Biosensors for Pathogen

DetectionAggiE Challenge Fall 2015

Dr. Kameoka

Jaskirat Batra

Agenda• Introduction

–Project Overview

–Group Responsibilities

•Group Progress

– Fabrication Team

– Optics Team

– Software Team

Project Overview• Objectives

– Create a microcantilever able to produce a measurable cantilever

deflection

– Initiate a clear image using a smart-phone

– Develop detection software from pictures from a smart-phone

• Requirements

– Affordable

– User-friendly

– Highly Sensitive

Group Assignments• Fabrication

– Create a polymer-based platform that can support the identification of a

biological sample in order to produce a deflection

• Optics

– Design the most sensitive optical configuration possible for a smart-

phone platform

• Software

– Develop a program to measure the deflection of the cantilever from the

smart-phone image

Fabrication Team

Meredith Davies [BMEN]

Rebecca Valencia [ECEN]

Last Semester’s Progress• Mold updates and parameterized files

• Fabricating cantilevers without silane coating

• Dyeing cantilevers to improve contrast

• Platform design

Overview• Fabrication process

• Sudan IV

• Finding the Young’s modulus

• Other Experiments of PDMS Properties

Fabrication Process

Soft Mold Fabrication Process1. Mix PDMS

2. Pour PDMS into hard mold

3. Cure at least 2 hrs @ 65C

4. Remove soft mold from hard mold

5. Cure soft mold only for at least 48 hrs @

125C

• They need to be remade every few

months for easier cantilever extraction

• Cantilevers were static and responsive to

our gloves and petridish

• Dipping in water usually helped but added

lint from paper towels

Example of soft mold with failed cantilevers

Cantilever Fabrication ProcessTwo-Tone Cantilever

1. Mix dye with PDMS

2. Pour PDMS into block

3. Cure 30 min @ 65° (or Cure 3~4 min @ 110°C)

4. Pour additional PDMS (may be different color) into cantilever channels

5. Use razor to smooth and rid excess PDMS

6. Cure at least 2 hours @ 65°C

7. Remove cantilever

Example of two colored cantilever with very

flexible cantilevers

Hard Molds

0.2 mm thickness

0.4 mm thickness

4 mm long8 mm long4, 6, 8 mm long

Clear Cantilever Problems

8mm 6mm 4mm

Modified Cantilevers: 4 mm long0.2 mm thick cantilevers

0.4 mm thick cantilevers

0.2 mm thick cantilevers

0.4 mm thick cantilevers

Concentration: 0.3 mL dye / 10 g PDMS

Sudan IV

Sudan IV Interest• Properties of PDMS

• Bleed less (on hands, into water)

• Better contrast image for processing

Sudan IV Solution

Instructions from Flinn Scientific

1. 37.5 mL of ethyl alcohol

2. Heated

3. Added 0.25 g of Sudan IV powder

4. Shake with vortex mixture

5. Add 12.5 mL of DI water0.3 mL Sudan/10 g PDMS

Sample created

Sudan IV• Cured at 65°C for 2 hours

– Samples reacted to heat

• Cured at room temperature for 48

hours

Finding the Young’s Modulus

Tensile SamplesThe gage length was pre measured and

marked on the sample and then inserted into

the headers

ASTM D412: Extension Rate is 500 mm/min

Used 12.7 mm/min for majority of the tests

Using increased extension rate (50 mm/min)

did not change the young’s modulus

In the process of being stretched

Clear PDMSSudan Dye

Food Dye

Food Dye Concentrations

No Dye 0.77 MPa

0.1 mL/10 g 0.39 MPa

0.3 mL/10 g 0.38 MPa

0.5 mL/10 g Not Found

• Young’s modulus did not appear to

change at different dye concentrations

• Higher concentrations are harder to

remove

Other Experiments of PDMS

Properties

Food Dye Water Soluble PropertyGoal

Test how much dye in the PDMS is

leaking

Experiment

Placed samples in water for 24 hrs and

then in the oven (65C) for 24 hrs repeatedly

Alternated environment for 6 days

Recorded the mass

Findings

Observed that the dyed PDMS leaked dye

into the water every time it was introduced

into fresh water

The change in mass was not found to be

statistically significant in relation to the

scale’s accuracy

Heat Strain

Heat Strain• Test if changing the temperature is changing the diffusion

rate of dye out of PDMS

• Control: Plain PDMS in green dye

• Experiment: Heating samples of clear PDMS then adding

into dye alternating for 6 days

Heat Strain Results• 6 days alternated heat/dye

• Tears on the surface

• Some green dye on outside

Food Dye vs SudanFood Dye

Cured at higher temperatures, faster cure

time

Water soluble, dye leaks out of PDMS

Contains corn syrup, at higher concentrations

the PDMS is sticky

Sudan IV

Larger Young’s modulus, less flexible

Class 3 carcinogen

Mutagenic for mammalian somatic cells

Next Semester’s Steps• Sudan IV tensile test

• Sudan IV in water

• Indicate the best dye option

• Fabricate successful cantilevers for imaging

• Modify detection platform as needed

Questions?

