ION BEAM TRIMMING OF SILICON DIOXIDE THIN FILMS

Henry Malm

School of Chemical Engineering Thesis submitted for examination for the degree of Master of Science in Technology

Espoo, 5.4.2019

Supervisor

Prof. Sami Franssila

Advisor

D.Sc. Ville Pale

Copyright © 2019 Henry Malm

Abstract

Author Henry Malm

Title Ion beam trimming of silicon dioxide thin films

Degree programme Chemical, Biochemical and Materials Engineering

Major Functional Materials Code of major CHEM3025

Supervisor Prof. Sami Franssila

Advisor D.Sc. Ville Pale

Date 5.4.2019 Number of pages 61+9 Language English

Abstract

Micro-electro-mechanical systems (MEMS) consist of mechanical and/or electrical

components in the micro scale. Microelectronic components need good control over

the fabrication process to achieve good yield and economical feasibility. For instance,

with bulk acoustic wave (BAW), surface acoustic wave (SAW) filters and Fabry-

Perot interferometers (FPI) is it common that certain critical film thicknesses directly

define the operation range of the device and thus are crucial to components

performance. The thickness variation needs to be sufficiently small to obtain good

yield from the fabrication.

To address these issues this thesis studies the ion beam trimming of silicon dioxide

thin films. The target was to obtain enough information to make decisions whether to

incorporate trimming step to existing FPI component fabrication. The obtained results

show that ion beam trimming improves uniformity of the silicon dioxide to 0.29 %

from 2.49 %. Metal contaminants generated from trimmer can be removed with HF

vapor etching and RCA washing while maintaining the good film thickness

uniformity. The results presented in this thesis provide important knowledge of the

trimming process for MEMS FPI development, which can be used in future process

integrations.

Keywords Ion beam trimming, silicon dioxide, thin film, MEMS, HF vapour

etching, SiO2, FPI, BAW, SAW

Abstract (in Finnish)

Tekijä Henry Malm

Työn nimi Piidioksidi ohutkalvojen ionisuihkutrimmaus

Koulutusohjelma Chemical, Biochemical and Materials Engineering

Pääaine Functional Materials Pääaineen koodi CHEM3025

Työn valvoja Prof. Sami Franssila

Työn ohjaaja D.Sc. Ville Pale

Päivämäärä 5.4.2019 Sivumäärä 61+9 Kieli Englanti

Tiivistelmä

Mikro-elektro-mekaaniset järjestelmät (MEMS) koostuvat mikrometri koossa

mekaanisista ja/tai sähköisistä komponenteista. Mikroelektroniset komponentit

tarvitsevat hyvän kontrollin valmistusprosessissa saavuttaakseen hyvän saannon ja

taloudellisen toteutettavuuden. Esimerkiksi akustisten aalto (BAW), pinta-akustisten

aalto (SAW) suodattimien ja Fabry-Perot interferometrin (FPI) kanssa on yleistä, että

tietyt kriittiset kalvon paksuudet ovat ratkaisevia komponenttien suorituskyvylle ja

paksuuden vaihtelun täytyy olla tarpeeksi pientä, jotta saavutetaan hyvä saanto.

Työssä tutkittiin piidioksidin ionisuihkuntrimmausta ja tavoitteena oli saada tarpeeksi

tietoa, jotta voitaisiin implementoida ionisuihkutrimmaus olemassa olevaan FPI

valmistukseen. Mittaustulokset osoittavat, että ionisuihkutrimmaus parantaa piidioksidin

tasaisuutta. Trimmeristä syntyvät metalliepäpuhtaudet pystytään poistamaan

HF-höyryetsauksella ja RCA-pesulla, säilyttäen samalla piioksidin hyvä tasaisuus.

Piidioksidin tasaisuuden paraneminen 2,49 %:sta 0,29 %:iin parantaa merkittävästi

MEMS FPI:n saantoa. Tässä opinnäytetyössä esitetyt tulokset antavat tärkeitä tietoja

MEMS FPI kehitystyöhön, jota voidaan käyttää tulevissa prosessi-integraatioissa.

