies and I leave knowing the

nanobars are in great hands with him and David Routenberg, who helped me through

many of the rough spots and performed some of the most exciting and important device

physics experiments. Additionally, Dr. Marleen van der Veen’s infectious personality

and work ethic helped reinvigorate me during the last months of the work and she should

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join Alek and David as a member of a very high-flying Reed group team in the future.

Doctors Jia Chen and Jeff Sleight, though graduated before I showed up, provided

exceptional help with many experiments. Additionally, Doctors Elena Cimpoiasu, Nilay

Pradhan, Wenyong Wang, Xiaohui Li, and Jie Su, in addition to Stan Guthrie, Ryan

Munden, and Aric Sanders contributed to sample growth and device measurements.

Matthew Phillips, though only present transiently, provided strong encouragement.

I have been blessed with having some truly exceptional undergraduates working for me

over time who have greatly contributed to the results. Daniel Turner-Evans began just as

the work got exciting and his fingerprints are all over the work presented here. Robin

Wagner single-handedly laid the groundwork not only for my final experiments but for

much of the future work I hope to accomplish. Carl Dietz and Eric Steinlauf, though in

lab just a bit too early to catch the most exciting work, contributed greatly to my original

understanding of the sensors. Burt Helm, Elizabeth Broomfield, Shin Rong Lee, Jamie

Capo, and Maria (Gaby) Oronchea (not under my direct supervision) also performed

some interesting and critical experiments.

As a very fortunate pseudo-member of the Fahmy group for the final semesters of my

work, I have had the opportunity to work with his exceptional students and very much

look forward to continuing these relationships. Erin Steenblock provided samples, a

watchful eye, and good luck for some of my final experiments and traveled more miles

with me than any other collaborator. Jason Park, Stacey Demento, Jason Criscione, and

Tarek Fadel have provided great encouragement and much of the work we have recently

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collaborated on will come to spectacular fruition under their direction. And the members

of the Fahmy group undergraduate army, Michaela Panter, Karlo Perica, Karen Chen,

Katie Allen, Gilbert Addo, Atu Agawu, Jeffrey Reitman, and Sean Mehra, have also

contributed not only to the work but to making it fun.

There are many professors in addition to my committee members whose advice and

support was instrumental and who have helped make my Yale graduate experience

exceptional. Yale Professors T. P. Ma, Jung Han, Jerry Woodall, Peter Kindlmann,

Yiorgos Makris, Eugenio Culurciello, Hur Koser, and Robert Schoelkopf helped at many

steps with device design and fabrication. Yale Professors Mark Saltzman, Michael

Levene, Ron Breaker, Michael Snyder, Andrew Hamilton, Eric Dufresne, John Wood,

Glenn Micalizio, Erin Lavik, and Dennis Spencer helped throughout my work with

functionalization and sensing. I also enjoyed very fruitful collaborations with Professors

Tadeusz Malinski of Ohio University and Chonwu Zhou of the University of Southern

California, and Dr. Jack Yu of the Medical College of Georgia. Professors Jonathan

Schneck (Johns Hopkins University), Herman Eisen (Massachusetts Institute of

Technology), and Ruslan Medzhitov provided critical samples for cellular response

measurements. Additionally, I am indebted to Profs. James Duncan, Fahmeed Hyder,

Saltzman, and Fahmy for selecting me as a Teaching Assistant for their classes and to

Prof. Levene for allowing me to be a guest lecturer in the Senior Seminar.

There are countless Yale researchers in addition to my group memebers whose advise,

assistance, and support was essential to my progress. I will try to name them all, but so

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many people have been helpful throughout time that I apologize in advance if I forget

some. In my eyes Thomas Boone and Robert Koudelka were always the ideal graduate

students and have always been a great example for me and both workers and friends.

Pauline Wyrembak single-handedly made functionalization possible by providing every

molecule I needed. James Hyland helped minimize the drudgery of the Yale cleanroom

and seemingly provided key suggestions every day and Christopher Tillinghast and

Michael Young allowed that advice to be useful by keeping the cleanroom up and

running (and also gave many critical suggestions themselves). Doctor Kathryn Klemic in

addition to James Bertram, Steven Jay, Benjamin Boese, and Alexis de Kerchove assisted

with (and oftentimes did) crucial studies that made some papers possible. Doctors Luigi

Frunzio, Jun-Fei Zheng, Hironori Tsukamoto, George Cui, Zhenting Jiang, and Sharon

Cui and Matthew Reese and David Schuster gave me many processing and metrology

tips throughout the course of the work. Tania Henry, Manisha Gupta, Sara Hashmi,

Joseph McManis, Yanxiang Liu, Weipeng Li, Chun-Chen Yeh, Joseph Schreier, Tolga

Kaya, Dechao Guo, Bozidar Marinkovic, Ayse Kose, Jason Hoffman, Liyang Song,

Miaomiao Wang, Chad Rigetti, Veronica Savu, Ning Li, and Sun Il Shim all look great in

bunny suits and helped make working in the cleanroom almost fun. I also had many

fruitful discussions that helped both the work succeed and time pass with Drs. Peter

Fong, Jeremy Blum, and Hung Te Hsieh in addition to Millicent Ford, Jeffrey

McCutcheon, Sara Royce-Hynes, Andrew Sawyer, Jennifer Saucier-Sawyer, Thomas

Chia, Andrew Barthel, Richard Torres, Zai Yuan Ren, and Qian Sun.

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Many researchers and companies outside Yale played significant roles in my project.

Robert Ilic, Daron Westly, Meredith Metzler, and Vincent Genova of the CNF taught me

real processing and their help and suggestions made the sensor fabrication possible.

Doctor Ling Xie and John Tsakirgis of the Harvard Cleanroom provided much-needed

fabrication assistance when the Yale Cleanroom was down. Doctors Emanuel Tutuc and

Robert Klie made and measured samples, respectively, that added incredible dimensions

to my work. Alec Flyer made some of the most critical functionalization suggestions that

enabled the work to continue. Additionally, a number of companies routinely went well

out of their way to help me meet my deadlines: CAD Art Servies, Benchmark

Technologies, nTEK, and Innovion.

The support of Yale’s staff also made the projects possible. Many of the apparatuses on

or in which experiments were run were built by Vincent, Nick, or Russel Bernardo. No

progress towards academic completion would ever occur without Cara Gibilisco and no

reagents or supplies would ever show up without the dedication of Vivian Smart, Arlene

Ciociola, Patricia Kakalow, Deanna Lomax, Elna Godburn, Senen Antunez and Susan

Johns. And the company of the Becton custodial staff at all times of the day and night

always helped to keep me going.

Additionally, I owe a huge debt of gratitude to Dean Paul Fleury, Claudia Merson, and

Bridget Calendo for making the Yale Engineering Futures in Science Research

Fellowship (YEFSRF) a reality and to them and Prof. Levene, Dr. Joanna Price, and

Steven Jay for continuing it. And I am very thankful to the students in my classes for

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supporting me as a TA while I learned the ropes and for (mostly) doing great work that

made my life incredibly easy.

And since altruism isn’t always the name of the game, I owe a huge debt of gratitude to

all the Yale Office of Cooperative Research employees, especially James Boyle.

Without the constant support of my family and friends I never could have dealt with the

(constant) setbacks and the eventual success would mean nothing. Words truly can’t

express how lucky I feel to have had them there every step along the way. My Mom and

Dad started me in this game and, man, do I love it—and what other parents would also

serve as the final evaluator of all papers? The constant love and support of (and interest

in my work) my Grandma and Grandpa, my Uncle Don and Aunt Antje, and my cousins

Bobby and Elizabeth, mean more than I can ever express. My brother, Alan, is the best

brother a guy could ever ask for and my best friend and I can’t wait to get to Boston in

good part because he’s there. My fill-in-something-here, Laura, was there every step

along the way and made me who I am today as both a person and a scientist—nearly

every piece of data here was taken with her on the phone or in my office and most

definitely in my heart; the last datafiles, named “tnxljg__” say it all. And the friendship

and support her parents, Mr. and Mrs. Greer, both means and has taught me more than I

can explain. My best friends James, Steve, Mike, Rob, Park, Pauline, and Jen D, kept me

going day-in and day-out and made grad school one of the best experiences of my life

outside the lab as well as in it. And the friendship and support of Rachael and Sarah Mc,

along with Jeremiah, Cutch, BD, Zak, Vip, Cogs, Fong, Tarek, Tom C, Andy, Rick,

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Marc, Raul, Jan, Andy S, Dwayne, Chu, Rasika, Tom B, Rob K, Jimmy, Diego, Bill,

Ashley, Elnaz, Tara, Carey, Julie, Sara, Rachel, Lauren H, Amy, Jen G, Jenny, Giggles,

Vomit, Chillable, Stace, Erin, Vivian, Rutkow, Flyer, Cole, Moral, Dan, Jesse, Goldy,

Lusty, the rest of the jellydonut crowd, and everyone else has made time fly. Thank you!

And I also thank Gourmet Heaven for serving a spectacular sandwich just about every

other night for the past two-and-a-half years, GPSCY and Thai Taste for Thursday nights,

and Anna Liffey’s and Solo cups for Fridays.

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Contents

List of Tables …………………………………………………………………….. 15 List of Figures ……………………………………………………………………. 16 1 Introduction ……………………………………………………………… 18 References …………………………………….……..……………. 27 2 Theoretical Considerations …………………………………………….... 39 2.1 Importance of Device Scaling on Sensitivity ...……........................ 39 2.2 pH Response …………………………...……………..…………… 41 2.3 Functionalization and Molecular Binding Considerations ……..…. 44 2.4 Chamber Design and Solution Exchange Considerations ………… 49 2.5 Debye Screening Considerations ………………………………….. 54 2.6 Conclusions ………………………………………………………... 56 References …………………………………….……..……………. 57 3 Nanobar Fabrication and Characterization …...……………………….. 61 3.1 Nanobar Fabrication ……..………………………………………... 61 3.2 Nanobar Characterization …………………………………………. 68 3.3 Conclusions ……………………………………………………….. 72 References …………………………………….……..……………. 74 4 Functionalization Techniques for Protein and DNA Conjugation ….... 79 4.1 Introduction ……………………………………………………….. 79 4.2 Oxidative Electropolymerization-Based Functionalization ………. 80 4.3 Electrically-Directed Silicon Functionalization …………………... 86 4.4 Silicon-Specific, Non-Electrically Directed Functionalization …… 88 4.5 Non-Silicon-Specific, Non-Electrically Directed Functionalization 91 4.6 Conclusions ……………………………………………………….. 92 References …………………………………….……..……………. 93

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5 Nanobar Sensing ……………………………………….………………… 99 5.1 Introduction ……………………………………………………….. 99 5.2 Unfunctionalized NB Sensing …………………………………….. 100 5.3 Unfunctionalized NB Sensing of Specific Cellular Responses …… 105 5.4 Silicon-Specific NB Functionalization ……………………………. 112

5.5 Nanobar Sensor Characterization …………………………………. 116 5.6 Nanobar Sensing of Unlabeled Proteins and DNA ………………... 125 5.7 Conclusions ……………………………………………………….. 130 References …………………………………….……..……………. 131 6 Conclusions ………………………………………………………………. 139 References …………………………………….……..……………. 142 Appendix I: Functionalization Methods ………………………………………... 144 Appendix II: Sensing Methods ………………………………………………….. 168 Appendix III: Nanowire-Field Effect Transistors ……...……………………… 181

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List of Tables Table 2.1 …………………... 56 Table 4.1 …………………... 90

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List of Figures Figure 2.1 …………………. 40 Figure 4.9 ..………………... 90 Figure 2.2 …………………. 46 Figure 4.10 ………………... 92 Figure 2.3 …………………. 50 Figure 5.1 ..………………... 101 Figure 2.4 …………………. 52 Figure 5.2 ..………………... 103 Figure 2.5 …………………. 53 Figure 5.3 ..………………... 104 Figure 3.1 …………………. 63 Figure 5.4 ..………………... 107 Figure 3.2 …………………. 65 Figure 5.5 ..………………... 108 Figure 3.3 …………………. 66 Figure 5.6 ..………………... 110 Figure 3.4 …………………. 67 Figure 5.7 ..………………... 112 Figure 3.5 …………………. 68 Figure 5.8 ..………………... 113 Figure 3.6 …………………. 70 Figure 5.9 ..………………... 114 Figure 3.7 …………………. 71 Figure 5.10 ………………... 115 Figure 3.8 …………………. 72 Figure 5.11 ………………... 116 Figure 4.1 …………………. 81 Figure 5.12 ………………... 117 Figure 4.2 …………………. 82 Figure 5.13 ………………... 118 Figure 4.3 …………………. 83 Figure 5.14 ………………... 119 Figure 4.4 …………………. 84 Figure 5.15 ………………... 120 Figure 4.5 …………………. 85 Figure 5.16 ………………... 122 Figure 4.6 …………………. 87 Figure 5.17 ………………... 123 Figure 4.7 …………………. 88 Figure 5.18 ………………... 124 Figure 4.8 …………………. 89 Figure 5.19 ………………... 126

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Figure 5.20 ..………………. 126 Figure 5.22 .……………….. 128 Figure 5.21 ..………………. 127 Figure 5.23 .……………….. 129

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Chapter 1: Introduction

The importance of sensing chemicals and biochemicals in disparate field environments

cannot be underestimated in today’s world [1-13]. Sensing small numbers of molecules

exactly, effectively, and expeditiously is paramount for army defense and homeland

security [1-3], clinical screening and diagnoses [4-8], drug discovery [9,10], and basic

research assays [7,8,10,11]. For each of these applications, it is highly desirable that an

ultrasensitive, small, versatile, robust, low-power, easy-to-use, inexpensive, variable-

sensitivity sensor be created [1,4,11-13]. In spite of the critical demand for such a sensor,

no single technology has yet shown the capability to meet all of these requirements [11-

29].

Sensors can be roughly grouped into two major categories: those that identify molecules

spectroscopically [30-35], or those that use a direct or indirect means of sensing a

specific molecule [36-47]. The detection of small molecules is readily achieved with

sensors in the first category and, due to the success of such technologies, many are now

being scaled down. In spectroscopic approaches, the aforementioned desirable

requirements have stimulated the development of miniaturized gas chromatographs [32],

Fourier transform infrared spectrometers [33], mass spectrometers [32,34], and solid-state

gas-phase sensors [37,40,41]. However, many of these techniques face lower limits on

size due to scaling limitations and lower limits on power dissipation because of the

fundamental physical phenomena by which they operate [12]. Furthermore, these

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methods are generally incapable of sensing large molecular species, such as proteins and

viruses [11-16].

In contrast, the macromolecular sensing required for biological research and clinical

applications is predominantly achieved by specific-molecule detection methods [39-44]

because these molecules are often too complex for spectroscopic recognition [11-16].

Specific-molecule detection techniques can be further divided into those solely reliant

upon chemical means for detection [43,44], and those that convert the chemical signal

into an electrical one [39-42]. Methods in the former category—such as enzyme-linked

immunosorbent [43] and immunoblotting [44] assays, or fluorescence/radioisotope/dye

labeling [45]—are significantly more sensitive but are of marginal utility outside the

laboratory environment (with some exceptions, such as home pregnancy tests) [11-16].

As sensing in disparate field environments becomes increasingly critical, development

has begun on a number of label-free, specific-molecule technologies for converting

chemical signals to electrical ones without the need for complex sample preparation [17-

29]. The most established approaches are metallic potentiometric [46] and amperometric

[24] sensors, which sense ions electrochemically in solution; solid state [37,47]

conductance sensors, which sense gas-phase ions and small molecules by measuring the

absorption-induced conductance change of a material; and chemical field effect

transistors (chemFETs; a type of ion sensitive field effect transistor, ISFET), which sense

ions in solution by charge modification of the gate of a FET [42,48]. Though each of

these techniques has been successful for various applications—metallic potentiometric

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and amperometric sensors for small molecules and ions [48,49], solid-state gas sensors

for chlorine and fluorine [37], and chemFETs for glucose and other small molecules

[48,50,51]—none are very sensitive (detection limits are generally parts per million).

One method that has successfully overcome this sensitivity barrier and currently serves as

the standard for unlabeled sensing is surface plasmon resonance [52]. In this approach,

an antibody of the protein to be sensed is attached to a thin gold film. The angular

reflection of a laser beam off the backside of the gold is dependent on the local dielectric

constant; binding of the protein changes the dielectric constant, and thus deflects the laser

beam. However this technique has not met with success outside research environments

due to its price, size, high-power, and mechanical alignment issues.

The lack of a scalable, inexpensive, label-free sensing technology has resulted in a

number of new methods that are currently under development. A few of note are

cantilever-sensors, which sense the binding of a desired molecule to a thin catilever by

measuring the deflection of the beam with a laser or piezoresistive elements [19,53];

fiber-optic sensors, which sense the binding of nanoparticle-linked antibodies to a protein

after that protein binds a specific antibody conjugated to a fiber-optic strand [23];

waveguide sensors, which sense the presence of a specifically bound protein to an

antibody film on a chip between two waveguides [21,22]; and nanoparticle-solution

sensors, in which the binding of a specific protein to an antibody-coated nanoparticle

results in the attachment of a second nanoparticle, resulting in a color change [20,54,55].

Though each of these methods has shown promise, none simultaneously meets the

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requirements in terms of sensitivity, versatility, and power consumption. Only the

cantilevers enable label-free sensing, a key requirement for many applications [1,3-13].

Due to these shortcomings, researchers have returned to the solid state condutance

sensors and chemFETs and sought to increase their sensitivity and versatility by reducing

the lateral dimensions of the devices in order to maximize the effect of surface charge on

device transport. When modified indium oxide (In2O3) FET sensors are scaled down to a

quasi-one-dimensional single-crystal nanowire (NW) [59,60], the resulting device can

achieve a NO2 sensitivity of ~1 ppb [61,62] as compared to ~1 ppm for larger devices

[56-58] , a three-order-of-magnitude increase in sensitivity. The cause of this sensitivity

increase is the maximized surface area-to-volume ratio of the NW-FET: the geometry of

the NW restricts current flow to a much thinner region than in the bulk, and thus

adsorbed molecules on the surface exert more significant effects [63-65]. Though

multiple successful demonstrations have been performed with NWs [66-70], carbon

nanotubes (CNTs) [71,72], and electrospun nanofibers [73], the drawback of this sensing

approach lies in the lack of versatility: only small, gas-phase molecules can be

distinguished. By configuring NW-FETs as solution-phase sensors, a nanoscale

chemFET is created, which is the focus of this work.

Before discussing one-dimensional chemFETs, the bulk chemFET sensing mechanism is

discussed. As described above, this device mimics a traditional FET with ions serving as

the gate [42,50]. In a FET the gate potential controls the channel conductance: for a

given source-drain voltage (VSD), modulating the gate voltage (VGD) will change the

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source-drain current (ISD) [74]. The ratio of the source-drain current to the gate voltage is

defined as the transconductance [74]. In order to sense a neutral molecule, an enzyme

that produces ions as a result of catalyzing a reaction with the neutral molecule is tethered

to the surface of the device, and the generated ions create a gate potential change which

modulates the FET ISD. For example in a glucose sensor, glucose oxidase produces

gluconic acid (plus hydrogen peroxide) which dissociates into gluconate plus a proton*,

and the resulting decrease in pH (increase in hydrogen ion concentration) modifies VGD

[75]. The shortcomings of a chemFET are patent: the sensitivity is limited (because of

the large channel), the versatility is low (devices can only be sensitive to a single

chemical species and must be physically isolated), and enzymatic activity is required for

device functionality (so robustness and shelf-life are important concerns).

Scaling the chemFET to quasi-one dimension by using a semiconducting NW, first

demonstrated by Lieber and coworkers [76], has the potential to produce a label-free

sensor capable of overcoming these problems. As with the quasi-one-dimensional solid

state conductance sensors, the NW increases the surface-to-volume ratio, thus increasing

device sensitivity to the point that charged molecules can be directly sensed, thereby

elminiating the reliance on enzymatic activity. By tethering an antibody/aptamer [77,78]

or single stranded- (ss)-DNA [77] to the surface of the NW-FET, the presence of a

specific protein [79-83] or complementary ss-DNA [18,83-85] can be sensed by the

change in NW conductivity. Furthermore, RNAses that self-cleave when bound to a

specific ligand could be used to sense neutral molecules [86]. It is worth noting that we

* In more advanced systems, a platinum electrode is utilized to oxidize the hydrogen peroxide, thereby producing two additional protons per original glucose molecule [75].

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chose not to pursue employing CNTs as biosensors in spite of prior claims [87,88] for

two primary reasons. First, previous work has shown that the metal-CNT Schottky

barrier contacts, rather than the CNTs themselves, are responsible for the observed

molecule-induced effects [89], eliminating many of the size scale benefits. Second,

current production methods cannot produce uniform semiconducting CNT material—

only two-thirds are semiconducting, with the remaining one-third metallic—and the tube

bandstructure is dependent on diameter and chirality, rendering deterministic device

design and realization impractical [90,91].

As previously discussed, chemFETs are inherently low-power, easy-to-use, and

inexpensive [42,50]. Nanowire-FETs are ultrasensitive [18,76,83], and by incorporating

multiple NWs sensitized to different molecules on the same chip, versatility in sensing is

achieved [80]. Lastly, by adding a backgate for tuning the semiconductor to regions of

greater or lesser transconductance [74], variable sensitivity can be achieved. Thus the

NW-FET sensor (hereafter referred to simply as a NW-FET) has the potential to meet the

seven sensing requirements outlined at the outset of this chapter. In spite of this promise,

NW-FET-based sensing has yet to become an established technique, primarily due to a

lack of available devices caused by the variability in material, and issues of hybrid device

fabrication.

The goal of this thesis was to create a NW-FET approach that would overcome these

obstacles and thereby enable NW-FETs to be a robust, reliable technology. There were

three primary steps in this process: first, creating high-quality NW-FET devices; second,

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developing surface functionalization techniques for robust bioconjugation to the NW-

FETs; and third, unambiguously demonstrating label-free, specific NW-FET sensing.

Theoretical considerations are discussed in Chapter 2; device processing and

characterization are presented in Chapter 3; surface functionalization is considered in

Chapter 4; and sensing results are demonstrated in Chapter 5.

Initial attempts at creating devices suitable for sensing utilized grown GaN NWs [92-93].

We developed a high-throughput method to fabricate and characterize devices [94,95] but

found that even after optimization of growth parameters, the GaN NW material quality

was unacceptable[96]. We subsequently attempted InN [97] and In2O3 [98] NWs, but

again the material quality was suboptimal. These results, in conjunction with the yield

loss due to the inherent randomness of this method led us to pursue a different, novel

approach to creating NW-FETs.

We developed a “top-down” technique [18,85] for device fabrication that enabled

nanoscale FETs, termed nanobars (NBs)† to be realized with traditional optical

lithographic methods [99]. This approach uses crystalline silicon-on-insulator material

[18,85,100] for NB fabrication, eliminating the need for poorly understood grown NW

material, while simultaneously eliminating the need for grown NW alignment [99].

With devices realized, we next created a technique for sensor-specific, selective

functionalization of consecutively arrayed devices [101], necessary for achieving high-

† It should be noted that while devices fabricated with “top-down” lithographic techniques are termed nanobars (NBs) throughout this document, we refer to them as nanowires or nanowire-like devices in peer-reviewed publications.

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density multiple-molecule sensing [80,83]. In spite of its success functionalizing oxide

semiconductors and metals, this method has not yet successfully worked for NB

functionalization. Device-specific functionalization utilizing previously demonstrated

approaches [102-103] also proved unsuitable, leading us to use an established selective—

but not device-specific—method [104,105] and later a more general technique [76,106]

for NB functionalization [99,107].

To correctly characterize sensor performance, we designed a sensor fluid-exchange

system to overcome diffusion limitations present in previously utilized systems [99,108].

We demonstrated that unfunctionalized NBs can perform as highly sensitive pH

detectors, and that sensitivity scales with dimension and carrier density [99]. These

sensors were then used in a novel application, as detectors for stimulus-induced live

cellular responses; we demonstrated that the sensors could be utilized to discriminate

specific cell types from samples containing as few as ~200 active cells [99,109].

We characterized functionalized NB sensitivity using the biotin-avidin/streptavidin

system [110] and showed that biotinylated NBs sense the presence of avidin and

streptavidin based on their intrinsic charge. We further demonstrated the ability of such

devices to robustly detect streptavidin at concentrations as low as 10 femtomolar (10 fM,

10-14 M) [99], with a noise floor < 0.1 fM. Complementary sensing with p- and n-type

devices [74], necessary for on-chip error detection [18,81], was demonstrated with

streptavidin [99], further illustrating the potential utility of the NBs. We also studied the

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sensor response [107] to solution-phase ionic charge screening (Debye screening) [111] ,

characterizing this critical dependence for the first time in such systems.

Lastly, we studied the ability of protein- and DNA-functionalized NBs to sense specific

proteins and DNA oligomers, respectively. We used devices selectively functionalized

with antibodies for immunodetection at 100 fM concentrations [99] and others

functionalized with DNA oligomers to measure specific DNA hybridization at 10

picomolar concentrations [107]. We demonstrated Debye screening with DNA-

functionalized devices and used our understanding of this principle to interrogate protein

denaturation (unfolding) [77] with NBs [107], a novel application for these devices.

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References

1. Carrano, J. in Public Release #2435 (DARPA, 24 June 2004).

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Chapter 2: Theoretical Considerations

2.1 Importance of Device Scaling on Sensitivity

We first discuss the importance of dimensional scaling on FET sensitivity to bound

surface charge [1]. We define device sensitivity as the change in device current (ΔID)

induced by the binding of molecular species, normalized by the initial device current

(ID,0) for constant source-drain voltage (VDS):

Sensitivity ≡ DSDS VD

DD

VD

D

III

II

0,

0,

0,

−=

Δ . (2.1)

The device current normalization is necessary to compare devices with different

dimensions [2-4]. We model the NW-FET as a cylinder, thus the device current can be

written as [3,4]:

DSD VqnLRI μπ

0

2

= , (2.2)

where R and L are the NW radius and length, respectively (Fig. 2.1); n0 is the initial

carrier concentration; q is the elementary charge; and μ is the carrier mobility.

39

R

L

Backgate

R

L

Backgate

Figure 2.1 | Schematic of a backgated NW of radius (R) and length (L). The NW is yellow, the oxide is blue and the backgate is silver.

The initial carrier concentration for this geometry is given by:

( )LRqVVCn tG

20 π−

= , (2.3)

where C is the NW-backgate capacitance, VG is the backgate voltage, and Vt is the

threshold voltage. The binding of charged species will affect the threshold voltage,

producing a change in the carrier concentration, Δn [3]:

LRq

VCn t2π

Δ=Δ , (2.4)

where Δn = n – n0. Defining the surface density of bound species as Ns, Eqn. (2.4)

becomes

sNR

n α2−=Δ , (2.5)

40

where the charge-transfer coefficient α denotes the number of electrons captured by the

bound molecule. Combining this result with the sensitivity definition in Eqn. (2.1) gives

00,

2nN

RII s

VD

D

DS

α⋅=

Δ . (2.6)

Thus, the NW-FET sensitivity is strongly dependent on device diameter, scaling with the

inverse of the NW radius, for a device of a given length and a constant space charge

density. This demonstrates the importance of minimizing device size in order to

maximize sensitivity, while maintaining high-quality material properties and device

transfer characteristics.