Optics Team

Nirmal Patel [ECEN]

Joe Slagel [ISEN]

Calvin Theriot [ECEN]

Images Without Optics

• Limited to 5x with Digital Zoom

• Very Lossy - High Noise

• Impractical Focal Length

• Low Reproducibility

Unutilized Pixels

Goals

• Review optics principles

• Find multiple potential lens which would

provide a high-resolution picture.

• Select the best lens among all potentials.

Preliminary

Before any research could be done, it was

important for us to review the following optics

principles. Reflection and Refraction• Images

• Mirrors

• Snell’s Law

• Lenses

Finding the right lens3 lenses were chosen:

a) Neewer 60X Zoom LED Clip-On Microscope Magnifier

Micro Lens with Universal Clamp.

b) TECHNO Universal Professional HD Camera Lens Kit

(12.5X Super Macro was used).

c) Also a lens provided by Dr. Kameoka “Gakken Suteifuru

Microscope” was considered.

Option A: Neewer 60X Zoom LED Clip-On Microscope Magnifier Micro

Lens with Universal Clamp.

● Advantages:

○ Very large zoom.

○ LED light attachment.

● Disadvantages:

○ Large amount of fish-eye.

○ Inability to take picture without

touching object.

○ Poor holder design. Testing the Neewer lens

using currency

Kit contained 3 lens: In our research project the 12.5X

Super Macro Lens was used

12.5X Super Macro Lens details:

• 12.5X zoom

• focal length = 23.54 mm

• d = 10 mm

• f/2.354

Source: Amazon.com

Option B: TECHNO Universal Professional HD Camera Lens Kit (12.5X

Super Macro was used)

Results: Galaxy S6 Stock Lens

• Taken using Galaxy S6

stock lens and 5X digital

zoom

• f/1.9

• Significant amount of

noise

• Distance of image: ~3.11”

but could vary.

Demonstration

of Clarity

Results: Galaxy S6 stock lens + 12.5X lens

• Taken using a Samsung

Galaxy s6 (no digital zoom)

and added 12.5X Super

Macro lens

• f/2.354

• Reduced noise

• distance of image = 0.75”

Demonstration

of Clarity

• Image taken with lens

• Less noise

• Long depth of field

● Picture without lens

● Significantly more

noise

● Shallow depth of field

Gakken Microscope

• Three optical powers

• 2x, 4x, 16x

• Easy integration with

existing systems

• Measurements taken

with 8 MP sensor

(image is 66% of a 16

MP image in y-axis)

Note: The Light Source is not included in this kit.

Phone Platform

Adjustment Wheel

Lens Housing

Stage

Light Source

Technical SpecificationsLens 2x 4x 16x

Focal Length 2.778 cm 1.27 cm 0.1588 cm

f/number* 2.692 1.455 0.333

Numerical

Aperture0.82 0.485 0.0378

Depth of Field 0.515 cm 0.23 cm 0.25 cm

Minimum

Theoretical

Detection**

58.8 µm 25 µm 5.2 µm

* The f/number without a lens is 2.4

**The minimum theoretical detection without a lens is 210 µm

MethodologyIn order to find minimum theoretical detection:

1. Measure Pixel Height

2. Measure Pixel Buffer

3. Measure Real Height

4. Calculate Buffer Height

2x Lens

No Magnification 2x External Magnification

4x Lens

4x External MagnificationNo Magnification

16x Lens

No Magnification 16x External Magnification

Miscellaneous

2x Magnification + Digital Zoom

Dark Cantilever with No Deflection

2x Magnification + Digital Zoom

0.2mm Cantilever with Deflection

Decision MatrixLenses Clarity No

DistortionNo

Background Noise

Ease of Use

Detail No Fisheye

Focus Practicality Deflection Picture Area

Total

Gakken Lens

System 2x

8 6 6 9 6 7 8 7 8 9 74

Gakken Lens

System 4x

8 4 7 9 8 6 6 5 7 7 67

Gakken Lens

System 16x

8 1 9 9 9 8 4 1 7 4 60

Macro Lens

7 8 7 4 4 8 7 3 5 10 63

60x Lens 5 1 1 2 4 2 3 1 3 1 23

No Lens 2 3 2 9 2 10 6 3 4 10 51

Conclusion• 2X and 4X Gakken lens ranked highest

according to decision matrix.