Avainsanat Ionisuihkutrimmaus, piidioksidi, ohutkalvo, MEMS, HF-höyryetsaus,

SiO2, FPI, BAW, SAW

v

Preface

I would like to thank Professor Sami Franssila for being my supervisor and he has

arranged all practical situations, such as the thesis presentation and the maturity test. I

would like to thank Ville Pale for being good advisor and giving useful tips for writing

academical text. Always when I have had questions related to my thesis work, Ville

has had time to give his thought. Tuomas Pensala has been as a second advisor even

he has been very busy. I would like to thank Tuomas Pensala from participating my

thesis, giving thoughts and advices. VTT has provided good working environment to

do my thesis. I would like to thank VTT to funding and enabling me to do my thesis

in Micronova cleanroom.

Many oxide test wafers were used to study ion beam trimming. Liisa Valkonen has

done all my test wafer and I like to thank her for helping me to do my thesis. Jaakko

Salonen has trained me to use ion beam trimmer. Thank you to always helping me if I

have had problems with trimmer. During my thesis I have had good roommates, who

have done their thesis at same time as me. Together we have supported each other and

we have kept good working spirit. Especially I would like to thank my roommate Jonne

Vähänissi for helping me with my writing skills. You have read some critical parts of

my thesis and giving good advices how to write them better.

Special thanks goes to my parents. They have supported me during my studying time

from first grade to this point. When I have had a low point, you have cheer me up and

said that everything will be right. You have provided me a good home and growth

environment, so thank you.

Espoo 5.4.2019

Henry Malm

vi

Contents

Abstract ................................................................................................................... iii

Abstract (in Finnish) ................................................................................................ iv Preface ..................................................................................................................... v

Contents .................................................................................................................. vi Symbols and Abbreviations .................................................................................... vii

1 Introduction ...................................................................................................... 1 2 Ion beam trimming ........................................................................................... 5

2.1 Ion beam trimmer contamination .............................................................. 10

3 Applications of ion beam trimming ................................................................. 12 3.1 Surface acoustic wave filters .................................................................... 12

3.2 Bulk acoustic wave filters......................................................................... 13 3.3 Fabry-Perot Interferometer ....................................................................... 15

4 Fabrication and characterization methods ....................................................... 18 4.1 Thermal oxidation .................................................................................... 18

4.2 Low-pressure chemical vapour deposition ................................................ 19 4.3 Hydrofluoric vapour etching ..................................................................... 20

4.4 RCA wash ................................................................................................ 22 4.5 Spectroscopic reflectometer ...................................................................... 22

4.6 Inductively coupled mass spectrometry .................................................... 24 4.7 Secondary ion mass spectrometry ............................................................. 25

5 Results and discussion .................................................................................... 27 5.1 Trimming and HF vapour etching process flow ........................................ 29

5.2 Trimmer properties ................................................................................... 31 5.2.1 Trimmer operation modes ................................................................. 31

5.2.2 Trimmer repeatability ........................................................................ 32 5.3 HF vapour etching .................................................................................... 34

5.3.1 HF vapour etch repeatability ............................................................. 35 5.3.2 Trimmer effects to HF vapour etching ............................................... 36

5.3.3 HF compensating map ....................................................................... 37 5.3.4 The effect of over-trimming to HF vapour etching............................. 38

5.4 Contamination analysis ............................................................................ 41 5.4.1 Contamination depth analysis ............................................................ 41

5.4.2 Surface contamination analysis ......................................................... 45 5.5 Trimming and HF vapour etching repeatability......................................... 48

5.6 Experiment for thick oxide ....................................................................... 49 6 Conclusions and future interests...................................................................... 52