2.2 pH Response

The protonation and deprotonation (and double-protonation) of the silanol groups of

silicon oxide enables properly configured FETs to serve as hydrogen ion sensitive FETs,

or ISFETs [5-7]. We now apply this concept to NW FETs, and explore the dependence

of the electrostatic potential at the device surface (ψ0) on changes in solution pH,

following Ref. 7.

Surface silanol groups can be deprotonated (negative), protonated (neutral), or doubly-

protonated (positive):

41

SiO– + 2HB+ SiOH + HB

+ SiOH2

where HB+ are hydrogen ions in the bulk of the solution. The equilibrium conditions are

SiOH

HSiO

as

aK

ν

ν +

= and 2SiOH

HSiOH

bs

aK

ν

ν +

= , (2.7)

where the Ks are dimensionless constants, vi is the density of surface states, and is

the activity of protons directly at the surface, which is related to the Nernst equation

by

+sH

a

+BH

a

, (2.8) kTqHH

eaaBs

/0ψ−+= ++

where k is the Boltzmann constant and T is the absolute temperature. The surface charge

density (σ0) is the product of the elementary charge and the difference between the

number of negatively and positively charged groups per unit area. Defining the number

of sites per unit area as Ns, the surface charge density is

⎟⎟

⎠

⎞

⎜⎜

⎝

⎛

++

−=

++

+

2

2

0

ss

s

HHbba

baHs aaKKK

KKaqNσ . (2.9)

42

The change in pH from the pH at the point of zero charge (pHpzc) is termed pHs and

differentiating the surface charge density with respect to this value gives the intrinsic

buffer capacity (βint)

( ) +

++

++

++

++−=−=

s

ss

ss

HHHbba

baHbaHbs

s

aaaKKK

KKaKKaKqNq

pH3.2

422

22

int0 β

δδσ . (2.10)

An equal and opposite charge must exist in the electrolyte near the semiconductor surface

to counter the charge buildup on the device. In order to describe the electrolyte side of

this double layer, the Gouy-Chapman-Stern model (which involves a diffuse layer of

solution charge starting at a distance x2 from the surface) is used. The charge in this

layer, σDL, must be equal and opposite to the surface charge density [7,8]

( ) 022/10

00 2sinh8 ψφεεσσ irDL C

kTzqnkT −=⎟

⎠⎞

⎜⎝⎛−=−= , (2.11)

where εr is the relative permittivity of the solution, ε0 is the permittivity of free space, ψ2

is the potential at x2, n0 is the number concentration of each bulk ion, z is the ionic

charge, and Ci is the integral capacitance. The electrolyte’s differential capacitance

represents its ability to store charge in response to changes in the electrostatic potential

and is defined as [7,8]

( )( ) ( )( )( )( ) ( )( ) ( )( )kTzqkTnqzx

kTzqkTnqzCrr

rdif

2/cosh/2/12/cosh/2

22/1022

002

22/1022

0

0

0

φεεεεφεε

δψδσ

+== . (2.12)

43

The two sides of the double layer are then combined, giving

difss C

qpHpH

int0

0

00 βδδσ

δσδψ

δδψ

−== , (2.13)

where the relation between pHs and pHB is given by the Nernset equation. Substituting

this [Eqn. (2.8)] into Eqn. (2.13) yields

( )⎟⎟⎠

⎞⎜⎜⎝

⎛

+−=

int2

0

3.2113.2

βδδψ

qkTCqkT

pH difB

. (2.14)

Thus, changes in the solution pH (pHB) directly affect the electrostatic potential at the

surface, ψ0. Taken together, Eqns. (2.4) and (2.14) show that the change in NW-FET

electron concentration will be directly proportional to the change in the electrostatic

potential and, using Eqn. (2.6), it follows that NW-FET (and, similarly, NB) sensitivity to

solution pH changes should scale with the inverse of device radius.

2.3 Functionalization and Molecular Binding Considerations

Surface functionalization and the resultant molecule-surface interactions must be

considered in order to determine the sensitivity limit of NB sensors. Terming the bound

44

molecular species the receptor and the solution-phase molecule the ligand, it is critical to

understand the number of receptors present, the number of ligands introduced, and the

resultant potential for binding events to occur. This section treats this problem by

considering only functionalized surface area and the next section adds fluid flow

considerations.

To the best of our knowledge, all previous silicon NW-FET sensing studies relied on

hydroxyl-reactive schemes for device functionalization [9-15]. These approaches require

the formation of a covalent bond between a surface oxygen atom (present at the silicon

oxide surface) and the silicon atom in the functionalization molecule [16]. This reaction

mechanism will thereby functionalize all silicon oxide surfaces (and most oxide surfaces

in general [16]); since most NW-FET device embodiments [9-15] use an underlying

silicon oxide layer, the entire wafer surface area—not only the NW-FETs—will be

functionalized. Thus, it is imperative to consider binding competition in order to assess

the number of molecules that will reach the NB surface.

We begin by determining the relative surface area of a NB (yellow, Fig. 2.2) to that of the

NB plus the exposed underlying oxide (yellow and aqua regions, Fig. 2.2). On each die,

the NB surface area‡ is 3 × 107 nm2, whereas the total exposed chip surface area§ is ~8 ×

1011 nm2. Thus, the ratio of exposed oxide to device surface area is ~25,000 : 1.

‡ For a typical NB, w = 50 nm, L = 20 μm, and t = 40 nm. Since we wish to determine the total surface area, we convert the thickness to the sidewall length, s ~ 50 nm, using θ = 54.7º for the angle between the (100) and (111) planes [17] (see Chap. 3 for device fabrication explanation and details). Thus, for a single 2-point device, the surface area is 3 × 106 nm2. However, each die contains four devices, each with four or six leads, so there is approximately tenfold this device surface area exposed per die, 3 × 107 nm2.

45

w

ts

L

θ

w

ts

L

θ

Figure 2.2 | Schematic (not to scale) of a NB device (yellow) on an oxide surface (aqua). The NB length (L), width (w), thickness (t), and sidewall length (s) are depicted. The angle θ = 54.7º is made between the (111) and (100) silicon planes.

The model biotin-avidin/streptavidin system [18,19] was used to characterize NB

sensitivity to bound macromolecular charge. Streptavidin and avidin bind with similar

affinity to biotin with a dissociation constant (KD) ~ 1 × 10-15 M [18]; the KD of a

ligand/receptor interaction is defined as the ligand concentration at which half of the

receptors are occupied, thus higher affinity reactions have lower KD values. Since

streptavidin and avidin bind biotin with similar affinity and are comparable in size

[18,20,21], the remainder of this section will only treat the case of streptavidin binding.

This protein has previously been shown to form densely packed monolayers on

biotinylated surfaces in an array with each protein occupying ~5 × 5 nm2 [20,21]. Based

on surface area considerations, ~1.2 × 106 streptavidin molecules can bind the

biotinylated NB surface whereas ~3.2 × 1010 can assemble across the entire oxide

surface.

§ On-chip reservoir fabrication leaves a ~0.5-1 mm-diameter region of the die exposed (the tubing that creates the reservoir is ~2.0 mm in diameter but epoxy puddling creates a ~0.5-1 mm rim) so the total exposed oxide surface area is at most ~8 × 1011 nm2.

46

At a streptavidin concentration of 10 fM, the lowest used in our sensing measurements

[19], a 100 μL volume contains ~6 × 105 molecules. At this (and higher) concentrations,

each streptavidin molecule can be assumed to nonreversibly bind the biotinylated surface

due to KD ~ 1 fM. Additionally, the KD of a surface-bound-receptor/ligand interaction is

well below that of the solution-phase KD for the same species due primarily to the

enhancement of the ligand concentration near the surface as a result of bound

receptor/ligand pairs [22-24]. Thus, the nonreversible binding assumption is valid for a

10 fM streptavidin concentration.

Because of the relative surface area considerations, a functionalization scheme that

biotinylates all oxide surfaces yields a ~1/25000 chance that a streptavidin molecule will

bind specifically on the NB. Assuming all molecules bind with equal affinity (neglecting

potential complications of nanoscale seeding affects [25]), a binomial distribution can be

used to estimate the probability of the number of molecules binding on the NB:

knk ppknk

npnkf −−−

= )1()!(!

!),;( , (2.15)

where n is the number of molecules (6 × 105), p is the probability of NB binding

(0.0004), and k is the number of molecules bound to the NB. Using these values, it is

most likely that k ~ 240 streptavidin molecules will bind, which represents only ~2%

coverage of the NB surface area. Thus it is clear that nonspecific functionalization

undermines the benefits of nanoscale-induced sensitivity by preventing effective

molecule-sensor binding. This finding led us to pursue a silicon-specific

47

functionalization technique, which was employed for concentration critical measurements

[19].

The case of specific protein-protein recognition with selectively functionalized NBs is

considered next, using the immunoglobulin G (IgG) system [27]. The ~10 × 10 nm2

[18,26] molecular footprint of anti-IgG antibodies (the receptors) enables at most ~3 ×

105 molecules to bind on all NB surfaces. It should be noted that the maximum number

of bound IgG molecules (the ligands) is expected to be significantly lower due to the

shielding of receptor binding sites due to the random attachment of the receptors during

covalent functionalization [24]—only antibodies with accessible F(ab’)2 domains will

successfully bind antigens [27]. At the 100 fM IgG concentration used in our sensing

measurements [19], a 100 μL volume contains ~6 × 106 molecules. The solution-phase

KD of anti-IgG/IgG interaction is ~10-9 M [27], implying that only ~1 in 5 × 104 or ~120

molecules will be bound**. The number of bound IgGs should be significantly greater

because of the decrease in KD at the sensor surface [22-24]. Thus, provided a silicon-

specific functionalization approach is utilized, it can be assumed that IgGs will bind to all

exposed anti-IgG receptors on the NBs.

Although specific functionalization is desirable for maximum sensitivity, there are

numerous applications where ultrasensitivity is unnecessary, and thus a nonspecific

functionalization approach [28] can be used. Because previous considerations implied a

decrease in sensitivity by ~1/25000, we reduced the available silicon oxide surface area

** Nonreversible binding can be assumed for this system on timescales of ~1-10 mins [24].

48

by selective masking [28], and achieved a 1/333 relative ratio††. We now apply this

approach to a test system, complementary DNA pairing, and demonstrate that a 10 pM

concentration is sufficient for NB sensing. One-hundred microliters of 10 pM probe

single stranded- (ss)-DNA (complementary to a surface-bound ss-DNA) was added, thus

~3 × 109 molecules were present. Since DNA hybridization can be assumed to be

nonreversible at room temperature‡‡, there should be a ~33% coverage of the NB surface;

assuming a DNA 20-mer footprint of ~2.5 × 2.5 nm2, it follows that ~1.6 × 105 molecules

of ~4.8 × 106 possible molecules will be bound.

Taken together, these data demonstrate that silicon-specific functionalization approaches

are critical to achieve femtomolar ligand detection with NB sensors, though nonspecific

functionalization is adequate for sensing picomolar ligand concentrations.

2.4 Chamber Design and Solution Exchange Considerations

In the above section we assumed that all ligands present after solution exchange would be

available to bind to the sensor surface. Previous studies with NW-FET sensing relied on

microchannels [29] for solution exchange [9-15] but theoretical studies suggested that

mass transport [30] in such systems would be diffusion-limited due to the laminar flow †† Thus, we protected the oxide surface with layer of photoresist and opened ~50 × 50 μm2 vias over active devices, leaving a functionalized surface area of ~1 × 1010 nm2 per die. ‡‡ The energy of a hydrogen bond is 1-5 kcal/mol [30], there are 2.5 hydrogen bonds per DNA basepair (2

for A-T, 3 for G-C), and we used a 20-mer, so: 37)300)(987.1()20)(5.2)(101(

10~3

−×−

= eKD .

49

through the microchannels [31,32]. We first apply the analytical solutions obtained by

the authors in Refs. 31 and 32 to the case of NB sensors and show that microfluidic

systems are impractical for nanosensors. We then discuss the theory behind our fluid

handling design and demonstrate that this setup is ideal for molecular transport to the

NBs.

The accumulation of molecules on the surface of a NW (approximated as a hemicylinder

of length L and radius a) based on solution flow through a microchannel above the device

(Fig. 2.3) is given by [31]

∫∞ −

+−

=0

320

20

0

)()(14)(

2

udu

auYauJeCLNtN

tDuA

π, (2.16)

where J0 and Y0 are Bessel functions, NA is Avogadro’s number, D is the diffusion

coefficient, the C0 is the ligand concentration.

Figure 2.3 | Schematic (not to scale) of a NW (red) in a flow channel. The arrows indicate the direction of flow.

Equation (2.16) is solved analytically in Refs. 31 and 32 to yield the molecular flux to the

NW surface:

50

( ) ( )⎟⎟⎠

⎞⎜⎜⎝

⎛−

−⎟⎟⎠

⎞⎜⎜⎝

⎛−

=s

s

sA Pn

PPn

CDLNJll 885.4

09266.01885.4

20

π , (2.17)

for Ps < 1, where

2

26DwhQWPs = . (2.18)

Here, Q is the volumetric flow rate, w is the width of the microchannel, h is the

microchannel height, and W = πa [31]. Using D = 150 μm2/s [31], L = 20 μm, a = 25

nm, w = 500 μm, and h = 100 μm to best approximate the NB geometry, we plot the

J(C0) for varying Q in Fig. 2.4. Flow rates of 0.1-10 μL/min are typical for

microchannels; Q = 8.3 μL/min is the flow rate used experimentally in Ref. 9 and Q =

3000 μL/min is the flow rate used experimentally in our work in Ref. 19. The dashed

lines in Fig. 2.4 account for nonspecific functionalization (ie. molecules nonreversibly

bind with equal affinity to all oxide surfaces), the case in Ref. 9, assuming a channel

length of 5 mm. The pink “X” in this figure represents the flow rate and lowest

concentration (25 pM) used by the authors in Ref. 9 for streptavidin sensing. Although

Fig. 2.4 indicates that ~100 min will transpire before the first streptavidin molecule binds

the nanosensor, the authors in Ref. 9 observed a sensor response (from a Si NW-FET)

instantly after the streptavidin flow began, with the signal reaching its maximum value

within 10 sec. This discrepancy (highlighted by the authors in Ref. 31) has yet to be

explained in the literature. However, these considerations indicate that microchannels are

51

ineffective at bringing sufficient numbers of molecules to nanosensor surfaces and led us

to design a different setup for solution exchange.

10-15 10-14 10-13 10-12 10-11 10-10 10-91E-6

1E-4

0.01

1

100

10000

1000000

1E8

1E10

1E12#

Mol

ecul

es/M

in

C0 (M)

XX

XX

Silicon-specificfunctionalization

Nonspecificfunctionalization

Ref. 9

Our work

10-15 10-14 10-13 10-12 10-11 10-10 10-91E-6

1E-4

0.01

1

100

10000

1000000

1E8

1E10

1E12#

Mol

ecul

es/M

in

C0 (M)

XX

XX

Silicon-specificfunctionalization

Nonspecificfunctionalization

Ref. 9

Our work

Figure 2.4 | Theoretical plot of the number of molecules per minute irreversibly binding to a representative NB surface in a flow channel versus ligand concentration. The flow rates are listed. The pink and purple X’s denotes the experimental parameters used by the authors in Ref. 9 and us in Ref. 19, repectively, for the lowest limit of streptavidin detection.

We hypothesized that we could overcome this diffusion limitation by creating a

macroscale solution chamber with a fluid supply tube perpendicular to the NB surface

such as that pictured in Fig. 2.5. These reservoirs were created by epoxying thin-walled,

~2 mm diameter PTFE tubing (pink) to the chip surface and by inserting thinner tubing

(0.5 mm ID, purple) to serve as the fluid supply and return (arrows). The solution input

tube was placed directly over the central region of the die. Alternatively, only a solution

input tube was used and excess liquid was wicked away. This system also enabled

52

continual mixing (equivalent to pippetting up-and-down) throughout the course of

sensing measurements.

aa

Figure 2.5 | a, Schematic of the solution chamber (~2 mm diameter) superimposed on an optical micrograph of a section of wafer containing multiple devices. Rigid, thin-walled tubing (pink) creates a reservoir into which softer, Tygon tubing (purple) serves as the fluid supply and return (arrows). b, Optical micrograph of a NB sensor array with fluid reservoir attached and source and drain contacted.

The flux of molecules to a surface is given by the mass transport equation:

020

2

Cudz

CdDJ zz +−= , (2.18)

where uz is the velocity in the z-direction. Since the solution flow is perpendicular to the

sensor surface, we hypothesized that convection and not diffusion would be the primary

determinant of mass-transport. In order to validate this, we calculated the Schmidt and

Reynolds numbers for the system [30]. The Schmidt number, defined as u/D, gives the

ratio of viscous to diffusive transport and is a property of the fluid/solute system. For

proteins in aqueous solutions, is number is ~104-105 [30]. The Reynolds number, u·d/v,

53

where d is the tube diameter and v is the kinematic viscosity, gives the ratio of inertial to

viscous forces and is system-specific [30]. A solution exchange rate of 50 μL/s (3000

μL/min) was used for sensing measurements, yielding a Reynolds number of 125 for the

0.5 mm-diameter input tube. Taken together, these values suggest that diffusion can be

neglected in this system due to the fact that the perpendicular convection will bring all

molecules directly to the sensor surface. Thus, we simplify Eqn. (2.18) to:

. (2.19) 0CuJ zz =

Because we are only considering flow in the z-direction and have neglected diffusion, we

must account for the fact that the NBs cover only 0.0015% of the cross-sectional area of

the inlet tube by multiplying the right-hand side of Eqn. (2.19) by this factor. We plot

J(C0) for Q = 3000 μL/min in Fig. 2.4 (solid cyan line). These data indicate that we have

overcome the diffusion limitation inherent in microchannels and have successfully

created a fluid-exchange system that can rapidly transport a sufficient number of

molecules to the NB surface to enable sensing within seconds.

2.5 Debye Screening Considerations

As described above, NW-FET and NB sensors work similarly to conventional chemical

field effect transistors (chemFETs) [5-7], sensing the presence of bound species by their

intrinsic charge [1,9-15,19]. When specific receptor molecules (ie. biotin, antibodies,

54

ssDNA) are conjugated to the NB surface in order to sense specific ligands, the ligands

are removed from the sensor surface by at least the length of the receptor, generally 10-

100 Å. Since the receptors are dissolved in the solution, an understanding of the

screening of molecular charge by dissolved ions (Debye screening) is paramount to

interpreting device results. The charge of solution-based molecules and macromolecules

is screened by dissolved ions: a negative species such as streptavidin or DNA will be

surrounded by positively charged ions due to electrostatic interactions. Beyond a certain

distance, termed the Debye length (λD), Coulomb interactions can be ignored because the

positively-charged cloud of ions will cancel out the negative charge inherent to the DNA,

rendering the species charge-neutral [33]. Thus, at distances beyond λD, the molecular

charge is effectively screened by the dissolved ions. For aqueous solutions at room

temperature, this length is given by

∑

=

iiiB

Dzl 24

1ρπ

λ , (2.20)

where lB is the Bjerrum length = 0.7 nm, ΣB i is the sum over all ion species, and ρi and zi

are the density (6.02 × 10 cm ) and the valence, respectively, of ion species i [ ]. In

our sensing measurements we used dilutions of phosphate buffered saline (PBS); these

dilutions were made relative to 1X PBS, which contains 150 mM NaCl, 3 mM KCl, and

10 mM phosphate salts (monobasic and dibasic). The calculated values of λ

20 -3 33

D for the five

solutions used in sensing measurements are given below in Table 2.1. These values show

that for functionalized NW-FET and NB measurements (those relying on a receptor-

55

ligand binding event), careful consideration must be given to buffer ionic strength so as

not to screen the ligand.

[PBS] λD (nm)

1X 0.7 0.1X 2.3 0.05X 3.3 0.01X 7.3 0.001X 23.2 Table 2.1 | Calculated Debye screening lengths (λD) for varying concentrations of PBS.

2.6 Conclusions

These theoretical analyses highlighted four primary considerations for our experimental

setup. First, in order to maximize sensitivity (pH and otherwise) we had to minimize the

cross-sectional area of the sensor. This consideration led to the design and realization of

the NBs, discussed in Chap. 3. Second, to harness the NB’s potential sensitivity based on

scaling, it was critical to develop a silicon-specific functionalization scheme, which is

described in Chap. 4. Third, a solution-exchange system other than a microchannel was

necessary to deliver the required number of molecules to enable rapid, ultrasensitive NB

sensing. We addressed this constraint by creating the reservoir described above. Fourth,

the Debye screening study highlighted the importance of choosing appropriate buffers for

sensing measurements, a point that is considered throughout the sensing measurements

described in Chap. 5.

56

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21. Darst, S. A. et al. Two-dimensional crystals of streptavidin on biotinylated lipid

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60

Chapter 3: Nanobar Fabrication and Characterization

3.1 Nanobar Fabrication [19]

In order to avoid the integration and fabrication issues inherent with grown, bottom-up-

fabricated NW devices [1-18], we designed a process to create semiconducting NWs—

termed nanobars (NBs)—with a traditional, top-down approach [19]. Although top-

down approaches have been demonstrated previously [20-26], those configured for

sensing showed disappointing performance in previous studies [20,21], most likely due to

process-induced material degradation. We used ultra-thin silicon-on-insulator (UT-SOI)

wafers as starting substrates [20,21,27], since these require only lateral (i.e., in-plane, 2D)

active layer definition to achieve the nanometer dimensions needed for a NW-type device

[17,18]. In order to avoid reactive-ion etching (RIE) [28] of the active silicon layer,

which unacceptably degraded device performance [20,21], but achieve the nanometer-

scale dimensions necessary for sensitivity [19], we developed a fabrication process using

an anisotropic wet etch {specifically, tetramethylammonium hydroxide, TMAH, which

etches Si (111) planes ~100 times more slowly than all other planes [17,18,29]}. This

approach allows retention of pattern definition (of a masking oxide layer), and smoothes

edge imperfections not aligned to the (111) plane [17,18]. Previous work on TMAH-

defined electronic devices [30] has shown excellent retention of electrical properties

[17,31], although not in configurations suitable for sensing. This approach uses

commercially available materials {(100) SOI wafers [32]} which yield trapezoidal cross-

61

section NWs with dominant Si (111) exposed planes, the preferred surface for selective

surface functionalization [32].

Devices used in this work were fabricated from three SOI wafers, with active Si layers

thinned to 25, 40, 80 nm by iterative oxidation/wet etching steps. We chose these

thicknesses because previous studies had shown that the transport properties of active

silicon layers are constant throughout this range [33]. All wafers were UNIBOND SOI

[27] but two sets were used: 4” wafers purchased from Silicon Quest were used for the 40

and 80 nm devices, while 8” SOI wafers purchased from SOITEC USA (and laser cut to

4” by Silicon Quest) were used for the 25 nm devices. No significant difference in

device quality was observed between the two wafer sets.

The fabrication steps are outlined in Fig. 3.1. Wafers were RCA cleaned prior to

oxidation steps and were cleaned with 3:1 sulfuric acid:hydrogen peroxide (piranha) prior

to all other lithographic steps save the final step, prior to which they were cleaned with

acetone and methanol [28]. All optical masks were purchased from Benchmark

Technologies (it should be noted that experimental design utilizied transparency masks

purchased from Cad Art Services, Inc.) and all optical lithographic steps were performed

using either an EV Group 600 or 620. In Step 1, the active layer of the wafer was thinned

to the desired height by subsequent wet thermal oxidation (MRL Industries Furnace) and

wet chemical etching. The active silicon thickness at this point was ~20 nm thicker than

the final desired thickness to account for the silicon thinning inherent in the masking

oxide growth (Step 5).

62

2. Define Mesas

4. Define Doping 9. Liftoff Metallize Al/Cr; RTA

10. Liftoff Metallize Cr/Au

7. TMAH Etch

6. Ebeam/RIE Pattern Transfer

8. Passivation Mask; RTA

5. Grow Oxide Mask

3. Define Backgates

1. Thin active Si (grow ox/BOE strip)

Handle Si

Oxide

Active Si

Degenerate Doping

Aluminum/Chrome Stack

Gold

2. Define Mesas

4. Define Doping 9. Liftoff Metallize Al/Cr; RTA

10. Liftoff Metallize Cr/Au

7. TMAH Etch

6. Ebeam/RIE Pattern Transfer

8. Passivation Mask; RTA

5. Grow Oxide Mask

3. Define Backgates

1. Thin active Si (grow ox/BOE strip)

Handle Si

Oxide

Active Si

Degenerate Doping


Gold

Handle Si

Oxide

Active Si

Degenerate Doping


Gold

Figure 3.1 | Side-view schematic of the primary NB fabrication steps. Steps 2-4 and 8-9 are achieved with optical contact lithography and Step 6 was performed with e-beam lithography. Steps 1-6 were performed at the Cornell Nanofabrication Facility and the remaining steps were performed at Yale University.

In Step 2, active layer mesas were defined by RIE (Oxford PlasmaLab 80+); it is critical

to align to the <110> wafer flat at this step. In Step 3, optical lithography and a two-step

RIE (Oxford PlasmaLab 100, PlasmaTherm 770) were used to define backgates to and

alignment marks in the handle wafer. In Step 4, ion implantation was repeated twice

(nTEK Technologies and Core Systems) to define the degenerate lead-ins, once for boron

doping (accumulation-mode devices) and once for arsenic doping (inversion-mode

63

devices) [34]. In Step 5, a masking oxide was grown by wet thermal oxidation (MRL

Industries Furnace).

In Step 6, e-beam lithography (JEOL JBX-9300FS) and subsequent RIE (Oxford

PlasmaLab 80+) were used to define and transfer, respectively, the NB pattern to the

masking oxide. Prior to Step 7, the wafers were sectioned to allow for multiple TMAH

etching and rapid thermal annealing (RTA) times. In Step 7, the samples were TMAH

etched followed by, in Step 8, the wet chemical etching of the masking oxide from above

contact pads and active devices. Next, the NBs were rapid thermal annealed (HeatPulse

720) in forming gas [35,36] and in Steps 9 and 10, a two-layer metal stack—Aluminum

(99.999%, Kurt J. Lesker Co.) / Chromium (99.998%, Kurt J. Lesker Co.), then

Chromium / Gold (99.999%, Cerac, Inc.)—was evaporated (Denton Vacuum Systems

Inficon 22) over the contact pads (RTA was used in Step 9 to drive in the Al). It should

be noted that another top metal could be substituted in this final step for full

complementary metal-oxide-semiconductor (CMOS) compatibility. A schematic (not to

scale) of a completed Hall-bar device is shown in Fig. 3.2 [19].

64

S

DG

S

DG

Figure 3.2 | Schematic of a NB after anisotropic etch definition and masking oxide removal. The active semiconducting region of the device is yellow, the conducting leads are red, the masking oxide is clear, the underlying buried oxide (BOX) is light blue, and the base “handle” silicon substrate is silver. The narrowing of the channel by wet etching undercuts the mask oxide while the conducting leads are not appreciably etched. The source (S), drain (D), and underlying backgate (G) are labeled. The active region has a trapezoidal cross-section—there is a 54.7º angle between the (111) and (100) crystal planes—as a result of the anisotropic wet etch.