• <10X lens with focal length ~1cm gives highest

precision.

• 16x Gakken Lens and 60X Neewer lens

disqualified due to practicality

Future Goals• Reproduce high resolution pictures of cantilevers.

• Research and recommend low-distortion lens.

–Preferably 16x

• Improve phone holder design.

Software Team

Lucas Cheung [ECEN]

Charlie Zhang [ECEN]

Stefan Manoharan [ECEN]

Last Semester’s Work

• Edge Detection Software–Greyscale

–Binary

–Edge Detection

– Invert Edge Detection

–Tabulate in Matrix

– Invert Matrix

–Shift

Pros

• Provides very good basis for further code

• Show a rough edge to measure

displacement

Cons• Not applicable for different types and angles

• Image provided did not show any displacement

• Small amount of noise

New Considerations

• New Images–Colored Cantilevers

–Lens

–Lighting

–New Angle

Goals

• Make code applicable to multiple situations

• Remove as much noise as possible– Image

–Matrix

Displacement Test• If able to detect rough displacement, then able

to calculate displacement - pixel scale

• Crop area of interest to reduce excess

information

• Different edge detection method

Crop Results• 1mm Cantilever

– ~5 pixel displacement

Crop Results (cont.)• 0.6mm cantilever

– ~20 pixel displacement

Threshold OptimizationProgramming Team

Overview of Fixes by Mid-Term

• Binary Detection Mechanism is more

calibrated (Used background as threshold

source)

• Edge Detection Source was changed from

Binary to Greyscale

• Better Edge Detection Algorithm was

proposed (Roberts)

Where We Left Off

Problem

Definition of ‘Salt and Pepper’, anyone?

• The salt and pepper in the image looks ugly.

• Edge detection algorithms were ineffective with this

much noise.

• Without a clear edge, image can’t be used

Possible Reasons• Threshold,

though better,

was not good

enough.

• Too much noise

in peripheral of

cantilever

Possible Reasons

• Slight changes in light intensity and color

in a greyscale image would be interpreted

as an edge according to the algorithm.

Solution

• We reintegrated binary to the process (better contrast

between two sides of an edge)

• Manual crop function was added to get rid of extraneous

peripherals.

• Threshold Selection: Three possible areas to look out for

thresholds

The New Cantilever Image

Threshold Selection Areas

• Inside the colored Cantilever tip

Threshold Selection Areas

• Containing the Cantilever-Background Edge

Threshold Selection Areas-

Background of Cantilever!

• Background was the most interesting

selection to play around with

• We found out that the amount and position of

salt and pepper depended on the dimensions

and position of threshold rectangle.

Threshold Selection- Background

• Selecting a ‘fat’ rectangle

Threshold Selection- Background

• Selecting a ‘vertical’ rectangle

Threshold Selection- Background• Selecting a Horizontal Image

• Found that Thinner rectangle is better (thinner salt and

pepper curve)

Correlations Between Rectangle

and Salt & PepperThere is possibly a radial light gradient

from the bottom centre, causing all

isoreflective areas to interact with the edge

detection in the same way.

Demonstration

• Matlab Code Module: Bin_Conv.m

• Must have in Path: Threshold_Test.jpg

Results

• Eliminated (for the most part) salt and

pepper from the necessary parts of the

figure

• Attained a clear, single line detection of

edge

OpenCV + Android

We eventually want our

software on mobile devices.

• Camera + Computer

• Portable

• They’re everywhere

Motivation

• OpenCV–Most popular open source image

processing library

• Android–More cameras to choose from

–Cheaper to iterate

Why OpenCV? Why Android?

Image processing basics

• I/O

• Matrix conversions and operations

Edge detection implementations

• Canny

• Sobel

OpenCV Features

Outdated documentation on OpenCV

makes using it difficult

Learning Android

Porting to Android

Android Demonstration

Questions?

Acknowledgments Thank you to the following for aiding our research:

• AggiE Challenge Program

• Magda Lagoudas

• Dr. Jun Kameoka

• Dr. Lei Fang

• Jaskirat Singh Batra