Reference ............................................................................................................... 55

vii

Symbols and Abbreviations

Symbols

d Distance

n Refractive index

R Reflection

T Transmission

θ Angle of the incoming light

viii

Abbreviations

Al Aluminium

AlN Aluminium nitride

APT Atom probe topography

Ar+ Argon ion

BAW Bulk acoustic wave

CH3O Methoxide

CH3OH2+ Protonated methyl alcohol

CH3OH Methanol

CH Hydrocarbon

CMOS Complementary metal oxide semiconductor

Co Cobalt

CO2 Carbon dioxide

Cs+ Cesium ion

CVD Chemical vapour deposition

DBR Distributed bragg reflector

DHF Diluted hydrofluoric acid - water mixture

DIW Deionized water

DL Detection limit

FBAR Film bulk acoustic resonator

Fe Iron

FIB Focused ion beam

FPI Fabry-Perot interferometer

FWHM Full width at half maximum

Ga+ Gallium ion

HF2− Bifluoride

H2 Hydrogen

H2O Water

HF Hydrogen fluoride

IC Integrated circuit

ICP-MS Inductively coupled mass spectroscopy

IR Infrared radiation

LCD Liquid crystal displays

Li Lithium

LPCVD Low-pressure chemical vapour deposition

MEMS Micro electro mechanical systems

MOEMS Micro-opto-electro-mechanical systems

WSS ICP – MS Wafer surface scan inductively coupled plasma – mass

spectroscopy

Ni Nickel

ix

O2 Oxygen

O2- Oxygen ion

O2+ Oxygen ion

PECVD Plasma-enhanced chemical vapour deposition

RCA Radio corporation of America

RF Radio frequency

RF-MEMS Radio frequency micro electro mechanical system

RIE Reactive ion etching

SAW Surface acoustic wave

SC-1 Deionized water (DIW) ammonia and hydrogen peroxide

SC-2 Hydrochloric acid-hydrogen peroxide- water mixture

SCI Scientific computing international

Si Silicon

SiF4 Silicon tetrafluoride

SiO2 Silicon dioxide

SIMS Secondary ion mass spectrometry

SMR Solidly mounted resonator

TEM Transmission electron microscopes

TEOS Tetraethyl orthosilicate

U Uranium

UV Ultraviolet

VPD ICP-MS Vapour phase decomposition inductively coupled mass

spectroscopy

VPD Vapour phase decomposition

VTT Technical research centre of Finland

1

1 Introduction

Our daily lives include many microelectronic technologies that enable many

applications and devices that we take for granted. These microelectronic components

need a good control over the fabrication process to achieve good yield and economical

feasibility. [1] If the process is not repeatable enough, it can affect components

performance and devices can differ between each other from batch to batch. This

creates problems especially with micro-electro-mechanical systems (MEMS), where

the devices are required to work with certain specification.

MEMS is a loosely defined term that includes devices consisting of mechanical and/or

electrical components in the micro scale. MEMS was commercially introduced at the

end of 1980 [2], [3]. MEMS components combine mechanical, optical, acoustic and

thermal functions enabling them to be used as sensors or actuators. [4] Actually many

devices in our life includes, many MEMS devices, such as inkjet printer head, or the

filters or sensors in mobile phone. As an example mobile phones and tablets hold many

MEMS parts, such as bulk acoustic wave (BAW) filters, MEMS microphones and

motion sensors (accelerometers, magnetometers and gyroscopes) [5].

MEMS components are many times smaller than comparable macro-system and

therefore one wafer can hold much more devices compared to macro-systems offering

cost benefits in high volume applications. [6] However, this miniaturizing creates

advantages and challenges at the same time. MEMS are fabricated using same

microfabrication methods as traditional integrated circuits (IC), such as lithography,

thermal oxidation and etching [2]. Moving mechanical parts are common with MEMS

and create fabrication challenges compared to IC devices [7]. Currently the market of

MEMS has grown to 20 billion and it is estimated to grow steadily. Some estimates

have stated that MEMS market could grow even as large as 82 billion by 2023 [8].