As illustrated in the schematic in Fig. 3.3a, the TMAH-etching process was used to yield

devices narrower than their microlithographic pattern definition [19,30]. The anisotropic

wet etch undercut the grown masking oxide, whose lateral dimensions could be achieved

with optical lithography. The degenerately doped (>1020 cm-3) boron lead-ins were not

appreciably etched by TMAH [29], dramatically simplifying device processing since

additional steps to protect this region from etchant were not necessary. The active region

has a trapezoidal cross-section—there is a 54.7º angle between the (111) and (100)

crystal planes [34]—as a result of the anisotropic wet etch. The inset, which shows a

cross-section of the active device region, defines the dimensions—width, w, and

thickness, t—used for device descriptions. A top-view field-emission scanning electron

micrograph (FE-SEM) of a NB with the oxide mask removed (Fig. 3.3b) clearly displays

its trapezoidal shape and illustrates an x ~ 200 nm undercut. The original lateral

definition was 600 nm and the final device has w = 80 nm. Although pattern-definition

65

roughness is evident on the lead-in regions, the NW has no such roughness, illustrating

the improved sharpness of the NW edges due to the planarization of the etch [19].

Figure 3.3 | a, Schematic of a NB after anisotropic etch definition but prior to masking oxide removal with the same coloring as Fig. 3.2. The TMAH-induced undercut is evident. The inset, which shows a cross-section of the active device region, defines the dimensions—width, w, and thickness, t. b, Scanning electron micrograph of a completed NB illustrating an x ~ 200 nm undercut. The original lateral definition was 600 nm and the final device has w = 80 nm.

Reproducible and well-controlled device narrowing (Fig. 3.4a and 3.4b, respectively) was

achieved due to the slow Si (111) etch rate [19]. A scatter plot of 40 total t = 80 nm

devices illustrating the repeatability and linearity (R2 = 0.97) of the etch undercut x (± 5

nm), with each point representing the average of four devices from the same sample (the

variation ≤ 10 nm), is shown in Fig. 3.5. The initiation of the (111) etch for x = 0 is

responsible for the ~55 sec offset. It should be noted that not all patterned devices

successfully undercut, most probably due to surface contamination.

66

Figure 3.4 | a, Optical micrograph of a device prior to anisotropic etching but after RIE pattern transfer to the masking oxide. The patterned dimension is w ~ 750 nm. The coloring is real and is due to the variations in thickness and composition of the thin films. b, Optical micrograph of the same device from Fig. 3.4a after anisotropic etching and making oxide removal. The resulting NB has w ~ 400 nm. The change in coloring is due to the removal of the masking oxide by wet etching. c, Optical micrograph of a completed NB. Different colors are due to process-induced thickness differences. The device is 100 nm wide, 40 nm high and 20 μm long. d, Scanning electron micrograph of a completed 4-point NB with w ~ 100 nm. The degenerate doping strips in the leads are evident due to conductivity differences. e, Scanning electron micrograph of a completed RIE control structure with w = 3 μm.

67

0 50 100 150 200 250 300 350 4000

50

100

150

Und

ercu

t Dis

tanc

e x

(nm

)

Etching Time (sec)

x x

0 50 100 150 200 250 300 350 4000

50

100

150

Und

ercu

t Dis

tanc

e x

(nm

)

Etching Time (sec)0 50 100 150 200 250 300 350 400

0

50

100

150

Und

ercu

t Dis

tanc

e x

(nm

)

Etching Time (sec)

x x

Figure 3.5 | Scatter plot of 40 NBs (t = 80 nm) illustrating repeatability and linearity (R2 = 0.97) of the etch undercut x (± 5 nm). Each point is the average of four devices from the same chip, illustrating variation ≤ 10 nm. The initiation of the (111) etch for x = 0 is responsible for the ~55 sec offset.

The fabrication approach is flexible, allowing the configuration of a variety of

sophisticated NW geometries without additional processing steps; for example, an optical

micrograph of a 6-point, Hall bar device is given in Fig. 3.4c. Different colors are due to

process-induced thickness differences. The device is 100 nm wide, 40 nm high and 20

μm long. Devices configured for 4-point characterization (Fig. 3.4d) and control

measurements (Fig. 3.4e) were also fabricated on the same wafer in the same process run

[19]. Sensor arrays and integrated signal processing electronics may be readily fabricated

as well.

3.2 Nanobar Characterization

68

All electrical measurements were performed with an HP4156B Semiconductor Parameter

Analyzer (SPA). Device transconductance was calculated by the linear best-fit to the

source-drain current-to-source-drain voltage [ISD(VGD)] dependence. The capacitance

was calculated using the measured geometrical parameters. For consistency, all NB

mobilities are calculated in the pre-saturation regime according to [15,34]

SDVGD

SDSD V

IVLC

∂∂

⎟⎠⎞

⎜⎝⎛=

−1

2μ , (3.1)

where

)/4ln(2 0

dhLC πεε

= , (3.2)

L is the source-drain NW length, h is the oxide thickness, d is the NW diameter, and VGD

is the gate-drain voltage.

Electrical characterization verified that the NB fabrication approach produced high

quality semiconducting devices. The ISD(VSD) dependencies for varying VGD are given in

Figs. 3.6a and 3.6b for representative p-type and n-type devices, respectively. Figure

3.6a shows the ISD(VSD) dependence for varying VGD from 0 to -40V in -1V steps

(indicated by the red arrow) for a (w = 50 nm, t = 25 nm) device, demonstrating p-type

accumulation mode behavior. Figure 3.6b shows the ISD(VSD) dependence for varying

69

VGD from 0 to 40V in 1V steps (indicated by the red arrow) for a (w = 50 nm, t = 40 nm)

nm device; the n-type behavior demonstrates an inversion-mode device [34].

0 -5 -10 -15

0

-1µ

-2µ

-3µ

I SD (A

)

VSD (V)

a

0 -5 -10 -15

0

-1µ

-2µ

-3µ

I SD (A

)

VSD (V)0 -5 -10 -15

0

-1µ

-2µ

-3µ

I SD (A

)

VSD (V)

a

b

0 5 10 15

0

2µ

4µ

6µ

8µ

I SD (A

)

VSD (V)0 5 10 15

0

2µ

4µ

6µ

8µ

I SD (A

)

VSD (V)

b

0 5 10 15

0

2µ

4µ

6µ

8µ

I SD (A

)

VSD (V)0 5 10 15

0

2µ

4µ

6µ

8µ

I SD (A

)

VSD (V)

Figure 3.6 | a, Plot of the ISD(VSD) dependence for varying VGD from 0 to -40V in -1V steps (indicated by the red arrow) for a (w = 50 nm, t = 25 nm) device. The characteristics show p-type accumulation mode behavior. b, Plot of the ISD(VSD) dependence for varying VGD from 0 to 40V in 1V steps (indicated by the red arrow) for a (w = 50 nm, t = 40 nm) nm device . The n-type behavior suggests an inversion-mode device.

The ISD(VGD) dependencies for constant VSD = –1V for the p- and n-type devices of Fig.

3.6a and 3.6b are shown in Fig. 3.7a and 3.7b, respectively. The small hystereses

between forward (red) and reverse (black) ISD(VGD) slopes suggest minimal defect-

induced charge trapping and ambipolar behavior is evident for the inversion-mode

device. This observed n-type behavior is due to the polarity of the degenerate contacts to

the ambipolar device. The small lead-to-device contact area (the device cross-sectional

area) is highly resistive and will not enable channel inversion at the observed voltages.

Thus, the observed negative shift of the flat-band voltage and the positive shift of the

inversion-mode threshold voltage are explained by positive charge buildup on the

degenerate lead at the contact region as a result of etching. This charge accumulation is

70

sufficient to invert the contact, thereby decreasing the contact resistance and enabling

inversion-mode behavior at the observed voltages. The presence of these devices on the

RIE-defined control structures indicates that the RIE pattern definition is responsible for

this charge accumulation.

0 -10 -20 -30 -401f

100f

10p

1n

100n

|I SD (A

)|

VGD (V)0 -10 -20 -30 -40

1f

100f

10p

1n

100n

|I SD (A

)|

VGD (V)

a

0 -10 -20 -30 -401f

100f

10p

1n

100n

|I SD (A

)|

VGD (V)0 -10 -20 -30 -40

1f

100f

10p

1n

100n

|I SD (A

)|

VGD (V)

a

b

0 10 20 30 401f

100f

10p

1n

100n

I SD (A

)

VGD (V)0 10 20 30 40

1f

100f

10p

1n

100n

I SD (A

)

VGD (V)

b

0 10 20 30 401f

100f

10p

1n

100n

I SD (A

)

VGD (V)0 10 20 30 40

1f

100f

10p

1n

100n

I SD (A

)

VGD (V)

Figure 3.7 | a, Plot of the |ISD|(VGD) dependence for VSD = -1V for a forward (red) and reverse (black) sweep of a p-type NB. The device hysteresis is seen to be minimal. b, Plot of the ISD(VGD) dependence for VSD = 1V for a forward (red) and reverse (black) sweep of a n-type NB. The device hysteresis is seen to be minimal and ambipolar behavior is evident.

Peak drift mobilities were calculated from the measured ISD(VGD) dependence and a self-

consistent device simulation (Silvaco). We obtain an average mobility value of 54

cm2/V·s across 12 devices, with a maximum of 139 cm2/V·s. These results compare

favorably with p-type silicon doped to 1015 cm-3 (which has a bulk mobility of 450

cm2/V·s [34]) and the known decrease in bulk mobility for anisotropically-defined Si

(111) planes [39-41]. The ability to produce NWs in a Hall bar geometry allowed us to

measure the Hall mobility [34] for the first time in a silicon nanowire-like structure, Fig.

3.8 [19]. The mobility degradation from bulk is due to three scattering mechanisms

induced by the prevalence of the silicon/silicon dioxide interface in the NBs [39,40]. The

71

first is phonon scattering, which is a result of the lattice vibration modes, specifically

surface acoustic and optical phonons. The second, important for lightly-inverted

surfaces, is Coulomb scatting due to charge centers, which include fixed oxide charge,

interface-state charge, and localized charge due to ionized impurities. The third,

important for strongly-inverted surfaces, is surface-roughness scattering induced by the

deviation of the interface from an ideal plane. These surface scattering mechanisms have

been demonstrated to exert a significant, deleterious effect on mobilities, even in the most

state-of-the-art NB-like devices (termed “finFETs” in the literature) [31,39-41].

100

100

Mob

ility

(cm

2 /V-s

)

Temperature (K)

HallDrift

30 300

50

300

100

100

Mob

ility

(cm

2 /V-s

)

Temperature (K)

HallDrift

30 300

50

300

Figure 3.8 | Hall and drift mobilities versus temperature for a (w = 300 nm, t = 25 nm) p-type device.

3.3 Conclusions

72

In this Chapter, we demonstrated the ability to produce high-quality silicon nanodevices

with traditional top-down techniques in a configuration suitable for sensing. The

resulting NBs can be fabricated in a variety of important geometries, including 4-points

and Hall-bars, and p- and n-type devices can be realized on the same chip. An additional

power of the fabrication technique is the ability to realize devices with dimensions

smaller than those patterned, potentially eliminating the reliance on serial write processes

for creating nanoelectronic devices.

73

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10. Martensson, T. et al. Nanowire arrays defined by nanoimprint lithography. Nano

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78

Chapter 4: Functionalization Techniques for Protein

and DNA Conjugation

4.1 Introduction

A promise of nanowire-field effect transistor (NW-FET) sensing is the ability to create an

ultrahigh density array of sensors, each specific for a distinct molecule [1-7]. Due to the

inability of current high-throughput surface functionalization schemes to selectively coat

patterned substrates at micron and nanometer scales [8-17], we explored a number of

schemes to realize selective functionalization. We also explored the well-known 3-

aminopropyltriethoxysilane functionalization method [4,18-21]. While this approach had

the highest functional device yield, its major shortcoming is that it confers amine

functionality to all exposed oxide surfaces, drastically decreasing device sensitivity (see

Chap. 2) [5,18-21].

Selective approaches explored were:

1. A new approach [22] based on the oxidative electropolymerization of derivatized

phenols [23-30], that was successfully shown to functionalize patterned conducting

surfaces down to 1 μm with free amine, aldehyde, and carboxylic acid groups.

79

2. An approach devised by Mrksich and coworkers [31-33] and adapted to silicon by

Heath and coworkers [34]. In this system, an inactive hydroquinone is tethered to an

electrically conducting surface and can be electrochemically cycled to its active, quinone

state [31-33].

3. A method devised by Hamers and coworkers that selectively confers amine

functionality to silicon but is not electrically active [35,36].

4.2 Electropolymerization-Based Functionalization [22]

We first demonstrated that electrically conducting and semiconducting materials in any

lithographically realizable geometry can be selectively functionalized and showed that

the derivatized groups can covalently bind molecular targets, including proteins and

DNA. In order to achieve selective functionalization, we utilized the method of phenol

electropolymerization, which has been previously shown to deposit insulating films on Pt

wires [23-30,37-40], primarily for the development of amperometric and potentiometric

sensors. Electropolymerization is a process whereby a conducting [41-43] or insulating

[23-30,37-40] film is deposited on a conductive [37-40] or semiconductive substrate

[41,44]. Two significant advantages of insulating films, such as polyphenols, are that

they are considerably thinner due to the self-limiting nature of the polymerization

reaction [37,38] and that substrates can be coated without significantly altering their

electronic properties. The electropolymerization of tyramine and 4-

hydroxybenzaldehyde has been shown to produce insulating films with reactive amines

80

and aldehydes on bulk electrodes [24-30], but the applications of this approach have been

severely limited due to the lack of integration with thin film microelectronic technology,

which enables simultaneous functionalization of electrodes in large arrays with different

molecular species. In contrast with other electrochemical-based methods [31-34,45], the

power of our method is that it offers multiple conjugation chemistries, is not surface

specific, is stable in aqueous environments, and is prepared entirely from commercially

available chemicals.

The deposition solution was created by dissolving a substituted phenol in phosphate

buffered saline (PBS), Fig. 4.1, which was subsequently loaded into an electrochemical

cell defined by a poly-dimethylsiloxane (PDMS) gasket (schematic, Fig. 4.2) [46-48]. A

potential was then cycled between the counter and reference electrodes, while current

was measured at the working electrode (the patterned surface in Fig. 4.2, which fans out

to a contact pad that can be accessed and electrically contacted by a microprobe). The

insulating surface coating was produced by a free radical polymerization, which was

previously reported to occur at the ortho positions of the ring [39], in which free radicals

are generated by the removal of an electron from deprotonated phenyl rings at the

working electrode (Fig. 4.1).

OH

R

O

R

O

R R

O

-e- atsurface+ H+

- H+

(

(

n

n

( nOH

R

O

R

O

R R

O

-e- atsurface+ H+

- H+

(

(

n

n

( n

Figure 4.1 | Schematic of surface electrochemical polymerization. R = (CH2)2NH2, CHO, CH2COOH for tyramine, 4-hydroxybenzaldehyde, and 4-hydroxyphenylacetic acid, respectively.

81

working

counterreference

working

counterreference

Figure 4.2 | Schematic (not to scale) of an electrochemical cell defined by a PDMS gasket on a patterned ITO-on-glass substrate.

The electropolymerization of tyramine at the working electrode, a patterned ITO lead,

was evident from the presence of a strong oxidation peak of ~50 μA during the first

sweep in the cyclic voltammogram in Fig. 4.3 (for an electrode of ~1.53 × 105 μm2, the

current density is ~0.29 nA/μm2). The absence of this peak from subsequent sweeps

indicates that tyramine oxidation is non-reversible and self-limiting. In the cyclic

voltammogram (CV), the current measured at the working electrode (IM) is plotted versus

the forced voltage between the counter and reference electrodes (VF) [49]. The potential

at which the oxidation occured is strongly dependent on (i) the working electrode

material and (ii) the freshness of the reference electrode (the peak has been seen to occur

between ~2.4-3.3V on ITO). Similar CVs were obtained for the electropolymerizations

of 4-benzaldehyde and 4-hydroxyphenylacetic acid.

82

-4 -3 -2 -1 0

0

25µ

50µ

OH

NH2

I M (A

)VF (V vs. Ref)

Sweep 1 Sweep 2 Sweep 3

Figure 4.3 | Cyclic voltammogram of the electropolymerization of tyramine (inset) on a single patterned ITO lead on a glass substrate.

We then demonstrated the ability of this method to selectively and sequentially

functionalize patterned electrodes by conformally coating only the working electrode

surface in an electrochemical cell. A PDMS gasket was placed around all the leads to

create an electrochemical cell (as depicted in Fig. 4.2). The outermost lead was used as

the working electrode and its surface was selectively functionalized with amine groups by

tyramine electropolymerization as described above. The sample was then exposed to a

blue, amine-reactive fluorophore [50] and the fluorescence micrograph in Fig. 4.4a

demonstrates that amines were selectively introduced as a result of the

electropolymerization. Second, the innermost electrode was functionalized with

aldehyde by 4-hydroxybenzaldehyde electrodeposition, which was followed by the

binding of a green, aldehyde-reactive fluorophore (Fig. 4.4b). After quenching remaining

aldehyde groups with hydrazine, the middle lead was functionalized with carboxylic acid

by 4-hydroxyphenylacetic acid electrodeposition. A red, carboxylic acid-reactive

fluorophore was subsequently conjugated to the surface and the sample was then imaged

(Fig. 4.4c). The three individual filtered images were merged to give the image shown in

83

Fig. 4.4d and the localization of each of the three fluorophores is apparent. The

fluorescence intensity plot versus position for the dashed red cutline in Fig. 4.4d is given

in the inset in Fig. 4.4d. This plot demonstrates the absence of cross-functionalization

(i.e. nonspecific) interaction.

Figure 4.4 | Fluorescence optical micrograph—(a) DAPI filter, (b) GFP filter, (c) TRITC filter, (d) merged image—of a central part of the lead pattern for a sample treated as follows: polytyramine was deposited on the outermost lead and the chip was subsequently treated with a blue, amine-reactive fluorophore. Poly-4-hydroxybenzene was then deposited on the innermost lead, followed by chip treatment with a green, aldehyde-reactive fluorophore. Free aldehyde groups were then quenched. Lastly, poly-4-hydroxyphenylacetic acid was deposited on the middle lead and the chip was treated a red, carboxylic acid-reactive fluorophore. In (d) the inset shows the fluorescence intensity versus position for the red cutline. The line color corresponds to the fluorescence color; the fluorescence intensity units are defined by ImageJ.

84

We then showed that macromolecules selectively bound to surfaces with our technique

retained their activity by studying the localization of a protein, bovine serum albumin

(BSA), to the functionalized surfaces. Amine and carboxylic acid groups are desirable

for protein conjugation [50], while aldehyde and carboxylic acid groups are preferred for

DNA binding [20]. A carbodiimide coupling reaction was utilized to conjugate BSA to

the central leads of a chip functionalized with amines. The sample was subsequently

incubated with chicken anti-BSA-FITC (green fluorescence) immunoglobulin G (IgG)

antibody [51] and the fluorescence micrograph of the sample is shown in Fig. 4.5 (the

inset shows a schematic of the reactions). The “bottom view” is immunofluorescence

viewed through the ITO; the “top view” is the immunofluorescence viewed directly,

illustrating the transparency of ITO. The fluorescent intensity is localized to the

functionalized lead, illustrating the conjugation of BSA to the surface and the subsequent

BSA-anti-BSA-FITC IgG binding.

Figure 4.5 | Fluorescence micrograph (GFP filter) of the end of an electrode pattern first coated with polytyramine, then carbodiimide coupled to BSA, and lastly incubated with a fluorescently-labeled BSA IgG, as illustrated by the schematic inset. The “bottom view” is immunofluorescence viewed through the ITO; the “top view” is the immunofluorescence viewed directly, illustrating the transparency of ITO.

85

Thus, we demonstrated that modified phenols could be electrodeposited from aqueous

solution onto lithographically patterned substrates to produce surfaces with free amine,

aldehyde, and carboxylic acid groups capable of conjugating small molecules, proteins,

and DNA oligonucelotides (see Appendix I) with no detectable cross-contamination.

Despite the utility of this approach to confer functionality to patterned electrodes, the

native oxide layer coating exposed silicon surfaces has so far prevented its application to

NBs under ambient conditions. Although only a short buffered oxide etch (BOE) is

needed to remove this native oxide coating, the subsequent washing, solution exchange,

and electrodeposition steps must occur in an inert atmosphere in order to prevent oxide

regeneration. Performing this series of sample manipulations was not possible in the

available laboratories, thus we were forced to pursue a second method for electrically-

directed functionalization. However, it is important to note that, given the proper

facilities, the electrochemical deposition approach described in this section has promise

and could potentially be applied to NB functionalization.

4.3 Electrically-Directed Silicon Functionalization [5]

We first sought to electrically direct NB functionalization by using the previously

reported hydroquinone/quinone scheme [31-34], in which an electrically active molecule

[33] is deposited and electrochemically cycled from its inactive (hydroquinone) to

reactive (quinone) state by applying a potential to the NB. This method was originally

86

developed by Mrksich and coworkers for gold substrates [31,32] and was later adapted to

silicon substrates by Heath and coworkers [34], who used 2-[2-(Undec-10-enyl)-4-

(tetrahydro-2H-pyran-2-yloxy)phenoxy]tetrahydro-H-pyran (2-THP), the molecule

depicted in Fig. 4.6a. A photochemical hydrosilation reaction was used to link terminal

C=C bond to a silicon surface, forming a direct Si-C bond. Devices were introduced into

an inert N2 atmosphere, etched for 5 sec in deoxygenated 10:1 buffered oxide etch

(BOE), rinsed in deoxygenated, deionized water, dried with N2, coated with the molecule

(an oil), and subjected to a 2 hr UV treatment. The UV-light source (254 nm) was an

ozone-free Hg pen lamp (Jelight, model 823-3309-2) and emitted ~10 mW/cm2 at 1 cm,

the distance from sample-to-source.

SurfO

OH

H

SurfO

O

O

O

O

O

a

b c

SurfO

OH

H

SurfO

O

O

O

O

O

a

b c

Figure 4.6 | a, Structure of the molecule 2-[2-(Undec-10-enyl)-4-(tetrahydro-2H-pyran-2-yloxy)phenoxy]tetrahydro-H-pyran (2-THP). b, Structure of the molecule shown in (a) after binding to the surface and subsequent deprotection. “Surf” represents a silicon atom. The aromatic ring is a hydroquinone. c, Structure of the molecule after electrochemical cycling to the oxidated, quinone state.

87

After the binding and subsequent deprotection steps on bulk Si (111) and (100)

substrates, we demonstrated successful electrochemically-mediated molecular cycling

between the inactive state (the hydroquinone, Fig. 4.6b) and the active, quinone state

(Fig. 4.6c) by electrochemical oxidation at ~600 mV and reduction at ~ –600 mV (cyclic

voltammogram, Fig. 4.7); the same electrochemical cell setup was used as illustrated in

Fig. 4.2. These redox peaks are similar to those reported in Ref. 34, verifying successful

electrically-addressable functionalization. Additionally, it should be noted that the redox

peaks present in the CV in Fig. 4.7 are not observed for unfunctionalized silicon samples.

Although we demonstrated successful functionalization with this approach, we found that

it caused an unacceptable deterioration in device performance (discussed in Chap. 5).

-1.0 -0.5 0.0 0.5 1.0

-300.0n

-200.0n

-100.0n

0.0

100.0n

200.0n

I M (A

)

VF vs. VRef (V)

Figure 4.7 | Cyclic voltammogram of the electrochemical conversion of the molecules shown in Fig. 4.6a. The reduction peak occurs at a negative potential (versus the reference electrode) and the oxidation peak lies at a positive potential (vs. reference).

4.4 Silicon-Specific, Non-Electrically Directed Functionalization [5]

88

These findings led us to choose an electrically-inactive molecule for functionalization.

The sensitivity considerations discussed in Chap. 2 dictated that we select a silicon-

specific approach; we chose to use dec-9-enyl-carbamic acid tert-butyl ester (CAE)

because previous studies had demonstrated that this molecule could confer amine

functionality both to bulk silicon and silicon nanowires (schematic, Fig. 4.8) [35,36]. As

described in Chap. 2, hydroxyl-reactive schemes will functionalize the entire chip surface

and decrease sensitivity due to binding competition [19-21]. Devices were functionalized

using CAE as described above for 2-THP. It should be noted that the deprotection step,

which uses 25% trifluoroacetic acid (TFA) in methylene chloride [35,36], is compatible

with all exposed surfaces on the chip but etches aluminum (necessary for contacting the

silicon), thus this metal must be conformally coated with a chrome/gold layer. Static

water contact angles on bulk Si (100) surfaces, Table 4.1, demonstrate successful

functionalization with, and subsequent deprotection of, CAE. These data compare

favorably with previously reported values from similar surfaces [35]. Each datapoint

represents the average (± one standard deviation) of two separate measurements on 12 ~1

cm × 1 cm chips. The same chips were used for pre- and post-deprotection

measurements.

NH

OO

NH

OO

Surf

NH

Surf

H

UV TFA

89

Figure 4.8 | Left: Structure of the molecule CAE. Middle: Structure of the same molecule after the UV-induced reaction with the surface. The “Surf” represents a silicon atom; the binding of the terminal olefin to the hydrogenated-silicon surface produces a single bond between a surface silicon atom and the terminal carbon atom in the chain. Right: Structure of the functionalized surface after t-BOC deprotection in trifluoroacetic acid (TFA).

Static Contact Angle Surface Measured Reported

[103]

t-Boc Protected Amine 81.3 ± 4.2º 78.1º Deprotected Amine 56.0 ± 3.7º 55.4º Table 4.1 | Static water contact angles on bulk (100)-silicon surfaces functionalized with dec-9-enyl-carbamic acid tert-butyl ester before and after deprotection. Each datapoint represents the average (± one standard deviation) of two separate measurements on 12 ~1 cm × 1 cm chips. The same chips were used for pre- and post-deprotection measurements.

Successful NB functionalization was achieved using this approach, as shown in the

fluorescent micrograph in Fig. 4.9. For this (w = 500 nm; t = 40 nm) device, the surface

was treated with an amine-reactive biotin conjugate [50] after deprotection and

subsequently incubated with a red fluorescent (AlexFluor 655) streptavidin conjugate.

After washing and deprotecting, the device yield for effective selective functionalization

was <2%.

Figure 4.9 | Fluorescence micrograph (TRITC filter) of a biotin-functionalized NB (w = 500 nm; t = 40 nm) treated with 1 nM streptavidin conjugated to a red fluorophore.

90

4.5 Non-Silicon-Specific, Non-Electrically Directed Functionalization [21]

Due to poor device yield with the CAE-functionalization approach, we used 3-

aminopropyltriethoxysilane (APTS) to functionalize devices for later studies [4,19-21].

This molecule reacts with free hydroxyls, which are abundant on oxide surfaces, and thus

converts the silanol surface to an amine surface [19-21]. In order to demonstrate

successful surface functionalization, glass slides were cut into 1” × 1” chips and were

treated with a 0.7% (v/v) solution of APTS in hexanes for 1.5 hrs at room temperature

with stirring. The chips were then washed with hexanes, toluene, and chloroform and

sonicated for 20 mins in chloroform. Next, the samples were patterned with an array of

25 μm × 25 μm squares such that the photoresist covered the entire surface except the

squares, Fig. 4.10a. The slide was then treated with an amine-reactive biotin molecule at

pH 8.4 and washed and the photoresist was subsequently removed with acetone. The

chip was next treated with an amine-reactive PEG molecule at pH 8.4 to prevent

nonspecific binding to free amines. After washing, the sample was incubated with a

green fluorescent streptavidin conjugate and was fluorescently imaged, Fig. 4.10b. The

strepavidin is seen to bind selectively to the exposed biotin surfaces, which were defined

by the photoresist pattern, verifying that the APTS approach successfully conferred

amine functionality to the substrate.

91

Figure 4.10 | a, Optical micrograph of a glass slide with photoresist patterned to expose 25 μm × 25 μm squares. b, Fluorescent micrograph (GFP filter) showing the chip in (a) after binding of green fluorescently-conjugated streptavidin.

4.6 Conclusions

We have thus demonstrated methods for conferring electrically active and inactive

chemical functionalities selectively and nonselectively to silicon surfaces. Although a

proper laboratory setup should enable the electropolymerization approach to be applied to

NBs, the sensing studies described in Chap. 5 rely solely on the photochemical

hydrosilation and the APTS approaches to selectively and nonselectively, respectively,

functionalize NB devices. Thus, through these studies we demonstrated sufficient

surface modification control to begin sensing measurements with NBs.

92

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98

Chapter 5: Nanobar Sensing

5.1 Introduction

We now discuss sensing results obtained with the devices and techniques described in the

previous chapters. We showed that the nanobars (NBs) are highly sensitive to bound

molecular charge, enabling the detection of specific label-free reagents [1-5]. Successful

sensing demonstrations with nanowire-field effect transistors (NW-FETs) had previously

been performed for ions [1], small molecules [6], proteins [7-11], DNA [12-14], and

viruses [15,16]. We began by using unfunctionalized NBs as pH sensors, enabling the

monitoring of real-time stimulus-induced cellular response without labels. Then, we

characterized functionalized devices as sensors with streptavidin and avidin and

subsequently utilized these devices to detect specific proteins and single stranded- (ss)-

DNAs.

First, the silanol-group termination of the native oxide coating of the NBs was exploited

in using the devices as hydrogen ion sensors. As discussed in Chap. 2, it has been shown

both for bulk and NW-FET devices that these silanol groups can be protonated and

deprotonated by varying solution pH, thereby gating the underlying device and

modulating the source-drain current [1-5]. We demonstrate the ability the NBs to sense

pH in a physiologically relevant range and utilize this property to measure monitor real-

time cellular response of activation-induced changes in extracellular pH [4,5].

99

Additionally, we showed that the sensitivity of a single NB device can be modulated by

accessing different transconductance regions [4].

We then utilized functionalized devices to sense specific proteins and DNA. We first

used biotinylated [3,4,17] NBs to illustrate that the NBs are sensitive to both the

magnitude and sign of adsorbed proteins (streptavidin and avidin), that complementary

detection with p- and n-type devices is possible, that the ionic strength of the solution can

be used to screen the charge, and that selectively functionalized devices can sense the

presence of <10 fM streptavidin [4,5]. We then demonstrated sensitivity to <100 fM

complementary DNA 20-mers and to <100 fM immunoglobulin G and A [4,18].

5.2 Unfunctionalized NB Sensing [4]

We begin by discussing the use of unfunctionalized NBs as hydrogen ion sensors [1-5].

The response of a large (w = 1000 nm, t = 80 nm) and small (w = 100 nm, t = 25 nm)

device to five solutions with pH varying from 6.0-8.0 (shown in blue) is displayed in Fig.

5.1. Consistent with p-type semiconducting behavior, the source-drain conduction

decreases as the acidity of the solution increases. Each device displays small hystereses

and high reproducibility (the average current levels repeat to <15%). Using the

sensitivity definition given in Eqn. (2.1), the measured sensitivity of the large NB is 10.3

and that of the small device is 43.1 for the pH range from 6.0 to 8.0.

100

0 100 200 300 400 500 600

10n

100n

1µ

|I SD (A

)|

Time (s)

largesmall

8.0

7.5

7.0

6.5

6.0

6.5

7.0

7.5

8.0

0 100 200 300 400 500 600

10n

100n

1µ

|I SD (A

)|

Time (s)

largesmall

8.0

7.5

7.0

6.5

6.0

6.5

7.0

7.5

8.0

Figure 5.1 | Response of two NB sensors—large: (w = 1000 nm, t = 80 nm) and small: (w = 100 nm, t = 25 nm)—to five pH solutions (shown in blue). The sensors were measured in separate runs, thus the timing of solution exchanges was not identical.

In order to compare these experimental values with those predicted by the theory, we

determine the dependence of βint (the change in surface charge density for changes in

pH , the pH at the semiconductor surface, from pHs pzc, the pH at the point of zero surface

charge) on pH (buffer pH) in the pHB B range from 6.0 to 8.0. Using the literature values

for a silicon dioxide surface [19], this ratio can be approximated by

17int 1023.2~ ×Δ BpH

β . (5.1)

Combining this expression with Eqn. (2.6), we calculated the theoretical sensitivities of

the large and small NB devices from Fig. 5.1 to be 12.8 and 107.0, respectively. In this

calculation, we use a charge-transfer coefficient (α) of 1, which should be an

101

overestimate because each bound proton does not necessarily represent the loss of an

electron from the NB channel. Additionally, Eqn. (2.6) assumes a device of radius R,

only a rough approximation for the NB geometry—the NB widths are significantly

greater than their thicknesses, by 12.5- and 4-fold for the large and small devices,

repectively. In spite of these approximations, the measured sensitivities are similar to the

calculated values, indicating the NBs are functioning as nanoscale ion-sensitive FETs.

We next show the impact of device scaling on sensitivity using the devices from Fig. 5.1

as well as a third, “medium,” NB with dimensions (w = 150 nm, t = 40 nm). In Fig. 5.2,

device sensitivity [Eqn. (2.6)] for the pH range from 6.0 to 8.0 and is plotted versus the

inverse of device radius (determined as described above). As predicted in Eqn. (2.6), the

NBs scale with inverse surface area, with R2 = 0.99. The pH response from a 3 μm-wide

reative ion etch (RIE) edge-defined control structure processed simultaneously with the

NBs is also shown. This device is nominally identical with the exception of edge

definition, and illustrates RIE-induced degradation of sensing performance. The

theoretical curve is obtained as described above; the increase in predicted versus

measured sensitivities is most probably due to the choice of α, which is generally

determined experimentally [20,21], and to the inaccuracy in determining a device radius.

Although the theoretical and experimental scaling factors differ, the 1/R dependence of

the device sensitivity is clear.

102

0 5 10 15 20 25

0

20

40

60

80

100

120

Sens

itivi

ty

Inverse Radius (μm-1)

NB device RIE device Theory

0 5 10 15 20 25

0

20

40

60

80

100

120

Sens

itivi

ty

Inverse Radius (μm-1)

NB device RIE device Theory

Figure 5.2 | Plot of sensitivity to pH in the range from 6.0 to 8.0 versus the inverse of device radius for three NB devices and a RIE control structure. The R2 of the linear fit (dashed black line) to the three NBs is 0.99. The blue line is the device sensitivity to pH (in the 6.0-to-8.0 range) determined by Eqns. (2.6) and (2.15).

This fabrication approach naturally provides a back-gating capability, which can tune the

sensitivity of a device by operation in different transconductance (gm) regions [22], an

important characteristic for high dynamic range applications [23]. Transconductance

⎟⎟

⎠

⎞

⎜⎜

⎝

⎛

∂∂

SDVGD

SD

VI is a measure of the current response with respect to gate voltage: thus, the

most sensitive sensor response to additional surface charge will occur at the maximum

transconductance value (gm,max) because bound surface charge will exert the greatest

effect on device conductance at this point. The gm,max occurs between the linear and

saturation regions of a FET transfer characteristic, as seen in the red curve of the inset in

Fig. 5.3. As shown in Fig. 5.3 for the (w = 150 nm, t = 40 nm) device from above, the

measured sensitivity tracks with gm (inset), with peak sensitivity at gm,max. The inset plot

shows the dry source-drain current versus gate-drain voltage [|ISD|(V )] and gGD m(V ) GD

103

dependencies at a source-drain voltage (VSD) of -1V and the voltages used for sensitivity

measurements are labeled.

-30 -32 -34 -36 -38 -400

5

10

15

20

25

30

Sens

itivi

ty [I

(pH

8.0

)/I(p

H 6

.0)]

VGD (V)

-20 -25 -30 -35 -4010p

100p1n

10n100n

1µ

VGD (V)|I SD

(A)|

0

200n

400n

600n

gm (S)

-30 -32 -34 -36 -38 -400

5

10

15

20

25

30

Sens

itivi

ty [I

(pH

8.0

)/I(p

H 6

.0)]

VGD (V)

-20 -25 -30 -35 -4010p

100p1n

10n100n

1µ

0

200n

400n

600n

gm (S)

VGD (V)|I SD

(A)|

Figure 5.3 | Plot of NB sensitivity (ISD, pH 8.0 / ISD, pH 6.0) for three gate voltages for the “medium” device from Fig. 5.2. The inset plot shows the dry |ISD|(V ) and gGD m(V ) dependencies at VGD SD = -1V and the voltages used for sensitivity measurements are labeled.

Although devices were stable under active conditions (VSD = -5V, VGD = -40V) in air and

under passive conditions (VSD = VGD = 0) in buffered solutions, device instability and

eventual failure after 60-600 sec was observed under active measurement conditions in

solution. This problem plagued initial studies and prevented long sensing measurements.

We eventually determined that this failure mode was due to a breakdown in the

passivating oxide (the masking oxide) covering the e-beam alignment marks. These

marks are 3 μm deep and penetrate through to the silicon handle wafer; the relatively thin

(43 nm) masking oxide breaks down in the presence of solution and shorts the solution to

the backgate (held at -30 to -40V), inducing device failure. A hardbaked (1 hour at

140ºC) photoresist layer successfully passivated these chip-level alignment marks,

yielding devices capable of performing solution-phase active measurements for hours,

104

with ISD remaining within 2.7% of its initial value after an initial settling period. These

devices are subsequently referred to as “photoresist-protected” devices.

5.3 Unfunctionalized NB Sensing of Specific Cellular Responses [4,5]

To demonstrate the efficacy of these sensors in monitoring real-time cellular responses,

we analyzed the well-characterized system of T-lymphocyte activation [24]. The

development and physiology of the immune system depends, to a large degree, on the

generation and maintenance of populations of antigen-specific T-cells [25-27]. The

ability to detect functional responses arising from a small number of these cells due to

their interaction with specific ligands on a time scale of seconds may offer the potential

for rapid clinical testing, as well as high throughput epitope and drug screening [28,29].

The cellular response of antigen-specific CD8+ + or CD4 T-cells is mediated by the

interaction of the T-cell antigen receptor with peptide-loaded major histocompatability

complexes (peptide/MHC Class I or II, respectively) displayed on the surface of antigen

presenting cells [30]. Recognition of these complexes by T-cells triggers a signaling

cascade leading to activation and proliferation of effector T-cell populations. Detection

of such T-cell subsets allows monitoring of antigen-induced immunity, and is critical to

understanding the natural course and designing efficient strategies for immune

modulation and intervention [31,32]. Peptide-MHC tetramers [31,33] and dimers [32,34]

105

that bind to the T-cell receptor with high affinity have emerged as powerful tools for

enumeration of the frequency and phenotype of specific T-cells in a variety of

applications, including autoimmune disease and cancer [32,33]. However, the use of

these tools for high throughput detection and screening of rapid functional responses of

T-cell populations with different antigen specificities is limited by the lack of available

assays capable of fast and sensitive read-out from minute populations of cells.

We first used the NBs to study the antibody-mediated crosslinking of cell surface CD3,

which triggers activation of T-cells, inducing intracellular signaling and, subsequently,

engaging effector mechanisms. One consequence of such activation includes the release

of acid [35,36]. Previous studies have demonstrated extracellular acidification within

three minutes as a result of specific (peptide/MHC) [36] or non-specific (mouse-anti-

CD3ε, anti-CD3) T-cell activation [37]. As illustrated schematically in Fig. 5.4, cellular

release of protons in response to T-cell stimulation results in the protonation of the silanol

groups of the NB (active region colored black). The resulting decrease in the negative

charge on the p-type NB results in a decrease in the magnitude of the source-drain

current, |ISD|, as schematically illustrated in the |ISD| vs. time plot. The time required for T

cell activation after stimulant addition can be quantified.

106

Figure 5.4 | Sensing schematic: pre-T cell stimulation (left) and post-stimulation and activation (right). Prior to T cell activation, a majority of the NB’s silanol groups (active region colored black) are deprotonated. After activation, extracellular acidification results in increased protonation of the surface silanol groups, which decreases |ISD| (|ISD| vs. time plot). The time required for T cell activation after stimulant addition can be quantified.

Initial experiments focused on examining the utility of the device for detecting proton

secretion due to activation-induced polyclonal T-cell signaling. Splenocytes isolated

from a C57/BL6 (B6) mouse (~7 × 104 cells) were suspended in a low-buffered solution

[4,5,34,36] and stimulated with anti-CD3 antibody (1 μg/μL). We first showed that the

addition of species-specific antibody directed against mouse CD3 complex (mouse-α-

CD3) caused a drop in the signal beginning at ~8-10 sec, and a continued negative

derivative until current instability at ~30 sec, Fig. 5.5a [4]. A control experiment with a

species-specific antibody to human CD3 (i.e., this antibody does not bind mouse CD3)

showed no response. These data are consistent with previous results obtained with a

107

microphysiometer [34,36] and with expectations regarding early signals responsible for

T-cell activation that involve clustering of CD3 receptors [24].

-20 -10 0 10 20 30 40 50400n

600n

800n

1µ

|I SD (A

)|

Time (sec)

Anti-CD3Anti-CD3,

Inhibited

-20 -10 0 10 20 30 40 50400n

600n

800n

1µ

|I SD (A

)|

Time (sec)

Anti-CD3Anti-CD3,

Inhibited

b

-20 -10 0 10 20 30 40 50400n

600n

800n

1µ

|I SD (A

)|

Time (sec)

Anti-CD3Anti-CD3,

Inhibited

-20 -10 0 10 20 30 40 50400n

600n

800n

1µ

|I SD (A

)|

Time (sec)

Anti-CD3Anti-CD3,

Inhibited

b

-10 0 10 20 30

800.0n

1.0µ

1.2µ

|I SD (A

)|

Time (sec)

Human-anti-CD3Mouse-anti-CD3

a

-10 0 10 20 30

800.0n

1.0µ

1.2µ

|I SD (A

)|

Time (sec)

Human-anti-CD3Mouse-anti-CD3

a

-20 -10 0 10 20 30 40 50400n

450n

500n

550n

600n

650n HCl Control

|I SD (A

)|

Time (sec)

-5.0 -2.5 0.0 2.5 5.0400n

450n

500n

550n

600n

650n

|I SD (A

)|

Time (sec)

pH ~ 7.4

pH ~ 6.9

-20 -10 0 10 20 30 40 50400n

450n

500n

550n

600n

650n HCl Control

|I SD (A

)|

Time (sec)-20 -10 0 10 20 30 40 50

400n

450n

500n

550n

600n

650n HCl Control

|I SD (A

)|

Time (sec)

-5.0 -2.5 0.0 2.5 5.0400n

450n

500n

550n

600n

650n

|I SD (A

)|

Time (sec)

pH ~ 7.4

pH ~ 6.9

c

-20 -10 0 10 20 30 40 50400n

450n

500n

550n

600n

650n HCl Control

|I SD (A

)|

Time (sec)

-5.0 -2.5 0.0 2.5 5.0400n

450n

500n

550n

600n

650n

|I SD (A

)|

Time (sec)

pH ~ 7.4

pH ~ 6.9

-20 -10 0 10 20 30 40 50400n

450n

500n

550n

600n

650n HCl Control

|I SD (A

)|

Time (sec)-20 -10 0 10 20 30 40 50

400n

450n

500n

550n

600n

650n HCl Control

|I SD (A

)|

Time (sec)

-5.0 -2.5 0.0 2.5 5.0400n

450n

500n

550n

600n

650n

|I SD (A

)|

Time (sec)

pH ~ 7.4

pH ~ 6.9

c

Figure 5.5 | a, Nanobar response to stimulation-induced changes in extracellular pH. A nonimmune (human-anti-CD3, black) and immune (mouse-anti-CD3, red) stimulant were added to ~6000 mouse-derived T cells after a current baseline was established for ~10 sec. No change in current resulted from the addition of the nonimmune protein. The response to the immune protein, a decrease in pH corresponding to a 7.3% decrease in average current, was detected after ~10 sec and continued to decrease until current instability at ~ 30 sec. b, Measurement of extracellular acidification upon stimulation of B6 splenocytes with mouse-anti-CD3. The T-cell response time is ~8 sec. Pre-treatment of splenocytes with genistein (50 μg/mL), which inhibits cell signaling, eliminates mouse-anti-CD3 induced cellular metabolic activity. In this experiment, 1 μL of anti-CD3 (0.5 μg/μL) was added to ~7 × 104 cells. c, Device response to the addition of 1 μL of dilute hydrochloric acid (HCl) to a cell-free buffer, demonstrating system response of ~1.5 sec; the inset highlights this delay time. Before HCl addition, the solution pH was ~7.4 and afterwards it fell to 6.9.

108

In a second experiment after the device instability was remedied, we again observed

extracellular acidification beginning within ~8-10 sec after injection of mouse-anti-CD3

(0.5 μg/μL) to B6 splenocytes, Fig. 5.5b. We determined that the system response time

to a direct change in pH was ~1.5 sec (Fig. 5.5c). Thus, the ~8-10 sec delays observed in

Fig. 5.5a and 5.5b were primarily due to the intrinsic cell response.

To ensure that extracellular pH changes were due to stimulation-induced cellular

metabolic activity, we treated splenocytes derived from the same mouse with genistein

(50 μg/mL), an antibiotic that inhibits the induced intracellular signaling cascade, without

affecting cellular viability [37]. In separate experiments, we noted that genistein, at the

concentration used in this study, did not affect cell viability as assessed by trypan-blue

staining. In the presence of genistein, addition of anti-CD3 antibody resulted in no

change in solution pH (Fig. 5.5b). This confirms that the positive response observed in

untreated cells is due to the anti-CD3 antibody-initiated proton secretion from

splenocytes, consistent with previous findings [37,38].

We next investigated the ability of this system to discriminate between well-established

peptide-specific MHC restricted responses of T-cell clones. We stimulated murine

splenocytes isolated from OT-1 and 2C transgenic mice with dimeric MHC ligands

presenting their cognate and non-cognate peptides. OT-1 and 2C CD8+ T-cells (cytotoxic

T-lymphocytes, CTLs) react well against a broad range of defined peptides presented by

a syngeneic MHC Class I, H-2Kb. OT-1 mice, expressing a transgene for the T-cell

antigen receptor, are reactive with the complex of H-2Kb and the ovalbumin octapeptide

109

SIINSIINFEKL, Kb [39]. As a negative control for this system we used a non-cognate

peptide derived from a peptide library, SIYRYYGL, SIYKb. In contrast, the 2C CTLs are

reactive to SIYKb, but should exhibit a null response to SIINKb [40]. Using our sensor, we

observed a drop in solution pH beginning ~40 sec after addition of SIIN bK dimer (2 μL at

0.5 μg/μL) to OT-1 splenocytes; no response was observed after addition of SIYKb (2 μL

at 0.5 μg/μL), Fig. 5.6a. Conversely, 2C CTLs reacted to the presence of the SIYKb (2 μL

at 0.5 μg/μL), with proton secretion beginning ~40 sec after peptide/MHC addition. The

device showed no discernable changes in conductance when SIINKb (2 μL at 0.5 μg/μL)

was added to 2C splenocytes (Fig. 5.6b).

-25 0 25 50 750.0

1.0µ

2.0µ

3.0µ

4.0µ

5.0µ

6.0µ

7.0µ

|I SD (A

)|

Time (sec)

SIINKb

SIYKb

-25 0 25 50 750.0

1.0µ

2.0µ

3.0µ

4.0µ

5.0µ

6.0µ

7.0µ

|I SD (A

)|

Time (sec)

SIINKb

SIYKb

a

-25 0 25 50 750.0

1.0µ

2.0µ

3.0µ

4.0µ

5.0µ

6.0µ

7.0µ

|I SD (A

)|

Time (sec)

SIINKb

SIYKb

-25 0 25 50 750.0

1.0µ

2.0µ

3.0µ

4.0µ

5.0µ

6.0µ

7.0µ

|I SD (A

)|

Time (sec)

SIINKb

SIYKb

a

-25 0 25 50 75400.0n

600.0n

800.0n

1.0µ

1.2µ

1.4µ

|I SD (A

)|

Time (sec)

SIINKb

SIYKb

-25 0 25 50 75400.0n

600.0n

800.0n

1.0µ

1.2µ

1.4µ

|I SD (A

)|

Time (sec)

SIINKb

SIYKb

b

-25 0 25 50 75400.0n

600.0n

800.0n

1.0µ

1.2µ

1.4µ

|I SD (A

)|

Time (sec)

SIINKb

SIYKb

-25 0 25 50 75400.0n

600.0n

800.0n

1.0µ

1.2µ

1.4µ

|I SD (A

)|

Time (sec)

SIINKb

SIYKb

b

Figure 5.6 | Antigen-specific CTL response. a, OT-1 and (b) 2C splenocytes stimulated with SIINKb and SIYKb dimeric constructs. For both positively-stimulated splenocyte populations (stimulation with SIINKb and SIINKb for OT-1 and 2C cells, respectively), extracellular acidification began at ~40 sec. In these experiments, 2 μL of peptide/MHC (0.5 μg/μL) was added to ~7 × 104 cells.

The observed onset of extracellular acidification of T cells upon stimulation with

peptide/MHC, after a lag of ~40 sec, was longer than that measured for anti-CD3

110

antibody stimulation, ~8 sec. There are two candidate mechanisms responsible for this

observed delay: 1) The kinetics of T cell activation are strongly affected by the dwell

time of the T-cell receptor-activating stimulus [41-43]. Antibodies that trigger the CD3

complex bind with higher affinities (KD ~ 1-10 nM) than peptide/MHC complexes (KD ~

1-100 μM), which may lead to faster intracellular signaling, resulting in earlier acid

release [44]; 2) A smaller population of responsive cells (typically ~20-30% of all

transgenic splenocytes are reactive to the specific antigen) may require a longer time for

accumulation of the signaling molecules needed to achieve sufficient extracellular

acidification.

We distinguish between these possible mechanisms by stimulating dilutions of OT-1 cells

mixed with background splenocytes derived from B6 mice. Upon stimulation with

cognate antigen (SIINKb; 2 μL at 0.5 μg/μL), we observed a decrease in device signal

intensity with decreasing numbers of OT-1 cells, Fig. 5.7. The observed responses were

due to OT-1 splenocyte populations of approximately 28000, 7000, and 700 cells for the

1:3, 1:10, and 1:100 dilutions, respectively. The onset of stimulus-induced extracellular

acidification began ~45-49 sec for all dilutions, indicating that the strength of the

stimulus, rather than changes in the cell density, was responsible for the delay. The |ISD|

values before and after the onset of extracellular acidification are significantly different at

the 99.9% confidence level for all dilutions (T-test). These data are consistent with

previous studies that monitored the dynamics of intracellular calcium flux after

stimulation with different agonists and showed that the duration of the delay after

antigen-specific T-cell triggering correlated with signal strength [45].

111

0 50 100 1501.1µ

1.2µ

1.3µ

|I SD (A

)|

Time (sec)

OT-1 : B6 1 : 3 1 : 10 1 : 100

0 50 100 1501.1µ

1.2µ

1.3µ

|I SD (A

)|

Time (sec)

OT-1 : B6 1 : 3 1 : 10 1 : 100

Figure 5.7 | Detection sensitivity of antigen-specific cells. OT-1 splenocytes were diluted at various ratios with wild-type B6 splenocytes; CTL response to stimulation with SIINKb was measured. The |ISD| values before and after the onset of extracellular acidification are significantly different at the 99.9% confidence level for all dilutions (T-test). All measurements were taken with the same device and in each case 2 μL of peptide/MHC (0.5 μg/μL) was added to ~7 × 104 cells.

5.4 Silicon-Specific NB Functionalization [4]

Although successful functionalization of nanoscale devices with 2-[2-(Undec-10-enyl)-4-

(tetrahydro-2H-pyran-2-yloxy)phenoxy]tetrahydro-H-pyran (2-THP, depicted in Fig.

4.6a) had previously been reported [47], its effect on device transport properties had not

been investigated. Prior to starting functionalized-NB sensing studies, we demonstrate

the effect of functionalization with this molecule on NB device performance. The

ISD(VSD) dependences of a representative p-type (w = 100 nm, t = 40 nm) device before

and after functionalization/subsequent deprotection with 2-THP are given in Figs. 5.8a

and 5.8b, respectively. The gate voltage was decreased from 0V to -40V in -2V steps in

112

Fig. 5.8a, and from 40V to -40V in -2V steps in Fig. 5.8b. The loss of device

responsiveness to gate voltage (non-monotonic dependence with VGD) is observed for the

functionalized device.

a

0 -5 -10 -15 -20 -25

0

-1µ

-2µ

-3µ

-4µ

-5µ

-6µ

-7µ

I SD (A

)

VSD (V)0 -5 -10 -15 -20 -25

0

-1µ

-2µ

-3µ

-4µ

-5µ

-6µ

-7µ

I SD (A

)

VSD (V)

a

0 -5 -10 -15 -20 -25

0

-1µ

-2µ

-3µ

-4µ

-5µ

-6µ

-7µ

I SD (A

)

VSD (V)0 -5 -10 -15 -20 -25

0

-1µ

-2µ

-3µ

-4µ

-5µ

-6µ

-7µ

I SD (A

)

VSD (V)

bb

Figure 5.8 | a, ISD(VSD) dependence of a representative p-type (w = 100 nm, t = 40 nm) NB. VGD was increased from 40 to -40 in 2V steps. b, ISD(VSD) dependence of the NB from (a) after functionalization with and subsequent deprotection of 2-THP. VGD was increased from 40 to -40 in 2V steps.

In order to determine the cause of this detrimental behavior, NB samples were

functionalized with 1-decene and Fig. 5.9 shows the ISD(VSD) dependence with VGD varied

from 40 to -40V in -2V steps for a representative post-functionalized p-type (w = 100 nm,

t = 40 nm) device. The absence of pinchoff for -VSD > 10V implies parallel conduction at

high bias through the functionalization layer. At -VSD < 10V, the leakage is negligible

and the device is suitable for sensing. Taken together these data suggest that the redox-

active hydroquinone/quinone moiety [47-50] is responsible for this detrimental effect.

113

0 -5 -10 -15 -20 -25

0.0

-500.0n

-1.0µ

-1.5µ

-2.0µ

-2.5µ

-3.0µ

I SD (A

)VSD (V)

0 -5 -10 -15 -20 -25

0.0

-500.0n

-1.0µ

-1.5µ

-2.0µ

-2.5µ

-3.0µ

I SD (A

)VSD (V)

Figure 5.9 | ISD(VSD) dependence of a representative p-type (w = 100 nm, t = 40 nm) NB with VGD varied from 40 to -40V in -2V steps after functionalization with 1-decene.

Thus, we continued using the terminal-olefin functionalization approach [51,52] (rather

than other silicon-specific approaches [51,53]) but chose the redox-inactive molecule

dec-9-enyl-carbamic acid tert-butyl ester (CAE) because this molecule had previously

been demonstrated to confer amine functionality to silicon surfaces [54,55]. Although

this technique had previously been demonstrated, its effect on device performance had

not been reported [54,55]. The characteristics of a representative (w = 100 nm, t = 40

nm) p-type NB device before and after functionalization and deprotection are shown in

Figs. 5.10a and 5.10b, respectively. Figure 5.10a shows a plot of the ISD(VSD)

dependence for varying VGD from 0V to -40V in -2V steps (indicated by the black arrow)

and Fig. 5.10b gives a plot of the ISD(VSD) dependence for varying VGD from 40V to -40V

in -5V steps (indicated by the black arrow). The inset in Fig. 5.10b is a highlight of the

black boxed region with VGD varied from 40V to -40V in -2V steps. Device pinch-off is

not achieved for -VSD > 5V consistent with functionalization-induced creation of

alternative conduction paths. The absence of pinchoff for -VSD > 5V implies parallel

conduction at high bias through the functionalization layer. This is similar to, though

114

more pronounced than, the functionalization-induced leakage seen in Fig. 5.9 for the 1-

decene-functionalized device. Thus, these data suggest that a parallel conduction path is

introduced by the Si-C bond formation but is increased by the presence of amine

moieties. However, since the leakage is negligible at -VSD < 5V, the device is well suited

for sensing within this low-bias regime.

a

0 -5 -10 -15 -20

0

-1µ

-2µ

-3µ

-4µ

-5µ

-6µ

-7µ

I SD (A

)

VSD (V)0 -5 -10 -15 -20

0

-1µ

-2µ

-3µ

-4µ

-5µ

-6µ

-7µ

I SD (A

)

VSD (V)

a

0 -5 -10 -15 -20

0

-1µ

-2µ

-3µ

-4µ

-5µ

-6µ

-7µ

I SD (A

)

VSD (V)0 -5 -10 -15 -20

0

-1µ

-2µ

-3µ

-4µ

-5µ

-6µ

-7µ

I SD (A

)

VSD (V)

b

0 -5 -10 -15 -20

0

-1µ

-2µ

-3µ

-4µ

I SD (A

)

VSD (V)

0 -1 -2 -3 -4 -50

-500n

-1µ

0 -5 -10 -15 -20

0

-1µ

-2µ

-3µ

-4µ

I SD (A

)

VSD (V)

0 -1 -2 -3 -4 -50

-500n

-1µ

Figure 5.10 | a, Plot of the ISD(VSD) dependence for varying VGD from 0 to -40V in -2V steps (indicated by the black arrow) for a representative p-type (w = 100 nm, t = 40 nm) device. b, Plot of the ISD(VSD) dependence for varying VGD from 40 to -40V in -5V steps (indicated by the black arrow) for the NB from (a) after functionalization with CAE and deprotection. The inset is a highlight of the black boxed region with V varied from 40 to -40V in -2V steps. GD

Due to the low yield of functionalized NBs after treatment with CAE [4], we used the

APTS modification approach [3,13,56,57] for some sensing measurements. As with the

terminal olefins, though this method had been reported to successfully functionalize

silicon NWs, no study on its effects on device transport properties had been performed.

Figure 5.11a and 5.11b below give ISD(VSD) dependences for a representative NB before

and after surface modification, respectively. The coating is seen to have a minimal effect

on device transport, expected because the native oxide remains intact with this technique.

115

aa b

0 -5 -10 -15 -20

0.0

-500.0n

-1.0µ

-1.5µ

-2.0µ

I SD (A

)

VSD (V)

VGD =-40

-200 -5 -10 -15 -20

0.0

-500.0n

-1.0µ

-1.5µ

-2.0µ

I SD (A

)

VSD (V)

VGD =-40

-20

b

0 -5 -10 -15 -20

0.0

-500.0n

-1.0µ

-1.5µ

-2.0µ

I SD (A

)

VSD (V)

VGD =-40

-200 -5 -10 -15 -20

0.0

-500.0n

-1.0µ

-1.5µ

-2.0µ

I SD (A

)

VSD (V)

VGD =-40

-20

Figure 5.11 | a, ISD(VSD) dependence for VGD varied in -2V steps for a representative device in air before functionalization with APTS. The inset is an optical micrograph of a representative photoresist-protected device. The exposed NB is yellow, the exposed oxide is blue, and the photoresist protection is beige. Die coloration is due to process-induced variations in the thin film compositions and thicknesses. The inset is a different device from that used for the ISD(VSD) dependence measurement. b, ISD(VSD) dependence for VGD varied in -2V steps in air after functionalization with APTS for the same device used for the I ) dependence in (a). SD(VSD

5.5 Nanobar Sensor Characterization [4,18]

The ability of NBs to sense bound macromolecular charge was characterized using the

well-known biotin-avidin/streptavidin interaction. As described in Chap. 2, in order to

avoid the critically important problem of Debye screening [14], the salt concentrations in

the buffers used for macromolecular sensing experiments were chosen such that the

Debye screening length (λD) was long enough so as not to impede sensing, but short

enough such that unbound macromolecules would be screened [58]. We first determined

biotinylated device [17] responses to streptavidin, biotin-quenched streptavidin

(streptavidin pre-treated with five equivalents of biotin), and avidin, all introduced at a 1

116

nM concentration. Figure 5.12 shows a plot of |ISD| vs. time for these devices as well as

for a control device functionalized with poly(ethylene glycol) (PEG), which has

previously been shown to resist protein binding [17]. It should be noted that time = 0 is

defined as the onset of protein addition for this and all subsequent figures. The addition

of streptavidin resulted in a current increase due to the protein’s negative charge (pI ~

5.6), whereas the previously-quenched streptavidin elicited no response. In contrast,

upon introduction of avidin, the current decreased because of the protein’s positive

charge (pI ~ 10.5).

-20 0 20 40 600

100n

200n

300n

|I SD (A

)|

Time (sec)

StreptavidinQuenched S-AvPEGylatedAvidin

Figure 5.12 | Plot of |ISD| vs. time. Sensor response to 1 nM protein solutions demonstrating specific protein recognition, and the dependence of the signal on protein charge. Black: PEG-functionalization with 1 nM streptavidin (pI ~ 5.6) addition; Red: Biotin-functionalization with 1 nM streptavidin addition; Green: Biotin-functionalization with 1 nM quenched-streptavidin (streptavidin treated with 5 equivalents of biotin prior to use) addition; Blue: Biotin-functionalization with 1nM avidin addition (pI ~ 10.5).

To unequivocally demonstrate that the biotin-streptavidin interaction was responsible for

sensor response, biotinylation of one sensor was performed with a cleavable molecule

[sulfosuccinimidyl 2-(biotinamido)-ethyl-1, 3-dithiopropionate, SS-biotin], while a

117

second device was biotinylated with a non-cleaving molecule [sulfosuccinimidyl-6-

(biotinamido)hexanoate, LC-biotin]. The response of each sensor to streptavidin is

similar, as seen in the plot of |ISD| vs. time in Fig. 5.13, which is expected because the

spacer-arm length of the molecules is similar—2.4 nm for the SS-biotin and 2.2 nm for

the LC-biotin. The subsequent addition of a reducing agent [tris(2-

carboxyethyl)phosphine hydrochloride, TCEP)], added as indicated by the appropriately

colored arrow, cleaved the disulfide bond [47], with the resultant current returning to the

original baseline value. The LC-biotin control, which does not cleave, was insensitive to

the reducing agent.

-40 -20 0 20 40 60 80 100 120 140

100.0n

200.0n

300.0n

|I SD (A

)|

Time (sec)

SS-BiotinLC-Biotin

-40 -20 0 20 40 60 80 100 120 140

100.0n

200.0n

300.0n

|I SD (A

)|

Time (sec)

SS-BiotinLC-Biotin

Figure 5.13 | Plot of |ISD| vs. time. Demonstration of the reversibility of sensor response to streptavidin addition and removal. Red: functionalization with LC-biotin (sulfo-NHS-biotin with a 2.2-nm PEG linker); Green: functionalization with SS-biotin (sulfo-NHS-biotin with a 2.4-nm linker with a dithiol bond). After a preliminary baseline was established, 1 nM streptavidin was added and a new equilibrium was reached. The reducing agent tris(2-carboxyethyl)phosphine (TCEP) was added as shown by the arrow (tail color corresponds to experiment). The LC-biotin produced a minimal response, while the SS-biotin functionalized sensor returned to baseline.

Device sensitivity to protein charge and concentration, the hallmarks of FET sensing,

were also studied. Avidin is positive in neutral solutions due to its high isoelectric point,

but its effective charge can be decreased by increasing solution pH. The normalized |ISD|

118

vs. time plot in Fig. 5.14 demonstrates decreased device sensitivity with increasing

solution pH (all solutions are 1 nM avidin; solution pH values are given in the legend).

This result unequivocally shows that the protein charge is responsible for the observed

gating effect. To optimize protein sensing, it is therefore imperative that the |pHsolution –

pI| be maximized.

-20 0 20 400.2

0.4

0.6

0.8

1.0

1.2

Nor

mal

ized

|ISD

|

Time (sec)

pH 10.5pH 9.0pH 7.4

Figure 5.14 | Plot of normalized |ISD| vs. time. Demonstration of sensor response to protein charge. Three solutions with different pH values were added and 1 nM avidin in the appropriate pH buffer was added in each case.

An exploration of the detection limit of these sensors is shown in the normalized |ISD| vs.

time plot in Fig. 5.15a, where streptavidin concentrations are decreased from 1 nM to 10

fM, as indicated in the legend. The 10 fM solution has an initial signal-to-noise response

of 140, implying a detection floor of ~70 aM. In all experiments, the initial solution

induces a rapid signal increase and close inspection of the post-transition current reveals

that the response at the highest protein concentrations saturates, likely fully coating the

sensor with bound protein during solution exchange. The signal does not saturate,

however, for the experiments with lower concentrations, Fig. 5.15b and 5.15c. For the

119

100 fM streptavidin case (Fig. 5.15b), the signal increases throughout the post-transition

mixing period (beginning at ~12 sec) until reaching a final, saturated value at ~50 sec;

this exponentially-decreasing binding agrees with a single ligand-receptor interaction, as

expected for the biotin-streptavidin system [17]. The device current for the experiment

with the 10 fM streptavidin solution did not saturate, Fig. 5.15c, suggesting that the

streptavidin-binding sites on the NB were not fully occupied. Thus, we can assume that

the binding is still in the linear regime of the exponential apparent in Fig. 5.15b.

-20 0 20 400.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

Nor

mal

ized

|ISD

|

Time (sec)

1 nM10 pM100 fM10 fM

a

-20 0 20 400.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

Nor

mal

ized

|ISD

|

Time (sec)

1 nM10 pM100 fM10 fM

a

10 20 30 40 50

|I SD (A

)|

Time (sec)

100 fM

b

200n

150n10 20 30 40 50

|I SD (A

)|

Time (sec)

100 fM

b

10 20 30 40 50

|I SD (A

)|

Time (sec)

100 fM

b

200n

150n0 10 20 30 40 50

|I SD (A

)|

Time (sec)

10 fMc

200n

125n0 10 20 30 40 50

|I SD (A

)|

Time (sec)

10 fMc

200n

125n

Figure 5.15 | a, Plot of normalized |ISD| vs. time. Demonstration of NB sensitivity for decreasing concentrations of streptavidin added to four sensors. b, Plot of |ISD| (log scale) vs. time for the 100 fM sample in (a). c, Plot of |ISD| (log scale) vs. time for the 10 fM sample in (a).

120

We next sought to use these data to verity that our sensor setup discussed in Chap. 2 was

not diffusion limited. In order to use Eqn. 2.6 to determine the number of filled surface

binding sites, Ns, a value for the charge-transfer coefficient, α, was required. By

assuming that all possible surface binding sites were filled at device saturation for the

three higher concentrations, we obtained an average α = 3.27 × 106. Using this value, we

calculate the number of sites on the NB bound for the 10 fM concentration study at two

points: after the initial solution exchange (~10 sec) is complete and at the conclusion of

the measurement (~55 sec). At the first point, ~30% occupancy of NB binding sites is

achieved, thus convection clearly dominates—the molecular flux to the surface is ~1 ×

105 molecules/min. A comparison with the binding site occupancy results of the NB

from the 100 fM streptavidin study, which achieved ~72% occupancy after the initial ~12

sec solution exchange, illustrates the impact of concentration on binding effenciency. For

the 10 fM experiment, after an additional ~45 sec, ~50% occupancy is obtained, thus

~1.5 × 104 molecules/min arrive at the NB, a significantly greater flux than that expected

from diffusion alone (~1 molecule/min, from Fig. 2.5). These findings suggest that

convection dominates in our experimental system both during and following solution

exchange (the solution was mixed throughout the course of the measurement, akin to

pipetting up-and-down).

The potential power for NW sensors is as part of an integrated system with on-chip signal

processing, error detection, and complementary detection [7-9,14] to avoid false

positives. Inversion-mode device responses to 1 nM solutions of streptavidin or avidin

121

are shown in the plot of ISD vs. time in Fig. 5.16. These devices react with the opposite

sense of the accumulation-mode devices shown previously.

-20 0 20 40

100n

200n

300n

400n

I SD (A

)

Time (sec)

AvidinStreptavidin

Figure 5.16 | Plot of ISD vs. time. Demonstration of complementary sensing, showing the response of an inversion-mode sensor to 1 nM streptavidin (red) and avidin (blue) solutions. This is the opposite response of the accumulation-mode devices in Fig. 5.12.

An understanding of the effects of Debye screening on molecular charge is crucial for

any charge-based sensor. We studied this effect by varying the salt concentration of

solutions used for a single NB sensor. Devices used for these studies were photoresist

protected and functionalized using the APTS approach and subsequently functionalized

with SS-biotin. For monovalent ions, λD is roughly inversely proportional to the square

root of the ionic concentration, thus our buffers must have low salt concentrations to

enable sensing. We used three titrations of PBS—1X, 0.1X, and 0.01X—with

corresponding Debye lengths of 0.7, 2.3, and 7.3 nm, respectively (see Table 2.1), as

illustrated schematically in Fig. 5.17.

122

Figure 5.17 | Schematic (not to scale) showing λD relative to the device surface. The blue bar represents the active region of the device, the yellow regions the leads (S = source, D = drain), the gray hashed region the underlying oxide, the purple diamonds are biotin, and the red objects are streptavidin. The negative charges surrounding the protein represent its negative charge. The green “1X” line (also not to scale) represents the screening length (λD) from 1X PBS relative to the protein and the blue and orange lines represent that from 1:10 and 1:100 dilutions of this buffer, respectively.

For the |ISD| vs. time plot shown in Fig. 5.18a, after the establishment of a baseline current

in 0.01X PBS, 10 nM streptavidin was added in the same buffer. As in Fig. 5.12, the

binding of streptavidin to the biotinylated NB resulted in an increased |ISD| of the p-type

device (red arrows indicate onsets of solution exchange). The ionic strength of this

buffer yields λD ~ 7.3 nm, thus the majority of the protein’s charge is unscreened at the

NB surface. A tenfold increase in the ionic strength of the buffer (0.1X PBS, λD ~ 2.3

nm) partially screens streptavidin’s intrinsic charge and a further tenfold increase in

buffer ionic strength (1X PBS, λD ~ 0.7 nm) effectively screens the majority of the

protein’s charge, returning the |ISD| approximately to its baseline value. It should be

noted that changes in salt concentration at room temperature have been shown to have a

minimal effect on streptavidin conformation (streptavidin-biotin binding is unchanged),

thus the observed changes in |ISD| are due solely to differences in λD [59-61]. In order to

demonstrate complete protein screening, 1 μM TCEP in 0.01X PBS—which, as shown in

Fig. 5.18a cleaves the dithiol bond, thereby removing the streptavidin from the surface—

was added last and the signal remains at baseline. Thus, controlled buffer screening of

bound molecular charge is demonstrated.

123

a

0 100 200 300

650n

700n

750n|I S

D (A

)|

Time (s)

0.1X 1X TCEP

.01X

S-Av

0 100 200 300

650n

700n

750n|I S

D (A

)|

Time (s)

0.1X 1X TCEP

.01X

S-Ava

0 100 200 300

650n

700n

750n

b

0 100 200 300600.0n

800.0n

1.0µ

|I SD (A

)|

Time (s)

t = 0:.01X AloneS-Av (.01X)

.1X 1X .01X TCEP.01X

0 100 200 300600.0n

800.0n

1.0µ

|I SD (A

)|

Time (s)



b

0 100 200 300600.0n

800.0n

1.0µ

|I SD (A

)|

Time (s)



0 100 200 300600.0n

800.0n

1.0µ

|I SD (A

)|

Time (s)


.1X 1X .01X TCEP.01X|I SD (A

)|

Time (s)

0.1X 1X TCEP

.01X

S-Av

0 100 200 300

650n

700n

750n|I S

D (A

)|

Time (s)

0.1X 1X TCEP

.01X

S-Av

Figure 5.18 | a, Biotin-functionalized sensor response (|ISD| vs. time) to varying buffer ionic concentrations with (red) and without (black) streptavidin addition at time = 0. The red text gives the PBS buffer concentration (TCEP was added in 0.01X PBS) and the red arrows represent the onset of solution exchange. b, Biotin-functionalized sensor response (|ISD| vs. time) to varying buffer ionic concentrations with streptavidin addition at time = 0 (red) and no streptavidin addition (black). The blue text gives the PBS buffer concentration (TCEP was added in 0.01X PBS) and the blue arrows represent the onset of solution exchange. The two results derive from different devices.

A similar experiment was performed with a second NB device, but prior to the addition

of the TCEP, 0.01X PBS (without streptavidin) was again added, Fig. 5.18b. Upon

addition of this low-salt buffer, the |ISD| signal is seen to begin returning to its original

value. This slow increase is most probably due to residual salt. As a control, a different

NB device was treated with the same series of buffers as that in Fig. 5.18b but without

the presence of streptavidin in the first buffer, Fig. 5.18b. The |ISD| signal of this device

remains constant due to the lack of bound charge (biotin is neutral), validating that the

current changes observed in the previous data were due to the screening of bound charge.

124

5.6 Nanobar Sensing of Unlabeled Proteins and DNA [4,18]

Device utility for immunodetection applications using antibodies was demonstrated with

commercially available antibodies to mouse immunoglobulin G (IgG) and mouse

immunoglobulin A (IgA) proteins. A cross-comparison assay was performed by first

functionalizing two devices with goat-anti-mouse IgG and two additional devices with

goat-anti-mouse IgA [17,62]. Devices from each group were then used to sense 100 fM

antigen. The |ISD| vs. time plots in Figs. 5.19a (goat-anti-mouse IgG-coated sensor) and

5.19b (goat-anti-mouse IgA-coated sensor) show clear discrimination (after injection

transient noise) of the specific antigen over the nonspecific control for the reciprocal

cases, demonstrating selective immunodetection. The PEGylated controls in Figs. 5.19a

and 5.19b show no response to 100 fM IgG and to 100 fM IgA, respectively. Two

inversion-mode devices were functionalized with goat-anti-mouse IgG and demonstrate

appropriately inverted and null responses to the presence of mouse IgG and mouse IgA,

respectively, Fig. 5.20. Thus, the ability of selectively functionalized NBs to detect

antibodies at <100 fM concentrations, additionally with complementary electronic

response, was demonstrated.

125

a

-20 0 20 4050n

75n

100n

125n

150n

175n

200n

225n|I S

D (A

)|

Time (sec)

PEG-ylatedmouse-IgGmouse-IgA

a

-20 0 20 4050n

75n

100n

125n

150n

175n

200n

225n|I S

D (A

)|

Time (sec)


b

-20 0 20 40 60100n

150n

200n

250n

|I SD (A

)|

Time (sec)


b

-20 0 20 40 60100n

150n

200n

250n

|I SD (A

)|

Time (sec)


Figure 5.19 | Plot of |ISD| vs. time for functionalized NB response to antibody introduction. a, Goat-anti-mouse IgG-functionalized and (b) goat-anti-mouse IgA-functionalized sensor response to 100 fM mouse-IgG (red) or 100 fM mouse-IgA (blue) are shown. The black curve shows the response of a PEG-functionalized sensor to (a) IgG and (b) IgA.

-20 -10 0 10 20 30

100n

120n

140n

160n

|I SD (A

)|

Time (sec)

Flow mouse-IgGFlow mouse-IgA

Figure 5.20 | Plot of ISD vs. time for functionalized, inversion-type (n-type) NB response to antibody introduction. Goat-anti-mouse IgG-functionalized sensor response to 100 fM mouse-IgG (red) or 100 fM mouse-IgA (blue) are shown.

For the case of NB-based DNA sensing, previous studies have highlighted the importance

of choosing an appropriate buffer ion concentration such that hybridized DNA produces a

signal while unbound DNA does not [12,14]. For specific ssDNA sensing experiments

we used 0.05X PBS, which has λD ~ 3.3 nm (schematically illustrated for complementary

and noncomplementary DNA in Figs. 5.21a and 5.21b, respectively); this Debye length

126

screens unbound DNA. In later experiments designed to highlight the importance of

charge screening, we use a buffer with λD ~ 7.3 nm (Fig. 5.21c) and DI (18 MΩ), which

has λD ~ 240 nm.

Figure 5.21 | Schematic (not to scale) showing λD relative to the device surface for 0.05X PBS with hybridized DNA 20-mers (complementary capture and probe strands). The majority of the probe DNA’s charge lies within the screening distance. b, Schematic (not to scale) showing λD relative to the device surface for 0.05X PBS with noncomplementary, unhybridized DNA strands. Few probe DNA molecules lie within the screening distance. c, Schematic (not to scale) showing λD relative to the device surface for 0.001X PBS with noncomplementary, unhybridized DNA strands. Some probe DNA molecules lie within this larger screening distance.

Device utility for specific ssDNA strand recognition was demonstrated by performing a

cross-comparison assay using APTS-functionalized devices§§. Two devices were

functionalized with the DNA-capture(1) [C(1)] sequence and two others with the DNA-

C(2) sequence [63]. Under active measurement conditions (VSD = -2V, VGD = -35V) and

after the establishment of a baseline signal in 0.05X PBS, the solution was exchanged

with 10 pM solutions of either DNA(1) or DNA(2) in the same buffer [63]. Figure 5.22a

and 5.22b show the responses of the DNA-C(1)- and DNA-C(2)-functionalized devices,

respectively, to DNA(1) and DNA(2). In both cases, complementary pairing results in an

increase in |ISD|, as expected for a p-type device, while the noncomplementary negative

§§ The time required for full DNA hydbridization required photoresist-protected devices to be used.

127

controls show little change in signal. The 35-50 sec time for complete 20-mer

hybridization is consistent with that observed previously for silicon NW-FET studies

[12,13]. The variation between device response times may be due to different DNA

binding rates on the NBs, a known problem with nanoscale surface coatings [64]. The

negligible signal of the negative controls indicates that our choice of λD ~ 3.3 nm

effectively screened unbound DNA.

a

-50 0 50 100 150

2.0µ

2.2µ

2.8µ

3.0µ

3.2µ

|I SD (A

)|

Time (sec)

Probe 1 Probe 2

-50 0 50 100 150

2.0µ

2.2µ

2.8µ

3.0µ

3.2µ

|I SD (A

)|

Time (sec)

Probe 1 Probe 2

a

-50 0 50 100 150

2.0µ

2.2µ

2.8µ

3.0µ

3.2µ

|I SD (A

)|

Time (sec)

Probe 1 Probe 2

-50 0 50 100 150

2.0µ

2.2µ

2.8µ

3.0µ

3.2µ

|I SD (A

)|

Time (sec)

Probe 1 Probe 2

b

-50 0 50 100 150500.0n

1.0µ

3.0µ

3.5µ

|I SD (A

)|

Time (sec)

Probe 1 Probe 2

-50 0 50 100 150500.0n

1.0µ

3.0µ

3.5µ

|I SD (A

)|

Time (sec)

Probe 1 Probe 2

b

-50 0 50 100 150500.0n

1.0µ

3.0µ

3.5µ

|I SD (A

)|

Time (sec)

Probe 1 Probe 2

-50 0 50 100 150500.0n

1.0µ

3.0µ

3.5µ

|I SD (A

)|

Time (sec)

Probe 1 Probe 2

Figure 5.22 | Response of NBs functionalized with the (a) Capture 1 and (b) Capture 2 DNA strands to the addition of 10 pM solutions of probe DNA strands 1 (blue) and 2 (red). Solution exchange occurred at time = 0, highlighted by the dashed line.

In order to study the effect of Debye screening on DNA sensing, we used a low ionic

strength buffer (0.001X PBS; dPBS; λD ~ 23.2) and DI (λD ~ 240), both of which fail to

screen unbound molecules, Fig. 5.23. A NB was functionalized with the DNA-C(1)

strand and after a baseline sensor response was established in DI under active

measurement conditions, a 1 nM solution of DNA(2) (noncomplementary, NC) in DI was

added. Although hybridization between the NC-DNA and DNA-C(1) strands does not

occur, the absence of ions to screen the probe DNA molecules results in an increase in

128

device current. Similar DI-induced false-positives were observed previously with silicon

NW-FETs [12]. After device equilibration, a 10 nM solution of NC-DNA in dPBS was

added; the observed signal decrease is due to ionic screening. However, the signal does

not completely return to baseline due to λD ~ 23.2 nm, showing that unbound DNA

molecules can be observed for very low-salt buffers.

Solution exchange was again performed and a 1 nM solution of DNA(1)

(complementary, C) in DI was added. The absence of ions again resulted in an

immediate increase in |ISD| to approximately the same level as with the NC-DNA in DI.

Here, however, the signal continued to increase for ~30 sec, indicative of DNA

hybridization, as observed in Fig. 5.22. When this solution was replaced with a 1 nM

solution of C-DNA in dPBS, the current level decreased due to the screening of a

majority of the unbound DNA, but the signal remained high relative to that observed with

the NC-DNA in dPBS due to the bound C-DNA.

0 50 100 150 200 250900.0n

1.0µ

1.1µ

1.2µ

1.3µ

1.4µ

1.5µ

|I SD (A

)|

Time (sec)

DI

NC, DI

NC,dPBS

C, DI

C,dPBS

0 50 100 150 200 250900.0n

1.0µ

1.1µ

1.2µ

1.3µ

1.4µ

1.5µ

|I SD (A

)|

Time (sec)

DI

NC, DI

NC,dPBS

C, DI

C,dPBS

Figure 5.23 | Plot of |ISD| vs. time showing NB response to NC and C DNA in DI and dPBS. The green arrows represent the onset of solution exchange and the blue text indicates solution components. No DNA was present in the DI while the initial baseline was established.

129

5.7 Conclusions

These data demonstrate that properly configured NBs can serve as pH detectors and,

when functionalized, as specific macromolecular detectors for applications that demand

ultrasensitivity with unlabeled reagents. Our cellular measurements showed that NBs can

be utilized to differentiate cell types from as few as ~210 cells, a technique that could

have powerful applications in diagnostics. Functionalized sensor measurements

demonstrated the ability of the devices to detect low concentrations of specific antibodies

(100 fM) and ssDNA (10 pM). These findings, in addition to our characterization of NB

response to Debye screening and our demonstrations of complementary sensing,

demonstrate the potential of the NBs for label-free detection of cellular response and

biomolecules.

130

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138

Chapter 6: Conclusion

We have described a novel approach to realizing fully complementary metal-oxide-

semiconductor (CMOS)-integrable silicon nanowire (NW)-like devices (nanobars, NBs)

that are capable of measuring real-time, live cellular responses and specific proteins and

DNA strands at concentrations in the femtomolar regime [1-3]. Additionally, we

demonstrated complementary sensing with n- and p-type devices and characterized

device response to molecular charge and buffer-induced ionic screening. Our work has

the potential not only to radically change clinical testing and screening but also to add

previously unheard of capabilities to assays used by basic researchers. For example, our

finding that protein sensing with NBs was dependent on the magnitude of the difference

between the solution pH and the charge-neutral or isoelectric point of the protein (pI),

|pHsolution – pI|, should enable the use a linear pH gradient to determine unknown protein

pIs, currently an extremely difficult task.

We have shown that unfunctionalized NBs are well-suited for the detection of stimulus-

induced extracellular acidification within seconds after stimulation at an unprecedented

level of sensitivity, ~210 cells (30% of 700). Though work to date has focused on one

specific cell type with variable specificities, these findings are likely to be extended to

other systems, because acid release is triggered by a general signal transduction pathway

through the generation of acidic metabolites or the activation of proton membrane

transporters [4]. The ultrasensitivity of this methodology, combined with the small

139

sample volumes required, the rapid response times observed, the suitability for high-

throughput analysis, and the ability to integrate into full electronic on-chip systems,

positions this technology for insertion into basic and clinical settings requiring detection

of antigen-specific responses. For example, the NBs could be used for rapid, inexpensive

screening of vaccine efficacy.

Throughout the work described herein, it is important to note that extensive care was paid

to theoretical considerations of functionalization, fluid exchange, and ionic screening. It

is very possible that initial reports of selective detection [5-9] may have been

misinterpreted as they did not fully consider these issues. A major finding of this thesis

was to show under what conditions true selective detection can be unambiguously

determined.

It is important to note that two significant obstacles to NB sensing currently exist. First,

device-to-device variation is still large (especially for the case of n-type, inversion-mode

devices), although this problem should be easily addressed with fabrication in an

industrial facility. Second, a high-yield method for conjugating organics selectively to

silicon surfaces, a critical requirement for specific protein and DNA sensing

measurements, has not yet been demonstrated. Although we utilized a number of

approaches in this work, each was plagued by significant shortcomings. Serious attention

must be paid to these issues in order to enable this technology to reach its full potential as

a high-density array of label-free sensors, each with specificity for a different molecule

(and, potentially, with different sensitivity thresholds).

140

Although this work focused on device and sensor performance, the strength of the

approach lies in seamless integration with CMOS technology. The ability to fabricate

NBs with a traditional parallel lithographic approach in concert with their full CMOS-

compatibility may enable the NBs to be applied to many disparate sensing environments,

from clinical diagnostics—using functionalized devices to specifically detect proteins and

DNA strands and unfunctionalized devices to screen cell types—to chemical and

biological weapons sensors—using an array of functionalized devices to screen for

airborne pathogens. In addition to their unprecedented sensitivity, the devices should

greatly decrease sample preparation costs in terms of reagents, time, and amount of

sample required, which will be greatly beneficial in both clinical and research settings.

The label-free detection mechanism should enable previously difficult field sensing of

chemicals—from screening for potential pathogens to monitoring water quality—and

through the use of chemical switches such as ribozymes [10], the NBs could be

configured to sense any molecular species of any size.

Thus, the work presented in this thesis could provide the foundation for revolutionizing

sensing across a vast number of fields. Label-free sensing, in conjunction with

microelectronic integration, should greatly decrease costs in numerous clinical, public

health, and basic research applications. Additionally, this new platform may enable

researchers to explore heretofore unobservable biomolecular properties and interactions.

141

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antigen-specific T cell immune responses with semiconducting nanowires.

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screening length. Submitted.

4. Wada, H. G. et al. GM-CSF triggers a rapid, glucose dependent extracellular

acidification by TF-1 cells: evidence for sodium/proton antiporter and PKC

mediated activation of acid production. J. Cell. Physiol. 154, 129-138 (1993).



1281-1292 (2001).

6. Hahm, J.-i. & Lieber, C. M. Direct ultrasensitive electrical detection of DNA and


(2004).




of small-molecule-protein interactions by using nanowires nanosensors. Proc.

Natl. Acad. Sci. U.S.A. 102, 3208-3212 (2005).

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9. Zheng, G., Patolsky, F., Cui, Y., Wang, W. U. & Lieber, C. M. Multiplexed

electrical detection of cancer markers with nanowire sensor arrays. Nature

Biotech. 23, 1294-1301 (2005).

10. Zivarts, M., Liu, Y. & Breaker, R. R. Engineered allosteric ribozymes that

respond to specific divalent metal ions. Nucl. Acid. Res. 33, 622-631 (2005).

143

Appendix I: Functionalization Methods

AI.1 Electropolymerization Methods

Chip Patterning. For indium tin oxide (ITO) devices, positive photoresist (S1813) was

spun on ITO slides purchased from Sigma-Aldrich. The resist was patterned by contact

photolithography using a CAD Art Services transparency mask and the ITO was etched

with TE-100 tin etchant at 50ºC (Transene). For polysilicon-on-oxide samples, a doped

polysilicon deposition was performed by R. Ilic at the Cornell Nanofabrication Facility

and photoresist patterning was performed at Yale as for the ITO samples. A silicon wet

etch (126 : 50 : 1 deionized water : nitric acid : ammonium fluoride) was used to define

the structures. Chrome-on-oxide samples were fabricated with NW contacting procedure

outlined above.

Electrode Preparation. The reference electrode was fabricated by depositing AgCl on

Ag wire (Earnest Fullham, Inc) in an electrochemical cell from a saturated aqueous NaCl

solution. The counter electrode is a Pt wire (Earnest Fullham, Inc) and the working

electrode was contacted with a Cascade Microprobetip.

Electrodepositions. Tyramine, 4-hydroxybenzaldehyde, and 4-hydroxyphenylacetic acid

were purchased at the highest available grade (Sigma-Aldrich) and used without further

purification. The modified phenols were dissolved to 50mM in 1X PBS, pH = 7.4, using

144

ultrasonication; fresh solutions were made at least every hour. Electropolymerization

depositions on ITO were performed using a Gamry Femtostat by cycling the counter

electrode voltage three times from 0.1 to -4V versus the reference electrode at a sweep

rate of 100 mV/s (note that with the Gamry setup in the lab this is from -0.1 to +4V). A

comparison of depositions performed on bulk and patterned ITO shows that the peak

current during deposition scales linearly with working electrode area. Following

deposition, samples were washed with PBS and treated with this buffer with stirring for

15 minutes. Comparing depositions on bulk and patterned ITO, it is evident that the

electropolymerization peak current scales linearly with working electrode surface area.

Electrodepositions from 100mM modified-phenol in 0.1M KOH in methanol were

performed for comparison and similar results to those presented were obtained; these

solutions were used for depositions on polysilicon, silicon, and chrome. It is important to

note that nucleophilic R groups such as amines must be at least one carbon removed from

the phenyl ring, or they will also polymerize and, hence, be rendered inactive [1]. It

should also be noted that we have observed functional electropolymerized films created

from 3-hydroxybenzaldehyde and 3-hydroxyphenylacetic acid. Though not studied in

this work, ketone functionality can also be obtained by the electropolymerization of

modified phenols [2].

Silicon and Polysilicon Depositions. Successful depositions on these materials were

only achieved under inert conditions (in a N2 glovebox), directly after etching with

buffered oxide etch (BOE). It should be noted that the BOE solution must be completely

145

removed from the cell prior to electrochemical cycling because hydrofluoric acid (HF), a

component of BOE, etches silicon under such conditions.

Thickness determinations. Three thickness measurements were performed on each of

five patterned samples, in which one lead had been coated by electrodeposition. These

measurements were taken with a Tencor AlphaStep IQ surface profilometer, which was

calibrated to have ~5 nm step-height resolution. For each measurement three leads were

swept, with the coated lead located between two uncoated leads. The step-heights are

determined using the packaged software, which calculates the difference between the

average height of the lead and that of the base flanking the lead. The step-heights of the

unfunctionalized leads are averaged and the thickness of the film is then calculated by

subtracting this value from the step-height of the functionalized lead. Of the 15 total

measurements, none of which gave negative film thicknesses, four yielded film

thicknesses <5 nm, which is below the resolution of the profilometer.

Blocking measurements. The solution for blocking measurements consists of 50mM

Fe2+/Fe3+ in 0.1M KCl. The blocking measurements were performed by sweeping from -

0.5 to 0.5V versus the reference electrode at 500 mV/s ten times; the tenth curve for each

measurement is plotted.

Sample washing. Prior to all conjugation reactions, chips were rinsed three times with

1X PBS and treated with this buffer for 15 min with agitation. Before imaging, each chip

146

was rinsed with deionized water and blown dry with nitrogen gas. It should be noted that

this drying procedure displaces the glass chips that fluoresce due to nonspecific binding.

Amine fluorescence conjugation. Samples were reacted with fluorophores (Molecular

Probes) at 0.25 mg/mL in a pH=8.5 bicarbonate buffer at room temperature for 1 hr with

agitation. The red fluorophore is AlexaFluor 568 succinimidyl ester and the blue is

AlexaFluor 350 succinimidyl ester.

Aldehyde and carboxylic acid fluorescence conjugation. Samples were reacted with

fluorophores at 0.25 mg/mL in a pH=5.5 acetate buffer for 1 hr at room temperature with

agitation. The fluorophore used to bind aldehyde was AlexaFluor 488 hydrazide, sodium

salt, and that used to bind carboxylic acid was AlexaFluor 568 hydrazide, sodium salt.

The amine-coated slide used as a positive control was purchased from BioSlide, Inc.

Amine quantification. Slide surface free amine quantification was performed based on a

serially diluted lysine standard run in triplicate; bound o-phthaldialdehyde (Sigma) was

excited at 360 nm and the fluorescence was measured at 460 nm.

Amine and aldehyde quenching. Amine-coated samples were treated with 0.1 M sulfo-

N-hydroxysuccinimide (NHS) in pH=8.3 bicarbonate for 1 hr at room temperature with

agitation for quenching. Aldehyde-coated samples were quenched with 0.1M hydrazine

in pH=6.5 acetate buffer for 1 hr at room temperature with agitation.

147

Carbodiimide couping, antibody binding, and oligonucleotide hybridization.

Carboxylic acid groups (either on BSA or bound to ITO) were treated with 0.015M 1-

Ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC) and 0.03M NHS at pH=5.5 and

amine groups were treated with pH=9.5 buffer for 15 mins at room temperature with

agitation. The solutions were then combined and left for 1 hr at room temperature with

agitation. The final BSA concentration was 1 mg/mL. It should be noted that NHS and

EDC are not required for the amine-aldehyde reaction of the DNA 20-mer conjugation.

Antibody binding was performed in 1X PBS at 37°C for 1 hr at a concentration of 100

μg/mL. Oligonucleotide hybridization was performed at a concentration of 50 μM in 1X

SCC buffer (pH=7.2) with 0.05% sodium dodecylsufate at room temperature for 30 mins

with agitation.

DNA oligonucleotide sequences. The amino-terminated DNA 20-mer sequence was 5'-

H2N-CGCCACTGCGTCACTGCAGG-3' and the fluorescently-labeled sequence was 5'-

FAM-CCTGCAGTGACGCAGTGGCG-3' (Integrated DNA Technologies, Inc).

BSA quantification. The bound BSA concentration was quantified with an absorbance

measurement at 562 nm using a micro BCA protein assay kit (Pierce Scientific) based on

a serially diluted BSA standard run in triplicate.

Fluorescent imaging. All images were taken with a Nikon microscope using GFP

(green), DAPI (blue), or TRITC (red) filters.

148

AI.2 Additional Oxidative Electropolymerization Results

The cyclic voltammograms (CVs) for the electrochemical depositions of 4-

hydroxybenzaldehyde and 4-hydroxyphenylacetic acid are given in Figs. AII.1 and AII.2,

respectively. The peaks are similar to that seen for tyramine electropolymerization in

Fig. 4.3.

-4 -3 -2 -1 0

0

25µ

50µ

OH

O

HI M (A

)

VF (V vs. Ref)


-4 -3 -2 -1 0

0

25µ

50µ

OH

O

OHI M (A

)

VF (V vs. Ref)


Figure AI.1 Figure AI.2

The insulating nature of the films was evaluated by performing blocking measurements

with an iron(II)/iron(III) redox couple. A cyclic voltammogram of the blocking solution

on bare ITO, polytyramine-coated ITO (NH2), poly-4-hydroxybenzaldehyde-coated ITO

(CHO), and poly-4-hydroxyphenylacetic acid-coated ITO (COOH) is given in Fig. AI.3.

Cyclic voltammetry with this solution was first performed on a bare ITO surface and

substantial oxidation and reduction peaks due to the conducting substrate are evident.

These peaks are not apparent in blocking measurements performed after film deposition,

consistent with the deposition of an insulating (polyphenol) film on the working

149

electrode. The residual current present in these sweeps can be attributed mainly to

tunneling through the polyphenol film [3]. The measurements were taken with the same

cell used for deposition. The reduction and oxidation peaks are not symmetric about 0V

due to coating of the reference electrode.

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6

-750n

0

750n

I M (A

)

VF (V vs. Ref)

bare NH2 CHO COOH

Figure AI.3

Film thickness was determined by profilometry to be < 5 nm (the resolution of the

profilometer) to 30 nm across 15 measurements (three on each of five samples), with an

average of 15 ± 6 nm, lower than that reported previously [4]. This variation was

expected as film thickness can be tuned by the sweep rate, the extent of the forced

voltage, and the number of sweeps performed to achieve the thinner values desirable for

semiconductor sensing applications or thicker values required to prevent metal corrosion

without affecting functionalization. Further studies on ITO leads showed that

electrochemical cycling in 1X PBS increases device resistance ~3-fold independent of

whether an electropolymerization reaction occurs, suggesting that adjusting the ionic

constituents of the deposition buffer could eliminate this observed effect. The presence

150

of amines on ITO substrates electropolymerized with tyramine was quantified with an o-

phthaldialdehyde assay [5]. We found that there were 3.1 ± 0.7 free amines per nm2,

which was in good agreement with the density of amine surfaces formed by closest-

packed self-assembled monolayers in the literature [6] and on a commercially available

amine-coated slide that was used as a positive control and showed 2.7 ± 0.4 available

amines per nm2.

We first demonstrated the ability of this method to conformally coat the exposed working

electrode surface in an electrochemical cell. A PDMS gasket was placed around all the

leads to create an electrochemical cell (as depicted in Fig. 4.2). The middle lead was

used as the working electrode and its surface was selectively functionalized with amine

groups by tyramine electropolymerization as described above. The sample was then

exposed to a green, amine-reactive fluorophore (fluorescein isothiocyanate, FITC) [7]

and the fluorescence micrograph in Fig. AI.4 demonstrates that amines were selectively

introduced as a result of the electropolymerization. As a result of the electrodeposition

mechanism, beaks in the working electrode (electrical opens) will prevent film formation

beyond that point. The white arrow in Fig. AI.4 illustrates such a break, a defect in the

middle ITO lead. The extent of the PDMS gasket is shown as a blue dashed line and

functionalization is seen to be confined to within this area.

151

Figure AI.4

We then showed the ability of this method to selectively and sequentially functionalize

patterned electrodes. A brightfield image of the edge of the lead pattern on a

representative substrate (Fig. AI.5) shows three 25 μm-wide, electrically isolated and

interdigitated “C-shaped” leads that fan out to contact pads (not shown). Treatment with

a red, amine-reactive fluorophore and subsequent fluorescence imaging at this stage

(TRITC filter) showed no specific binding. As before, a PDMS gasket was placed

around all the leads to create an electrochemical cell and only one lead was used as the

working electrode (here, the innermost lead). Its surface was selectively functionalized

with amine groups by tyramine electropolymerization and the sample was then exposed

to a red, amine-reactive fluorophore. The fluorescence micrograph in Fig. AI.6

demonstrates that amines were selectively introduced as a result of the

electropolymerization. The inset plot of the fluorescence intensity—determined with

arbitrary units defined by ImageJ alone the orange dashed cutline—shows that the amines

are solely detectable on the innermost lead. Leads functionalized with amines and

subsequently quenched exhibited no specific fluorescence pattern when treated with the

same fluorophore. A subsequent tyramine electrodeposition was performed on the

middle lead and the sample was treated with the same amine-reactive fluorophore and

152

imaged; both the innermost and middle leads now fluoresce (Fig. AI.7). Visible scratches

were purposely introduced at this stage (with tweezers) to register sample identity. The

electropolymerization/fluorescence conjugation was then performed on the outermost

lead and the fluorescence micrograph in Fig. AI.7 shows all leads fluorescing, indicative

of the third selective deposition. The scratch patterns in Figs. AI.7 and AI.8 are identical.

The experiment was repeated four times with similar results. The average intensity of the

fluorescent signal across the 25-μm leads for the four experiments was 37 ± 4 over a

background of 8 ± 5. The stability of the coating did not appear to be a problem as the

fluorescence remains visible for at least six months after functionalization for samples

stored in air.


153


We also demonstrated electrodepositions on polysilicon- and chrome-on-oxide, Figs.

AI.9 and AI.10, respectively. In each case a poly-4-hydroxyphenylacetic acid film was

electrodeposited and the fluorescence micrograph was taken after subsequent treatment

with a red, carboxylic acid-reactive fluorophore. The white arrows represent the working

electrode (note there were 4 total working electrodes in Fig. AI.10, though only 2 are

highlighted) and the red arrows indicate unfunctionalized electrodes (only 2

representative unfunctionalized leads are highlighted in each figure). The scale bar in

Fig. AI.10 is important: depositions on electrodes as narrow as 1 μm, spaced as closely as

500 nm have been successfully demonstrated.

154


A carbodiimide coupling reaction was utilized to conjugate BSA to a chip functionalized

with carboxylic acid groups. In Fig. AI.11, 4-hydroxyphenylacetic acid was polymerized

to the central leads of a chip and, after BSA conjugation, the sample was incubated with

chicken anti-BSA-FITC IgG and fluorescently imaged (the inset shows a schematic of the

reactions). When the anti-BSA IgG was replaced with a nonimmune, fluorescently

labeled IgG from the same species and at the same concentration, or when BSA was not

bound on the surface prior to anti-BSA-FITC IgG incubation, no specific

immunofluorescence pattern was observed. As in Fig. 4.5, the fluorescent intensity is

localized to the functionalized lead, illustrating the conjugation of BSA to the surface and

the subsequent BSA-anti-BSA-FITC IgG binding. Surface-conjugated BSA density was

determined with a bicinchoninic acid (BCA) assay [8] to be 4.2 ± 0.6 molecules per 100

nm2 on bulk ITO substrates, which is reasonable given the ~25 nm2 footprint of the

protein.

155

Figure AI.11

In order to study the binding of DNA oligonucleotides to the electropolymerized

surfaces, a third sample was functionalized with carboxylic acid on the outermost lead

and aldehyde on the innermost lead. A 5' amine-terminated DNA 20-mer was conjugated

to the surface under similar conditions for BSA conjugation. The sample was

subsequently treated with a complementary DNA 20-mer labeled with a 5'-FAM (green

fluorescence) and fluorescently imaged (Fig. AI.12; schematic inset). Both

functionalized leads fluoresce, demonstrating DNA conjugation to each surface and

subsequent hybridization with the fluorescent DNA probe. When a noncomplementary

DNA 20-mer was used for hybridization at the same concentration or when DNA was not

immobilized on the lead surface prior to probe hybridization, no specific fluorescence

was observed.

156

Figure AI.12

Figure AI.13 shows a post-functionalized, bulk ITO sample; the polytyramine coating

(light yellow) extends only to the edge of the PDMS cell (as indicated by the blue dotted

line). A tweezer scratch (black arrow) through the functionalized area reveals the

underlying ITO (faded pink). In order to show the amine functionality of the polymer,

the chip was treated with a green, amine-reactive fluorophore and the fluorescence

micrograph is shown in Fig. AI.14 The polymer and amine regions in Figs. AI.13 and

AI.14 respectively, line up—including the tweezer scratch—demonstrating that the

polymer is responsible for the amine-functionality of the surface. A poly-4-

hydroxyphenylacetic acid deposition was performed similarly on a bulk silicon wafer

chip and the chip was subsequently treated with a red, carboxylic-reactive fluorophore,

Fig. AI.15 As in Fig. AI.14 the boundary of the PDMS cell is clearly visible and the

electrodeposited polymer is seen to confer functionality to the substrate.

157


Figure AI.15

AI.3 Reductive Electropolymerization-Based Functionalization

In studying device electrical responses to electrodepositions, we found that chrome leads

were more susceptible than their ITO counterparts to electrochemical-induced resistance

increases. This led us to question whether we could use this deposition approach to

confer functionalization to an electrically active substrate while simultaneously

eliminating the electrical activity. This would enable one to deposit a sacrificial metal

layer on a device that would be rendered insulating during the electrically-directed

158

functionalization process. We found that this could be achieved on ITO substrates using

a reductive electropolymerization; leads with resistances ~1 kΩ prior to the

electrodeposition of derivatized phenols (same molecules as in the previous section)

routinely became open circuits, with resistances > 10 GΩ. Reductive electrodepositions

have been demonstrated previously with various films, but had not been applied to phenol

electropolymerization [9-14]. A CV of the reductive electrodeposition of polytyramine

from a 0.1M NaOH-methanol solution on a patterned ITO lead is given in Fig. AI.16;

CVs of reductive electropolymerizations of poly-4-hydroxybenzaldehyde and poly-4-

hydroxyphenylacetic acid from the same buffer (Figs. AI.17 and AI.18, respectively)

were similar. The voltage was cycled versus the reference electrode oppositely to the

oxidative depositions described previously and all other parameters were nominally

identical; the deposition peak current level is similar to that in Fig. 4.3. As with the

oxidative electropolymerizations, the potential at which the oxidation occurs is strongly

dependent on (i) the working electrode material and (ii) the freshness of the reference

electrode (the peak has been seen to occur between ~1.25-2.5V on ITO).

0 1 2 3 4-60µ

-50µ

-40µ

-30µ

-20µ

-10µ

0

I M (A

)

VF (V vs. Ref)


0 1 2 3 4

-50µ

-40µ

-30µ

-20µ

-10µ

0

I M (A

)

VF (V vs. Ref)



159

0 1 2 3 4

-40µ

-30µ

-20µ

-10µ

0

I M (A

)

VF (V vs. Ref)


Figure AI.18

We again used fluorescence optical microscopy to validate surface functionalization.

Figures AI.19 and AI.20 show the ability of the reductive electrodeposition method to

specifically and sequentially confer amine functionality to ITO electrodes on a single

chip (a green, amine-reactive fluorophore was used; GFP filter). The fluorescent

micrographs (TRITC filter) in Figs. AI.21 and AI.22 show the ability of this method to

specifically deposit aldehyde and carboxylic acid moieties on ITO electrodes by

electropolymerization of 4-hydroxybenzaldehyde and 4-hydroxyphenylacetic acid,

respectively (red, aldehyde-/carboxylic acid-reactive fluorophores were used).

160



AI.4 Syntheses and Experimental Details of Terminal-Olefin Silicon

Functionalization

Synthesis of dec-9-enyl-carbamic acid tert-butyl ester. The molecule was synthesized

in two steps according to reported procedures (note this is the same molecule as 10-N-

boc-amino-dec-1-ene). Chemicals were purchased from Sigma-Aldrich. 1H NMR (500

MHz, CDCl3) δ 5.79 (1H, ddt, J = 17, 10.2, 6.7 Hz, CH), 4.98 (1H, dd, J = 17, 1.7 Hz,

CH), 4.91 (1H, dd, J = 10.2, 1.7 Hz, CH), 4.88 (1H, s, NH), 3.09 (2H, m, CH ), 2.03 (2H, 2

161

13m, CH ), 1.47-1.29 (12H, m, CH ), 1.44 (9H, s, CH ); C NMR (500 MHz, CDCl2 2 3 3)

δ 156.06, 138.98, 114.20, 78.68, 40.62, 33.80, 30.12, 29.43, 29.29, 29.06, 28.92, 28.46,

26.83.

Synthesis of 2-[2-(Undec-10-enyl)-4-(tetrahydro-2H-pyran-2-

yloxy)phenoxy]tetrahydro-H-pyran. This molecule, shown in Fig. 4.6a, was

synthesized according to the procedure in Ref. 15 from 2-[4-(tetrahydro-2H-pyran-2-

yloxy)phenoxy]tetrahydro-2H-pyran. The intermediate was synthesized as follows: To a

solution of hydroquinone (0.25 g, 2.3 mmol ) in CH Cl2 2 (3 mL) was added dihydropyran

(0.83 mL, 9.1 mmol) and pyridinium p-toluenesulfonate (0.11 g, 0.45 mmol). This

reaction mixture was stirred for 12 hours and then diluted with 10 mL of CH Cl2 2. The

mixture was washed 3 X 5 mL of NaHCO and 1 X 5 mL of brine, dried over MgSO3 4,

and concentrated to a white solid. Silica gel chromatography (4:1 hexane/ethyl acetate)

provided the di-tetrahydropyran hydroquinone as a white solid (0.48 mg, 75%). All

analytical data correspond to previously published results [15].

Bulk silicon functionalization with 2-[2-(Undec-10-enyl)-4-(tetrahydro-2H-pyran-2-

yloxy)phenoxy]tetrahydro-H-pyran. Bulk silicon chips—(111) and (100)—functionalized

with this molecule have similar static water contact angles before and after deprotection

(performed according to the procedure outlined in [15]). These data are given in Table

AI.1 and compared with the reported values from [15]. Each datapoint represents the

average (± one standard deviation) of three separate measurements on six ~1 cm × 1 cm

chips. The same chips were used for pre- and post-deprotection measurements. Silicon

162

surfaces—(111) and (100)—were also functionalized with 1-decene as a control and

static water contact angles for 10 samples were all >90º. Static water contact angles for

piranha-cleaned silicon surfaces were repeatedly <10º.

Si (111) Si (100) Pre Post Pre Post

Measured 73.6 ± 2.1º 58.3 ± 3.3º 73.7 ± 3.8º 60.9 ± 2.0º

Table AI.1

The electrochemical cell illustrated in Fig. 4.2 was used to electrochemically oxidize a

functionalized Si (111) chip; immediately after removal of the poly(dimethylsiloxane)

(PMDS) gasket the chip was treated with sulfosuccinimidyl 2-(biotinamido)-ethyl-1, 3-

dithiopropionate (sulfo-NHS-SS-biotin) in 600 mM tris[2-carboxyethyl] phosphine

(TCEP) in 1X phosphate buffered saline (PBS), following the protocol in Ref. 15. The

chip was subsequently washed and treated with a fluorescent (Texas Red) streptavidin

conjugate and the specific binding of this protein to the biotinylated surface (over the

hydroquinone surface) is illustrated in the fluorescence micrograph in Fig. AI.23. The

extent of the PDMS gasket is highlighted with a dashed blue line.

Reported [15] 73.7 ± 0.8º 54.6 ± 1.4º 74.1 ± 0.1º 61.1 ± 2.0º

163

Figure AI.23

Bulk silicon functionalization with dec-9-enyl-carbamic acid tert-butyl ester. Bulk

polished silicon surfaces were functionalized as described above for NB devices. All

wafers were purchased from Silicon Quest.

AI.5 3-Aminopropyltriethoxysilane (APTS) Surface Modification and Additional

Results

DNA Conjugation. Sulfosuccinimidyl-4-(N-maleimidomethyl)cyclohexane-1-

carboxylate (sulfo-SMCC; Pierce) was bound at pH 8.4 and subsequently reacted with a

5'-thiol ss-DNA purchased from Integrated DNA Technologies at pH 7.0. The sample

was then treated with the complementary FAM-modified (green fluorescence) strand.

The capture sequence was 5'-/ThioMC6-D/-TTT CGC CAC TGC GTC ACT GCA GG-3'

and the complementary strand was 5'-CC TGC AGT GAC GCA GTG GCG-3'.

164

In order to demonstrate successful NB functionalization, chips were treated with APTS

and the sample was subsequently treated with a heterobifunctional crosslinker that

converted the amines to maleimide groups. A 20-mer strand of thiol-terminated DNA

was bound, followed by hybridization with the complementary DNA 20-mer terminated

with a green fluorescent molecule. A fluorescent micrograph is given in Fig. AI.24

demonstrating derivatization of the entire surface rather than the NB alone.

Figure AI.24

In order to demonstrate successful surface functionalization, glass slides were patterned

with an array of numbers and a liftoff chrome metallization was performed such that the

chrome covered the entire surface except the numbers. The slide was then treated with

APTS and a wet chemical etch was performed to remove the chrome (CR-7, Transene).

Thus, the amine surface was present only on the number array, whereas the remainder of

the surface was terminated with oxide moieties. The sample was then treated with a

heterobifunctional crosslinker that converted the amines to maleimide groups and a

capture 20-mer strand of thiol-terminated DNA was bound. The complementary DNA

20-mer terminated with a green fluorescent molecule was then hydridized and the sample

was fluorescently imaged, Fig. AI.25.

165

Figure AI.25

166

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168

Appendix II: Sensing Methods

AII.1 Unfunctionalized Nanobar Sensing Methods

General sensing considerations. The initial sensor equilibration time is not shown. For

all measurements ISD was measured at 0.25 sec intervals while VSD and VGD were held

constant; V was set to -5V and VSD GD to -33V. The active region of all devices used for

sensing experiments was 10 μm in length. The solutions were titrated from 1X PBS

(phosphate buffered saline), pH 7.4, and were correct to ±0.02. Mixing was continued

after injection of the solution of interest.

Mice. All animals were routinely used at 6-8 weeks of age and were maintained under

specific pathogen free conditions and routinely checked by the Yale University Animal

Resource Center. OT-1 transgenic breeder mice were a gift from (Ruslan Medzhitov,

Yale) and 2C TCR animals were gift from (Herman Eisen, MIT). C57/BL6 (B6) mice

were obtained from Jackson Laboratories (Bar Harbor, ME). All transgenic mice were

maintained as heterozygous by breading on a B6 background in our animal facility.

Phenotypes were tested with the clonotypic 1B2 antibody (for 2C mice) and Valpha and

CD8 for OT-1.

Cells. All cells used were obtained from homogenized naive mouse spleens after

depletion of RBC by hypotonic lysis (Acros organics). Splenocytes were used without

169

further purification. For experiments involving inhibition of cellular signaling, 1 mL of 1

mg/mL genistein (Quality Biological) was added to splenocytes at 1 × 107 cells/mL

followed by incubation for 1 hr at 4°C. Cell viability was assessed with trypan blue

before and after genistein treatment.

Sensing measurements. The low-buffered solution was created by diluting 1X PBS

tenfold and adding sodium chloride to a final concentration of 150 mM. Cells were

resuspended in this solution immediately prior to sensing measurements at a

concentration of 1 × 107 cells/mL. 7 μL of this solution was initially present in the sensor

reservoir for all cellular measurements, thus ~7 × 104 total cells were present. 2 μL of

stimulant (anti-CD3 or peptide/MHC dimmer, a gift from Jonathan Schneck-Johns

Hopkins School of Medicine) was added at a concentration of 0.5 mg/mL for all cellular

measurements. Mixing was induced throughout the measurement.

AII.2 Functionalized Nanobar Sensing Methods

Functionalized Sensing. For functionalized-sensor measurements VSD was set to -2V and

V to -20V because experiments showed that VGD GD = -20V was the optimal gate voltage.

For studies involving macromolecule addition, time = 0 is defined as the onset of

protein/DNA addition. In all plots the initial sensor equilibration time is not shown.

Experiments were run for ~100 sec and mixing was continued after injection of the

solution of interest.

170

Macromolecule Sensing. All devices used for functionalized-sensing experiments were

nominally similar, with t = 40 nm and w within 50-150 nm. Each measurement was

produced by a single device; the device-to-device variation in sensor response is within

20%. For all sensing experiments, the volume of liquid in the solution chamber was ~10

μL, starting with 10 μL of buffer and displacing this with 100 μL of protein/DNA

solution, of which 10 μL remained.

Biotin-Streptavidin/Avidin Sensing. We used 0.1X PBS, pH 7.4, for all biotin sensing

experiments (unless otherwise noted); for 0.1X PBS, λD ~ 2.3 nm [1,2]. The pH 9.0 and

pH 10.5 solutions were mixed with similar salt concentrations, thus both have λD ~ 2.3

nm [1,2]. Biotinylation was performed with N-hydroxysulfosuccinimide (sulfo-NHS)-

biotin, sulfo-NHS-SS-biotin, or sulfo-NHS-LC-biotin (Pierce Chemical) at pH 10.5 (see

Appendix I). For Figs. 5.14 and 5.15, currents were normalized by dividing the measured

ISD by the pre-addition average current.

Antibody-Antigen Sensing. The capture antibodies were bound using NHS/ethylene

dicarbodiimide coupling (see Appendix I). The sensing was performed in a 1mM sodium

bicarbonate buffer, pH 8.4 (λD ~ 6.8 nm) [1,2].

DNA Sensing. Sulfosuccinimidyl-4-(N-maleimidomethyl)cyclohexane-1-carboxylate

(sulfo-SMCC; Pierce) was bound to two functionalized devices at pH 7.5 and

subsequently reacted with the 5'-thiol ss-DNA at pH 7.0 (see Appendix I). For sensing,

171

0.05X PBS was used (λD ~ 3.3 nm) [1]. DNA sequences were purchased from Integrated

DNA Technologies. The data in Fig. 5.23 was consistent with a conventional

fluorescence-microscopy-based labeled-DNA assay performed with the same surface

chemistry (see Appendix I) on glass slides, Fig. AII.1.

Figure AII.1

AII.3 Nanobar Failure Characterization Details

As described in Chap. 5, non-passivated devices were stable under active conditions (VSD

= -5V, VGD = -40V) in air, Fig. AII.2. We found the problem of device failure under

active solution-phase measurements to also exist with only deionized water (DI) present

in the reservoir, as shown for two characteristic devices in Fig. AII.3 (V = -5V, VSD GD = -

40V). This figure shows a plot of |ISD| vs. time (note in seconds) of two representative

NB devices under active sensing conditions (in DI) with VSD = -5V and VGD = -35V. A

similar initial current spike to that in Fig. AII.2 is observed but subsequent long-term

device stability is not achieved for solution-phase measurements. Nanobars such as

172

Device 1 could be successfully utilized for sensing measurements and devices in this

category survived (ie. maintained a constant ISD) under active sensing conditions for 50-

600 secs. Nanobars similar to Device 2 were unsuitable for sensing as a steady ISD was

never established. These devices failed completely after 50-2000 secs. Interestingly, a

short-lived transient state of 10-100 secs existed for most NBs immediately before

complete failure, as seen for these representative devices. As discussed in Chap. 5, after

passivation, devices were stable under active measurement conditions in the presence of

phosphate buffered saline (1X PBS), Fig. AII.4. Initial NB instability during solution-

phase measurements similar to that in Fig. AII.4 was observed for many devices, though

most eventually reached a relatively constant ISD.

0 2 4 6 8 102.0µ

2.5µ

3.0µ

3.5µ

4.0µ

4.5µ

5.0µ

5.5µ

6.0µ

|I SD (A

)|

Time (hrs)

Figure AII.2

0 500 1000 1500 2000

0

3µ

6µ

9µ

12µ

|I SD (A

)|

Time (sec)

Device 1 Device 2

Figure AII.3

173

0.0 0.2 0.4 0.6 0.8 1.01.0µ

1.5µ

2.0µ

2.5µ|I S

D (A

)|

Time (hr)

Figure AII.4

Attempts at revitalizing failed devices proved unsuccessful and optical microscopy

routinely showed that solution-induced failure changed device characteristics; Figure

AII.5 shows a characteristic device before failure, whereas Fig. AII.6 illustrates a

destroyed device. The dark red hue of the exposed active region and the leads of the

failed device are evident.

Figure AII.5 Figure AII.6

Further studies showed that this failure mode is due to a breakdown in the passivating

oxide (really the masking oxide) covering the e-beam alignment marks, as shown in Fig.

174

AII.7; the upper left mark is shown circled (white dashed line) and a total of four marks

surround the active device region. These marks are etched 3 μm deep, thus penetrating

through to the silicon handle wafer, which serves as the backgate. The 43 nm masking

oxide breaks down in the presence of solution and shorts the solution to the backgate

(held at -30 to -40V), thereby destroying the device.

Figure AII.7

AII.4 Additional Nanobar Sensing Results

An understanding of the effects of Debye screening on molecular charge is crucial for

any charge-based sensor to have practical applications. In our first attempt to

experimentally demonstrate the importance of Debye screening, the response of devices

functionalized with different biotin spacer-arm lengths to 1 nM concentrations of

streptavidin were compared. The response of three devices to 1 nM streptavidin

solutions, |ISD| vs. time, is shown in Fig. AII.8. The biotin-functionalized device, with a

1.4 nm spacer-arm, is that from Fig. 5.12 and the LC-biotin-functionalized device, with a

175

2.2 nm spacer-arm, is that from Fig. 5.13 (prior to TCEP addition). The third device was

functionalized with sulfosuccinimidyl-6(biotinamido)-6-hexanamidohexanoate (LC-LC-

biotin), which has a 3.1 nm spacer-arm length. All spacer-arm lengths yield similar

signals, most probably due either to incomplete extension (ie. bunching up) of the spacer-

arms in solution or to device-to-device electrical and functionalization variability.

-20 0 20 40 60 8050n

100n

150n

200n

250n

300n

|I SD (A

)|

Time (sec)

BiotinLC-BiotinLC-LC-Biotin

Figure AII.8

Device utility for specific ssDNA strand recognition was demonstrated last. A 20-mer,

5'-thiol ss-DNA was bound to two CAE-functionalized devices and under active

measurement conditions either the complementary (Comp) or a noncomplementary (NC)

20-mer at a 100 fM concentration was added; a plot of |ISD| vs. time is shown in Fig. AII.9

(note the vertical scale between breaks is the same). The complementary 20-mer was

added to the PEGylated NB. The sensor response to complementary strand addition

increases relative to the controls. The continued positive derivative of the signal from the

NB to which the complementary DNA was added suggests that DNA hybridization is

ongoing and the response seen in the first 45 sec is due to a smaller number of DNA

176

strands than that required to coat the entire surface. Note that this experiment was

performed prior to the solution of the nanobar device failure problem and the device

failed before complete hybridization was achieved.

-30 -20 -10 0 10 20 30 40 50

175n

200n

225n

325n

350n

375n

|I SD (A

)|

Time (sec)

Comp-DNA NC-DNA PEGylated

100n

-30 -20 -10 0 10 20 30 40 50

175n

200n

225n

325n

350n

375n

|I SD (A

)|

Time (sec)

Comp-DNA NC-DNA PEGylated

100n

Figure AII.9

Last, we hypothesized that partially screening the charge of a bound protein—by using a

buffer of intermediate ionic strength (0.1X PBS)—would enable us to use the NB to

study protein denaturation induced by solution exchange [3]. As the bound protein

unfolds, its charges are distributed farther from the sensor surface, as shown in the

schematic in Fig. AII.10 (same coloring as Figs. 5.17 and 5.21). The change in the

number of charges present beyond the Debye screening length, λD, (shown by the pink

line in Fig. AII.10) as a result of unfolding modulates the device current. Since altering

the solution’s salt concentration or pH—the traditional means of achieving protein

denaturation—affects device response independent of protein conformation, we used a

90% ethanol solution with the same ionic strength and pH as 0.1X PBS to denature the

protein [4-7]. Lysozyme was conjugated to a device [8] and a baseline current was

177

established in 0.1X PBS. After complete solution exchange with the ethanol denaturant

(beginning at time = 0), which required ~0.5 sec, the device current decreased to a stable

level in 3-4 steps, Fig. AII.11. The 90% ethanol solution contained 1% 1X PBS, thus λD

remained unchanged throughout the experiment. This decrease in |ISD| is due to the flux

of negative charge away from the sensor surface and beyond λD, which is consistent with

the denaturation of lysozyme, a negative protein with pI ~ 4.3. A control study with no

lysozyme bound showed no significant change in signal after solution exchange,

indicating that the ethanol solution affected the lysozyme rather than the device. The

stepwise fashion in which the signal intensity decreased suggests the presence of transient

intermediate conformations existing between the native and fully denatured states,

consistent with previous reports [9-11]. Additionally, the variance in step duration

suggests different transition state stabilities, as seen previously with optical methods [9-

11]. Although future work is required to fully understand these data, Fig. AII.11 shows

that NB sensors can be used as solid-state tools for studying protein folding.

178

Figure AII.10

-2 0 2 4 61n

10n

100n

1µ

|I SD (A

)|

Time (s)

-25 0 25 50 75 1001n

10n

100n

|I SD (A

)|

Time (sec)

-2 0 2 4 61n

10n

100n

1µ

|I SD (A

)|

Time (s)

-25 0 25 50 75 1001n

10n

100n

|I SD (A

)|

Time (sec)

Figure AII.11

179

References

1. Stern, E. et al. Label-free immunodetection with nanowire CMOS-compatible


2. Israelachvili, J. N. Intermolecular and Surface Forces with Applications to

Colloidal and Biological Systems. (Academic Press, New York, 1985).


1995).

4. Sasahara, K. & Katsutoshi, N. Effect of ethanol on folding of hen egg-white

lysozyme under acidic condition. Proteins: Struct. Funct. Bioinform. 63, 127-135

(2006).

5. Thomas, P. D. & Dill, D. A. Local and nonlocal interactions in global proteins

and mechanism of alcohol denaturation. Protein Sci. 2, 2050-2065 (1993).

6. Hirota, N., Mizuno, K. & Goto, Y. Group additive contributions to the alcohol-

induced α-helix formation of melittin: implication for the mechanism of the

alcohol effects on proteins. J. Mol. Biol. 275, 365-378 (1998).

7. Kamatari, Y. O., Konno, T., Kataoka, M. & Akasaka, K. The methanol-induced

transition and the expanded helical conformation in hen lysozyme. Protein Sci. 7,

681-688 (1998).



180

9. Mizuguchi, M., Arai, M., Ke, Y., Nitta, K. & Kuwajima, K. Equilibrium and

kinetics of the folding of equine lysozyme studied by circular dichroism

spectroscopy. J. Mol. Biol. 283, 265-277 (1998).

10. Zaidi, F. N., Nath, U. & Udgaonkar, J. B. Multiple intermediates and transition

states during protein unfolding. Nature Struct. Biol. 4, 1016-1024 (1007).

11. Laurents, D. V. & Baldwin, R. L. Characterization of the unfolding pathway of

hen egg white lysozyme. Biochem. 36, 1496-1504 (1997).

181

Appendix III: Nanowire-Field Effect Transistors

AIII.1 Nanowire-FET Fabrication Overview

Owing to the lack of successful schemes NW alignment on planar substrates [1-12],

electron beam (e-beam) lithography is typically the method of choice for NW-FET

fabrication because it allows a specific lead pattern to be written for each NW, assuring

the geometric definition of successful contacts [13-24]. The inability to achieve parallel

device fabrication with this method prevented us from performing statistical studies,

which are required to thoroughly characterize nanoscale materials [25], and led us to

develop an optical lithographic approach [25,26].

The NWs we used [25-29] were grown in-house by the vapor-liquid-solid (VLS)

mechanism [13,18,24,25,27,28] and were fabricated into the NW-FETs required for

sensing by transferring them from their growth substrate to an oxide-coated,

degenerately-doped silicon wafer and performing microlithographic fabrication to define

source and drain contacts to the NW. A liftoff metallization was used for contact

definition to prevent NW exposure to metal etchants. Topside backgate contacts to the

degenerate silicon wafer were also fabricated, allowing for high-throughput device

characterization in a configuration suitable for sensing [25-29].

182

The primary advantage of the e-beam contacting method is that the NW suspension can

be applied to the wafer multiple times until the NW density in the e-beam writing

window (checked with an optical or scanning electron microscope, SEM) is sufficient to

guarantee successful NW-FET fabrication. Thus, this dispersion method proved

relatively insensitive to growth yield (compared with the optical approach) because of the

potential deposition/screening iterations and because NWs lying in any orientation in the

e-beam window could be contacted. However, this method is labor intense, thereby

limiting the number of devices that can be fabricated, and pre-selection of NWs, whereby

the best NWs are fabricated into devices, is extremely difficult to avoid. A representative

4-point e-beam-defined NW-FET is shown in Fig. AIII.1 [26,29].

In contrast, the optical processing method enables parallel NW-FET fabrication across an

entire wafer and, in turn, eliminates the pre-selection inherent in the e-beam fabrication

process. However, there are two key limitations to this high-throughput method: the

NWs must be at least ~3 μm long (ideally > 5 μm) to span the leads, which are spaced 2-

3 μm due to contact lithography limitations, and the NW density must be high in order to

obtain devices since the leads cover 1.6% or 2.4% of the chip’s area for the 2 and 3 μm

patterns, respectively [25-29]. Samples with low NW yields were sometimes

successfully fabricated by applying multiple drops of the NW suspension to the wafer but

a certain density threshold was required in order to obtain devices. The NW density must

also be sufficiently low such that the majority of devices were due to an individual NW,

thus the density must be carefully chosen to lie within these boundaries. A 7-point

optically-defined NW-FET is shown in Fig. AIII.2 [25-29]. Figure AIII.2 gives a

183

photograph of a patterned 2” wafer, an optical micrograph of a typical 3.333 mm2 die,

and a field-effect scanning electron micrograph (FE-SEM) magnification of a GaN NW

contacted with seven metal leads. The black arrows denote the pads contacting the

degenerate backgate. The die is shown contacted by the 33 probetips of a Cascade

Microsystems Autoprobestation, used for automated device screening.

Figure AIII.1 Figure AIII.2

Typical characterization was achieved by backgating due to the ease of fabrication, but

topgates were defined on some samples to contrast gating efficacy. Oxide was deposited

across NW-FET samples by plasma-enhanced chemical vapor deposition (PECVD),

184

through vias were etched through the oxide to the contact pads, and topgates were

realized with an e-beam-defined liftoff metallization over NW devices between

contacting leads. The final device is pictured in the optical micrograph in Fig. AIII.3

[25].

Figure AIII.3

AIII.2 Nanowire-Field Effect Transistor Fabrication Details [25,26]

The fabrication steps for both the e-beam and optical processes are outlined in Fig.

AIII.4. Starting with a 2-inch p++ (1019 cm-3) boron-doped silicon wafer with a 200nm

thermal oxide (Silicon Quest International), vias were defined through the oxide to create

topside contacts to the backgate. Positive photoresist, Shipley S1813, was used to define

the via pattern and after exposure and development, the wafer was etched in 6:1 buffered

oxide etch (BOE) and metallized with 50 nm Al (99.999%) / 10 nm Ni (99.995%).

Liftoff was subsequently performed in acetone with sonication. The wafers were then

rapid-thermal annealed at 300°C for 30 seconds to ensure the backgate (substrate)

contacts were Ohmic.

185

Figure AIII.4

On wafers destined to be used for e-beam lithography, an additional optical lithographic

processing step was used to define leads from contact pads to an 80 μm-square e-beam

writing window, including e-beam alignment marks within this window. In order to

minimize flagging of the liftoff metallization, a resist bilayer consisting of a liftoff resist

(LOR), that develops anisotropically, and photoresist (S1813) was used (Fig. AIII.4, Step

5a). Thus when a LOR/S1813 stack was created (Fig. AIII.4, Step 6b; Fig. AIII.5), the

undercut of the LOR can be carefully controlled to create an ideal liftoff profile. A 10

nm Ti (99.995%) / 200 nm Au (99.999%) stack was evaporated and liftoff was achieved

in 60°C 1-methyl-2-pyrrilidinone (NMP) with sonication (Fig. AIII.4, Step 6a).

Although it was possible to write contact pads directly using e-beam lithography for

186

individual NW devices, it was not practical for producing large numbers of devices with

four or more contacts, required to eliminate contact resistance.

Figure AIII.5

The NWs were then transferred from their growth substrate by suspending them in

isopropanol (IPA), achieved by briefly sonicating the growth substrate in the alcohol for

10-45 seconds. The suspension was then is applied dropwise to the wafer (Fig. AIII.4,

Step 7a) and upon IPA evaporation NWs adhered to the oxide surface in a random

dispersion across the wafer. The NWs strongly adhere to the wafer: sonication and

etching are the only successful removal methods. The writing windows were canvassed

using an optical microscope (a scanning electron microscope could also be used) until the

desired number of e-beam windows contained NWs. This dispersion method was

relatively insensitive to growth yield because of the potential deposition/screening

iterations and because NWs lying in any orientation in the e-beam window could be

contacted.

187

After NW deposition, a MAA EL 13 MAA / PMMA 950 A4 bilayer was applied to the

wafer and an optical image was taken of each writing window. Alternatively, an SEM

image could be taken before resist spinning and it was found that the location of the NWs

on the wafer surface was largely unaffected by the resist spinning. Patterns were then

created to define leads to each NW device with a JEOL 6400 SEM converted to perform

direct write. The resist was exposed using typical electron doses of 350 μC/cm2, and a 1 :

3 mixture of methyl isobutyl ketone (MIBK) : IPA was used for development (Fig.

AIII.4, Step 8a). A 50 nm Ni / 300 nm Au evaporation was then performed using boiling

acetone for the liftoff (Fig. AIII.4, Step 9a).

In the optical processing method, NWs were dispersed by the technique described above

after backgate processing was completed (Fig. AIII.4, Step 5b). A subsequent optical

step was then performed to create metal contacts to the NWs that fan out to contact pads

using the LOR/photoresist bilayer described above. Photolithography was used to pattern

lines 2 or 3 microns wide spaced 2 or 3 microns apart, respectively, that run parallel for

~1 mm before fanning out to contact pads. A liftoff metallization of the contacts must be

performed because subjecting the NWs to metal etchants could be detrimental to their

properties since their stability is unknown. Furthermore, sonication cannot be used to

clean the wafers or to aid the liftoff because it may remove NWs from the wafer. Again,

a LOR/S1813 bilayer is used to create the necessary liftoff profile. A 50 nm Ni / 200 nm

Au stack was then evaporated and liftoff was performed in NMP at 60°C without

sonication, creating the contacts to the NWs (Fig. AIII.4, Step 7b). Adjacent metal leads

were electrically isolated unless linked by a NW.

188

For topgate definition (schematic Fig. AIII.6), a 200 nm-thick silicon oxide was

deposited by plasma-enhanced chemical vapor deposition (PECVD). Wafers were then

optically processed to remove the PECVD oxide overlaying the contact pads, achieved

with a BHF etch. A MAA/PMMA e-beam resist bilayer was again then deposited on the

wafer (same resist specifications as mentioned previously). Openings were defined

above leads not in contact with NWs and through vias were wet etched into the PECVD

oxide with a timed BHF etch, a step then followed by an evaporation of a 10 nm Ni / 400

nm Au stack. Alignment marks for the subsequent e-beam fabrication step were also

defined during this process step. Liftoff was performed in boiling acetone without

sonication and, upon completion, wafers were again prepared with the MAA/PMMA

stack. Topgates were then defined over NW devices between the contacting leads by e-

beam exposure; alignment was achieved using the marks defined in the previous process

step. After development, an evaporation of a 10 nm Ni / 400 nm Au metal stack was

again performed and followed by a boiling-acetone liftoff. Nickel is used as an adhesion

layer and the Au thickness is chosen to be equal to that of the metal via previously

defined to ensure metal conformality.

189

Figure AIII.6

AIII.3 Device Characterization [25-29]

All electrical measurements were performed with an HP4156B Semiconductor Parameter

Analyzer (SPA). Two-point measurements were taken by varying the voltage and

measuring current; four-point measurements were taken by sweeping a current across the

outer leads and measuring the voltage across the inner leads. Two-point measurements

were taken for the inner electrodes of the 4-point contact and resistance values are

defined as the zero-bias slope [25,27,28].

Nanowire samples processed with e-beam lithography were measured on a manual

probestation with Cascade Microtech probes; for the optical process, a Cascade

Microtech Autoprobestation was used to step die-by-die and electrically screen all

190

adjacent contact leads across the entire wafer of ~150 dies for NW crossings. An Agilent

Technologies Switchbox was used to multiplex the Cascade system for the optical

process samples. Leads with Ohmic contacts to NWs were imaged with a FE-SEM to

ensure each lead pair contacted a single NW; data from lead pairs with multiple parallel

NWs are discarded [25-28].

Device transconductance was calculated by the linear best-fit to the source-drain current

(ISD) versus gate-drain voltage (V ) dependence for constant source-drain voltage (VGD SD).

The capacitance was calculated using the measured geometrical parameters. For

consistency, all NW and nanobar (NB) mobilities are calculated in the pre-saturation

regime at VSD = 1V. Thus, we calculated mobility (μ) according to Eqn. (3.1) and used

this value to determine the carrier concentration according to [25,27,28,30]

μσe

n = , (AIII.1)

where e is the elementary charge and σ is the measured conductance.

Device simulations (Silvaco) quantitatively reproduce the characteristics from the derived

mobility, show the suppression of saturation at these mobilities/densities over the

accessible source/drain voltages, and verify saturation at lower densities.

The lengths and diameters of the NWs must be known, so this data is obtained by

scanning all leads with devices of interest with a SEM. Further, during this process all

devices that are found to consist of multiple NWs are identified and discarded. Nanowire

191

diameters were approximated to the nearest 5 nm and lengths to the nearest 0.05 μm [25-

29].

AIII.4 Metal-NW Contact Characterization [26,29]

Nanowire contacts for the GaN devices fabricated as described were found to have

resistances varying over two orders of magnitude, from ~35 kΩ to ~5.4 MΩ. Four-point

measurements that eliminate contact resistance show that this wide dispersion in

resistance values is not due to the metal-semiconductor contact. We define Ohmic

contacts as devices with the best-fit-line to the ISD(VSD) plot having a correlation

coefficient R2 > 0.99 for V = -1 to 1 V. Data from seven e-beam defined devices and

from 206 optical devices is presented in this section for GaN NWs. Electron-beam

processed NW devices were found to repeatedly produce contacts with apparent Schottky

barriers of varying heights and, consequently, linear best-fits to the 2-point ISD(VSD)

characteristics of these devices routinely yield R2 < 0.975 (Fig. AIII.7). An ISD(VSD)

characteristic of a representative device is shown in the left-hand curve in the inset plot in

Fig. AIII.7. The pre-annealed and post-475°C-annealed datapoints in Fig. AIII.7 for this

device are highlighted by arrows.

192

104 105 106 107 108 109 1010 1011 1012 1013

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

R2 o

f Lin

ear F

it

Resistance (Ω)

pre 350oC 375oC 400oC 425oC 450oC 475oC

-0.6 -0.3 0.0 0.3 0.6-40n

-20n

0

20n

40n Pre-Anneal 475oC Anneal

Voltage (V)

Cur

rent

(A)

-6µ

-3µ

0

3µ

6µ

Current (A

)

104 105 106 107 108 109 1010 1011 1012 1013

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

R2 o

f Lin

ear F

it

Resistance (Ω)


-0.6 -0.3 0.0 0.3 0.6-40n

-20n

0

20n


Voltage (V)

Cur

rent

(A)

-6µ

-3µ

0

3µ

6µ

Current (A

)

104 105 106 107 108 109 1010 1011 1012 1013

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

R2 o

f Lin

ear F

it

Resistance (Ω)


-0.6 -0.3 0.0 0.3 0.6-40n

-20n

0

20n


Voltage (V)

Cur

rent

(A)

-6µ

-3µ

0

3µ

6µ

Current (A

)

Figure AIII.7

Annealing metal-bulk GaN contacts has been shown to decrease the contact resistance

[18,23,24]; in order to study the effects of different annealing temperatures on the contact

resistance the samples were annealed on a hotplate in a N2 environment for 1 minute at

25°C increments from 350°C to 475°C. Samples were immediately transferred to a

thermal sink after each anneal and electronic measurements were subsequently taken.

The 2-point resistances and corresponding R2 values of the linear fit are shown for each

temperature in Fig. AIII.8. It is interesting to note that some devices became

significantly more resistive and nonlinear after intermediate annealing temperatures

before reaching their final low-resistance, linear states at higher annealing temperatures.

Over 50 NW devices have been fabricated by the e-beam process and ~95% have been

found to survive the post-processing annealing step.

193

104 105 106 107 108 109

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

R2 o

f Lin

ear F

it

Resistance (Ω)

No O2 Plasma O

2 Plasma

0.0 0.3 0.6 0.9 1.20

20n

40n

60n No O2 Plasma O2 Plasma

Voltage (V)

Cur

rent

(A)

0

4µ

8µ

12µ

Current (A

)

104 105 106 107 108 109

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

R2 o

f Lin

ear F

it

Resistance (Ω)

No O2 Plasma O

2 Plasma

0.0 0.3 0.6 0.9 1.20

20n

40n


Voltage (V)

Cur

rent

(A)

0

4µ

8µ

12µ

Current (A

)

104 105 106 107 108 109

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

R2 o

f Lin

ear F

it

Resistance (Ω)

No O2 Plasma O

2 Plasma

0.0 0.3 0.6 0.9 1.20

20n

40n


Voltage (V)

Cur

rent

(A)

0

4µ

8µ

12µ

Current (A

)

Figure AIII.8

Optically fabricated devices were also found to have contacts with Schottky barriers,

exemplified by the dataset of 104 devices with low R2 linear fit values in Fig. AIII.8. The

nonlinear nature of the ISD(VSD) sweeps is shown on the right-hand axis in the inset plot

for a characteristic device, denoted by an arrow. We hypothesized that resist residue

remaining on the NWs after development was responsible for the nonlinear electrical

behavior of the contacts. To eliminate this problem, a GaSonics Aura 2000 Asher was

used to perform a 20 second post-development, pre-metallization descum in an oxygen

plasma with 4 standard liters per minute O2 at 100 mTorr and 25°C. The vast majority of

the 102 devices obtained from this process and plotted here have linear ISD(VSD)

characteristics and lower resistances than the devices not subjected to the oxygen plasma,

Fig. AIII.8. A characteristic device is denoted by an arrow and the ISD(VSD) plot is shown

in the inset. We observe that the post-fabrication annealing protocol developed for e-

beam processed devices did not produce Ohmic contacts for optical devices without

194

oxygen plasma treatment and often destroyed devices. Additionally, we observe that use

of an identical oxygen plasma protocol on e-beam defined samples is ineffective (e.g.

contacts are initially Schottky and require subsequent anneals in order to be made

Ohmic).

We next sought to carefully characterize the effect of metal-NW contact resistance on the

NW device behavior. Four-terminal Kelvin probe measurements were taken by varying a

current (I ) across the outer leads while measuring the voltage (V4 4) across the inner leads.

Device resistances are defined as the zero-bias slope of the inverse of the I (V4 4)

dependence. The NW resistivity is defined conventionally as

LAR NW

NW 4=ρ , (AIII.2)

where ANW is the cross-sectional NW area and L is the source-drain NW length.

All samples measured had a linear best-fit correlation coefficient R2 > 0.995. The contact

resistance, RC, of a device is determined by subtracting the 4-point resistance from the 2-

point value from the inner electrodes of the 4-point contact. The specific contact

resistivity is then defined as

CCC AR=ρ , (AIII.3)

where AC is the area of the contact, which is assumed to be half of the total NW surface

area lying under the metal lead (reasonable for e-beam evaporated films). Representative

195

2-point and 4-point ISD(VSD) curves are shown in Fig. AIII.9 for an optically- and an e-

beam-processed device. In addition to the Ohmic nature of the contacts, it is seen that the

current levels of the 2-point and 4-point measurements are nearly identical, suggesting

low specific contact resistivities.

-0.010 -0.005 0.000 0.005 0.010-30n

-20n

-10n

0

10n

20n

30n

I SD (A

)

VSD (V)

Sample 1 2-Point 4-Point


-0.010 -0.005 0.000 0.005 0.010-30n

-20n

-10n

0

10n

20n

30n

I SD (A

)

VSD (V)



Figure AIII.9

The measured specific contact resistivity of 32 optical and 6 e-beam devices are plotted

versus NW resistivity in Fig. AIII.10. The linear best-fit line indicates the same

functional dependence ρ (ρC NW), independent of processing method (the average

higher ρNW values observed for e-beam fabricated devices are due to run-to-run growth

variations). The NW specific contact resistivity is also comparable to that of an

unannealed contact to bulk n-GaN, which for ρ ~ 0.027 Ω-cm (from Ref. 24 with 1.5 ×

1019 cm-3 and using the same carrier density-resistivity relation as for NW samples) has

ρ -4C = 8.2 x 10 Ω-cm2, and is plotted in Fig. AIII.10. This work shows that metal

contacts to degenerate semiconducting NWs are comparable to bulk material.

196

0.01 0.1 1

10-5

10-4

10-3

ρ C (Ω

-cm

2 )

ρNW (Ω-cm)

Optical E-Beam Bulk Data

Sample 1Sample 2

Slope = 1.03 ± 0.13R2 = 0.66

0.01 0.1 1

10-5

10-4

10-3

ρ C (Ω

-cm

2 )

ρNW (Ω-cm)


Sample 1Sample 2

Slope = 1.03 ± 0.13R2 = 0.66

0.01 0.1 1

10-5

10-4

10-3

ρ C (Ω

-cm

2 )

ρNW (Ω-cm)


Sample 1Sample 2

Slope = 1.03 ± 0.13R2 = 0.66

Figure AIII.10

AIII.5 GaN NW-FET Characterization and Optimization [25]

The ISD(VSD) device characteristic for varying VGD for a ~10 nm-diameter GaN NW-FET

is shown in Fig. AIII.11. This is one of the few devices—14 out of 1096—that exhibited

full pinchoff. The inset plot shows the ISD(V ) for constant VGD SD = 1V (which yields a

mobility of 9.49 cm2/V·s and a carrier density of 1.62 × 1020 cm-3). The ISD(VSD) plot

shows the Ohmic nature of the contacts as well as the fact that saturation is not reached,

due to the high carrier densities of these NWs. Four-point ISD(VSD) measurements were

performed to show that the observed transconductance is due to channel conductivity

modulation and is not a contact effect. Figure AIII.12 shows results comparing 2-point

and 4-point carrier modulation for a representative device. There is little difference

197

between the 2- and 4-point channel currents, eliminating the parasitic effects in the

contact region for these devices.

-1.0 -0.5 0.0 0.5 1.0-2.0x10-6

-1.5x10-6

-1.0x10-6

-5.0x10-7

0.0

5.0x10-7

1.0x10-6

1.5x10-6

2.0x10-6

I SD (A

)

VSD (V)

VG=40 VG=30 VG=20 VG=10 VG=0 VG=-10 VG=-20 VG=-30 VG=-40

-40 -20 0 20 40

0.0

3.0x10-7

6.0x10-7

9.0x10-7

1.2x10-6

1.5x10-6

1.8x10-6

VGD (V, VSD = 1V)

I SD

(A)

VG=40

VG=-40

-1.0 -0.5 0.0 0.5 1.0-2.0x10-6

-1.5x10-6

-1.0x10-6

-5.0x10-7

0.0

5.0x10-7

1.0x10-6

1.5x10-6

2.0x10-6

I SD (A

)

VSD (V)

VG=40 VG=30 VG=20 VG=10 VG=0 VG=-10 VG=-20 VG=-30 VG=-40

-40 -20 0 20 40

0.0

3.0x10-7

6.0x10-7

9.0x10-7

1.2x10-6

1.5x10-6

1.8x10-6

VGD (V, VSD = 1V)

I SD

(A)

VG=40

VG=-40

Figure AIII.11

-20 -10 0 10 20

-5.8µ

-5.6µ

-5.4µ

-5.2µ

-5.0µ

-4.8µ

I SD (A

)

VGD (V; VSD = 1V)

2-point 4-point

Figure AIII.12

Devices sometimes exhibit a small hysteresis in ISD(V ) sweeps (with constant VGD SD) for

gate voltages > |10 V|, the voltage range used in the transconductance determination. For

198

223 devices, the percent error between transconductance values calculated from sweeps

in opposite directions is 5.92 ± 0.29 % (± 1 σM, standard error of the mean). Thus, the

total error reported for mobility and carrier concentration is the geometric mean of the

error of the measurement error and the maximum due to potential hysteresis, 6.22%. In

practice this turns out to be largely insignificant with respect to the other sources of error.

Since the backgated geometry is essential for the high throughput characterization

required for NW material optimization, the use of a backgate in place of a traditional

topgate was validated by employing e-beam lithography to define a topgate over an

optically contacted NW. Sweeps of ISD(VSD) with VGD varied from -40 to 40V in 10V

steps are shown in Fig. AIII.13 for the device pictured in Fig. AIII.3 for both the topgate

and the backgate. As expected, the current level of the device when topgated is slightly

higher, due to the narrower gate. Figure AIII.14 shows the I (V ) plots at VSD GD SD = 1V for

both gates, illustrating no appreciable difference in transconductance.

0.0 0.2 0.4 0.6 0.8 1.0

0.0

10.0µ

20.0µ

30.0µ

40.0µ

50.0µ

60.0µ

I SD (A

)

VSD (V)

Backgate Topgate

-40 -20 0 20 40

54.0µ

56.0µ

58.0µ

60.0µ

62.0µ

I SD (A

)

VGD (V; VSD = 1V)

Backgate Topgate


199

To verify that a statistically significant comparison can be performed to compare material

synthesis parameters, we examine the fluctuations of intra-growth run electrical

characteristics and compare the electrical properties of NWs from two different

fabrication runs with nominally identical growth parameters. The distribution of NW

diameters for devices from a single growth, Growth A, is shown in Fig. AIII.15; the mean

diameter is 94.4 ± 3.5 (1 σM) nm. For Growth A, the NWs were grown at 900ºC at 760

Torr from a mixture of Ga and Ga O [31] with a 100 sccm NH2 3 3 flow rate on an alumina

source coated with nickel. Figures AIII.16 and AIII.17 are plots of carrier concentration

[mean log n is 20.36 ± 0.03 (1 σM) cm-3] and mobility [mean mobility is 3.54 ± 0.28 (1

σM) cm2 ***/V·s] versus diameter for NW samples; neither has a significant diameter

dependence: for carrier density the coefficient of determination R2 = 0.20, and for

mobility R2 = 6.2 × 10-4. Since the dispersion in device characteristics can both be

interdevice and intradevice, a sampling of devices that had both a backgate and multiple

(>5) contacts were examined. Nanowire resistances derived from 4-point measurements

exhibit a 3.5% mean variation, and a 5.1% mean variation exists for mobilities and carrier

concentrations between different leads contacting the same wire (Table AIII.1). Thus,

interdevice fluctuations dominate over intradevice variances. Reported values of

mobility and carrier concentration do not include this error (by geometric mean of the

errors) since the sample size of multiple-point devices is sparse; however, the correction

is insignificant.

*** Hereafter, mobility, carrier concentration, and diameter errors are reported as σM unless otherwise noted.

200

0 50 100 150 2000

5

10

15

20N

umbe

r of D

evic

es

Diameter (nm)0 20 40 60 80 100 120 140 160 180 200

19.5

20.0

20.5

21.0

Log

n (c

m-3)

Diameter (nm)


0 20 40 60 80 100 120 140 160 180 200

0

2

4

6

8

10

Mob

ility

(cm

2 /Vs)

Diameter (nm)

Figure AIII.17

Lead Pair Device 1 Device 2 Device 3 Device 4 Device 5 A 70320Ω 889846Ω 40783Ω 289733Ω 32164Ω B 70849Ω 873489Ω 42089Ω 294654Ω 33481Ω C NA NA 40142 272228Ω 33051Ω D NA NA NA NA 31034Ω E NA NA NA NA 31744Ω

(%)/ RRΔ 0.75 1.86 3.97 4.79 3.46 Table AIII.1

A second sample was grown under nominally identical conditions (Growth B), with the

following comparison: mean mobility for A is 3.54 ± 0.28 cm2/V·s and for B is 2.96 ±

0.36 cm2/V·s. The mean log carrier concentration for A is 20.36 ± 0.03 cm-3 and that for

201

-3B is 20.43 ± 0.05 cm . A plot of mobility versus the log of the carrier concentration for

both samples A and B is shown in Fig. AIII.18. Population means (triangle) ± 1σΜ

(brackets) are shown at the periphery of the plot. Brackets are not observable when the ±

1σΜ range is less than the width of the data point (triangle) signifying the mean. A T-test

is performed to compare the sample populations and to assess the significance of

population isolation. At the 95% confidence level (CL), neither the mobility nor the

carrier concentration is statistically different. Thus, populations with nominally identical

growth conditions yield statistically identical mobilities and carrier densities. These

results were consistent with previous studies performed with similarly grown GaN NWs,

which were also degenerately doped [32].

19.5 20.0 20.5 21.0

0

2

4

6

8

10

12

Mob

ility

(cm

2 /Vs)

Log n (cm-3)

Growth A Growth B

19.5 20.0 20.5 21.0

0

2

4

6

8

10

12

Mob

ility

(cm

2 /Vs)

Log n (cm-3)

Growth A Growth B

Figure AIII.18

In an attempt to determine the source of the degenerate n-type NW doping—due either to

oxygen vacancies or nitrogen impurities—a systematic study of the effect of each growth

parameter on the mobility and carrier concentration of the NWs was performed. We first

found that use of a silicon substrate (rather than the alumina used in Growths A and B)

202

yielded significantly lower NW diameters and carrier concentrations and significantly

higher mobilities at the 99% CL. We then determined that changes in the NH3 flow rate

in the 50-150 sccm range had no significant effects on NW material properties. Next, we

found that including Ga O2 3 with elemental Ga as the gallium source (used to increase the

gallium vapor pressure to improve NW yield [31]) did not significantly affect the

resulting NW material properties. Additionally, data showed that a decrease in growth

pressure to 300 Torr had no affect on NW material properties, though an increase in

growth temperature to 1100ºC decreased the carrier concentration and increased the

diameter at the 99.9% CL (mobilities increased at the 95% CL). Changing the metal

catalyst to Fe [14] yielded NWs with significantly increased mobilities (99% CL) and

decreased carrier concentrations (99.9% CL). The potential incorporation of oxygen as a

dopant via the presence of Ga O2 3 was also investigated with NWs grown with Fe

catalysts and as was the case with Ni, no significant difference in carrier density was

observed.

Since free oxygen was not being incorporated as a dopant, a test for nitrogen vacancies as

the dopant was devised. Previously it was observed there was no significant dependence

on the ammonia flow during growth, indicating that little could be done to affect nitrogen

incorporation during growth. This led us to select a post-growth, pre-fabrication anneal

of the NWs in (atomic) nitrogen, which was calculated (using bulk parameters) to have

sufficient diffusivity to potentially fill these vacancies. Nanowires from the same growth

were annealed at 900°C in either forming gas (4% H in N2 2) or ammonia, and compared

to a sample grown with nominally identical conditions with no anneal, Fig. AIII.19. The

203

forming gas anneal does not produce atomic nitrogen and, in turn, should have a minimal

effect on NW quality, while nitrogen produced by the ammonia cracking during this

anneal should decrease the carrier concentration. At the 99.9% CL the ammonia anneal

decreases the carrier concentration while the forming gas anneal does not produce a

significantly different carrier concentration at the 95% CL. Thus, nitrogen vacancies are

found to be the dominant as-grown n-type intrinsic dopant in these NWs.

19.0 19.5 20.0 20.5 21.0-5

0

5

10

15

20

25

30

35

40

Mob

ility

(cm

2 /Vs)

Log n (cm-3)

Growth A Growth C

19.0 19.5 20.0 20.5 21.0-5

0

5

10

15

20

25

30

35

40

Mob

ility

(cm

2 /Vs)

Log n (cm-3)

Growth A Growth C

Figure AIII.19

Combining the results of the above studies, one can optimize material parameters to

obtain higher mobility and lower carrier concentration. For Growth C, Si was chosen as

the substrate and Fe as the catalyst, the ammonia flux was set at 2 sccm, a high

temperature — 950°C — and atmospheric pressure were used, and Ga and Ga2O3 were

used (to increase yield [31]). The resulting NWs were then annealed in NH3 for 4 hours

at 900°C. The average mobility for this sample is 9.12 ± 1.56 cm2/V·s and the mean log

carrier density is 19.39 ± 0.05 cm-3. A comparison of this growth to the original growth

conditions (Growth A), shows a stark contrast in both mobility and carrier concentration,

204

seen in Figure AIII.20. These NWs show significant improvement in transport properties

compared with the non-optimized growth parameters commonly found in the literature

[33] for GaN CVD NWs; however, their transport properties are significantly lower than

those reported for LA-CVD-grown GaN NWs [14].

19.0 19.2 19.4 19.6 19.8 20.0 20.2 20.4 20.60

2

4

6

8

10

12

14

Mob

ility

(cm

2 /Vs)

Log n (cm-3)

No Anneal NH3 Anneal Forming Anneal

19.0 19.2 19.4 19.6 19.8 20.0 20.2 20.4 20.60

2

4

6

8

10

12

14

Mob

ility

(cm

2 /Vs)

Log n (cm-3)

No Anneal NH3 Anneal Forming Anneal

Figure AIII.20

AIII.6 In O NW Growth Method Comparison [28] 2 3

These findings led us to investigate the effect of different growth systems on NW

transport properties. We used In O2 3 NWs synthesized either by LA-CVD or CVD alone

with nominally identical growth conditions. Nanowires were fabricated by LA-CVD at

770°C (LA-CVD #1) because this growth temperature had previously been reported to be

optimal [34]. However, we found that NW yield for CVD-grown samples is strongly

temperature-dependent and growths at 770°C (CVD #1) produced very few NWs and

thus few electronic devices could be fabricated. At 850°C a high yield of NWs was

205

obtained for both methods (LA-CVD #2 and CVD #2), which allowed for a statistically

significant direct comparison.

OThe n-type semiconducting behavior of representative In2 3 NW devices from LA-CVD

#2 and CVD #2 is evident in the ISD(VSD) for varying VGD dependencies, Figs. AIII.21 and

AIII.22, respectively. The FE-SEMs of the devices and the ISD(V ) at VGD SD = 1V plots

are inset in each panel. The linearity of the ISD(VSD) curve is indicative of Ohmic metal-

semiconductor contacts. Although no Kelvin probe (4-point) measurements could be

made on a single NW due to insufficient NW lengths, the linear nature of the ISD(VSD)

curves was preserved to 4K for all devices measured at variable temperature, consistent

with negligible contact resistivities. The ISD(VSD) and ISD(VGD) dependencies in Fig.

AIII.21 is similar to those previously reported [34,35], with an on/off ratio of ~104. In

comparison, the on/off ratio of the CVD device is ~103, suggestive of a lower mobility.

-1.0 -0.5 0.0 0.5 1.0-800n

-600n

-400n

-200n

0

200n

400n

600n

800n

I SD (A

)

VSD (V)

VG (V) = 40 30 20 10 0

-40 -20 0 20 400

200n

400n

600n

I SD (A

)

VG (V; VSD = 1V)

-1.0 -0.5 0.0 0.5 1.0-800n

-600n

-400n

-200n

0

200n

400n

600n

800n

I SD (A

)

VSD (V)

VG (V) = 40 30 20 10 0

-40 -20 0 20 400

200n

400n

600n

I SD (A

)

VG (V; VSD = 1V)

-1.0 -0.5 0.0 0.5 1.0

-9µ

-6µ

-3µ

0

3µ

6µ

9µ

I SD (A

)

VSD (V)

VG (V) = 40 30 20 10 0

-40 -20 0 20 40

0

2µ

4µ

6µ

8µ

I SD (A

)

VG (V; VSD = 1V)

-1.0 -0.5 0.0 0.5 1.0

-9µ

-6µ

-3µ

0

3µ

6µ

9µ

I SD (A

)

VSD (V)

VG (V) = 40 30 20 10 0

-40 -20 0 20 40

0

2µ

4µ

6µ

8µ

I SD (A

)

VG (V; VSD = 1V)


206

The mobilities and carrier concentrations were calculated for 50 LA-CVD #1 devices, 38

LA-CVD #2 devices, four CVD #1 devices, and 47 CVD #2 devices. Mobility versus

carrier concentration plots for growths #1 and #2 are given in Figs. AIII.23 and AIII.24,

respectively. For growth #1, the mobilities of the LA-CVD NWs vary from 30.9 to 359.3

cm2/V·s, while those of CVD NWs lie between 2.6 and 42.6 cm2/V·s. For growth #2, the

mobilities of the LA-CVD NWs vary from 1.6 to 188.0 cm2/V·s, while those of the CVD

NWs lie between 0.1 and 45.8 cm2/V·s. It is seen that higher growth temperatures reduce

NW mobility but have little appreciable affect on carrier concentration.

1016 1017 1018 1019

10

100

Mob

ility

(cm

2 /Vs)

Carrier Concentration (cm3)

LA-CVD #1 CVD #1

1016 1017 1018 1019

10

100

Mob

ility

(cm

2 /Vs)


LA-CVD #1 CVD #1

1018 1019 1020

0.1

1

10

100

Mob

ility

(cm

2 /Vs)


LA-CVD #2 CVD #2

1018 1019 1020

0.1

1

10

100

Mob

ility

(cm

2 /Vs)


LA-CVD #2 CVD #2


This work showed that LA-CVD In2O3 NWs did indeed have significantly higher

mobilities than their CVD counterparts. Since there is no appreciable change in yield

with decreasing growth temperature for LA-CVD-fabricated NWs, whereas NW yield

decreases dramatically with unassisted CVD, LA-CVD can access growth regimes for

higher mobility material than unassisted CVD.

207

AIII.7 Nanowire-Field Effect Transistor Sensing

For sensing measurements, a hole was cut in the center of a ~2.75 mm x ~2.75 mm x ~1

mm poly(dimethylsiloxane) (PDMS; Dow Corning) membrane to create a fluid cell

above a single die [36-39], optical micrograph Fig. AIII.25. A micropositioner was used

to place one end of thin-walled tubing above this cell to serve as the input; the other end

was attached to a syringe. During solution exchange, a Kimwipe was held above the cell

to wick away excess solution. The cell held ~5 μL and 500 μL of new solution was

flushed during solution exchange. Solutions of pH 6.0 and 8.0, each titrated from 1X

phosphate buffered saline PBS, were used. Measurements were run for 120 sec; VSD was

sourced and ISD was measured at 0.25 sec intervals with VGD held constant: 0V for the

GaN sample and 10V for both In O2 3 devices. In Figs. AIII.26-AIII.28 the initial

equilibration time is not shown and time = 0 is defined as the onset of solution exchange.

Figure AIII.25

208

Unfunctionalized NW-FETs can be used as pH sensors due to their native surface oxide

coating. The response of a GaN NW-FET device [25] with a mobility of 16.1 cm2/V-s

and a carrier concentration of 3.31 x 1019 cm-3 to a change in pH from 8.0 to 6.0 is shown

in Fig. AIII.26. As would be expected for a n-type device, the source-drain current

increases with decreasing pH due to the presence of more protons, which bind the free

surface Si-O- groups, in turn increasing the effective gate potential. The sensitivity of

this device, defined as the source-drain current (ISD) ratio at pH 6.0 to pH 8.0 is 1.01. The

response of a CVD-grown In2O3 NW-FET [28] sensor with a mobility of 40.6 cm2/V-s

and a carrier concentration of 8.23 x 1018 cm-3 to a change in pH from 8.0 to 6.0 is shown

in Fig. AIII.27. Again, the proper n-type behavior is observed and the sensitivity of this

device is 1.52. The response of a LA-CVD-grown In O NW-FET device [28,34,352 3 ]

with a mobility of 117.0 cm2 18/V-s and a carrier concentration of 4.64 x 10 cm-3 to a

change in pH from 6.0 to 8.0 is shown in Fig. AIII.28. The proper n-type behavior is

evident and the sensitivity of the device is 2.62. As expected due to the relative device

characteristics, the LA-CVD-fabricated In2O3 NW is the most sensitive, followed by the

CVD-grown In2O NW, and last the GaN NW. 3

-40 -20 0 20 40 60 80

18.75µ

19.00µ

19.25µ

I SD (A

)

Time (sec)-40 -20 0 20 40 60

3.0µ

3.5µ

4.0µ

4.5µ

5.0µ

5.5µ

I SD (A

)

Time (sec)


209

-20 0 20 40 60 80

400.0n

600.0n

800.0n

1.0µ

1.2µI S

D (A

)

Time (sec)

Figure AIII.28

These data demonstrate the critical impact of semiconducting NW device and material

properties on sensitivity and the relatively poor results from the GaN and CVD-In O2 3

NW-FETs led us to use the NBs for all other sensing measurements (note the LA-CVD

In2O3 NWs were obtained through a collaboration with Prof. Chongwu Zhou and had

already been well characterized as sensors [40-42]).

References

1. Huang, Y., Duan, X., Wei, Q. & Lieber, C. M. Directed assembly of one-

dimensional nanostructures into functional networks. Science 291, 630-633

(2001).

2. Ahn, J.-H. et al. Heterogeneous three-dimensional electronics by use of printed

semiconductor nanomaterials. Science 314, 1754-1757 (2006).

3. Whang, D., Jin, S., Wu, Y. & Lieber, C. M. Large-scale hierarchical organization

of nanowire arrays for integrated nanosystems. Nano Lett. 3, 1255-1259 (2003).

210

4. Englander, O., Christensen, D., Kim, J., Lin, L. & Morris, S. J. S. Electric-field

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Label-free sensing with semiconducting nanowires · Label-free sensing with semiconducting nanowires ... Label-free sensing with semiconducting nanowires ... experiment has been performed