Most impact for sensors and actuators lie in the smart automotive, 5G and healthcare

markets. Biggest growth at the near future will come from RF-MEMS, which are

needed for the coming 5G networks. [8]

2

Micro-opto-electro-mechanical systems (MOEMS) is a special class of MEMS and

combines mechanical, optical and electrical moieties. First MOEMS components were

introduced during the 1990s and demonstrated the potential of miniaturization of

optical systems. Examples of commercial MOEMS devices include optical switches,

optical shutters, digital micro-mirror devices, laser scanners and dynamic micro-mirror

displays. Fabry-Perot interferometer (FPI) is one example of MOEMS device, where

optical system has been miniaturized to microscale. [9]

Fabry-Perot interferometer was introduced by C. Fabry and A. Perot in 1899 [10], [11].

At the beginning C. Fabry and A. Perot used G. Airy’s interference phenomena theory,

where light is reflected between two mirrors. They realized that their finding could be

used as a filter element in wide range of sensing applications. [11] By altering the

distance of the mirrors, the FPI can be made tunable. Tunable FPIs can reject unwanted

side bands and change the operating wavelength. Tunable FPIs can be used in many

applications, for example, in imaging, optical sensing and spectroscopy [12]. Using

modern fabrication methods, FPIs can be made sufficiently small to meet today’s

needs for volume.

The FPI miniaturizing trend has appeared during the last decade and this scaling down

has helped to reduce prices and even raised new application subjects. [10] MEMS FPI

have been used to detect gases from air, such as carbon dioxide (CO2) and

hydrocarbons (CH) [10], [13]. While spectroscopy is probably the main target field for

FPI, many other applications can also exploit FPI as well [10]. For instance, colour

filter in Liquid Crystal Displays (LCD) use FPI filters to improve colour purity.

Enhancement is done with FPI, so that unwanted transmitting light is blocked by

tuning air gap between the mirrors. [14] Another exiting prospect originates from

imaging and hyperspectral imaging. It means that photos can be imaged with different

spectral filters or wavelengths and this technique has been demonstrated in use in

medical or remote sensing applications to detect skin cancer or monitor ripening in

farming. [13], [15].

3

For a MEMS FPI filter, it is desirable to be able accurately control the distance between

the mirrors, which is mainly determined by the sacrificial oxide thickness. This gap

between the mirrors is crucial to the performance of the FPI, because it defines

operating wavelength, where the FPI will perform. In a typical VTT FPI process, the

oxide is deposited with low pressure chemical vapour deposition (LPCVD), which will

be etched away to create a cavity. LPCVD deposited films frequently exhibit thickness

variations across the LPCVD tube and even within a single wafer. This thickness

variation is so large that it will affect the desired FPI performance and thus methods

to improve film uniformity are very beneficial. One such method could come from ion

beam trimming. With ion beam trimming one can control the film thickness in sub-

nanometer scale and tune the gap between the mirrors to desired thickness. Ion beam

trimming uses ions to etch thin film layers more uniform. Focused ion beam is used to

remove non-uniformities from wafer surface and it is compatible for many materials.

Trimmer will etch thicker points on wafer to same level as the thinner points. The

oxide uniformity after trimming could potentially be in such level that thickness

variation is in desired specification across the whole wafer increasing the yield of FPI

fabrication.

The challenge of many ion beam trimming machines is that they will implant

contaminants into the wafer. Different contaminants will be implanted to different

depths, depending of the configuration of machine. For instance, the contamination of

aluminium (Al) and iron (Fe) in the substrate make wafers non-compatible for most

CMOS-clean process. Motivation of this thesis arose from these aforementioned pros

and cons of ion beam trimming in FPI process. In earlier studies, it was observed that

contamination in oxide penetrates mostly to 50 nm depth due to the amorphous nature

of the oxide film. Thus, contamination from trimmer needs a cleaning step to be a

potential fabrication method.

Another challenge is that trimming will affect the HF vapour etch properties, because

HF vapour will etch different etch rates as the ion beam trimming changes the surface

properties of the oxide. Moreover, contamination and ion induced damage will make

the HF vapour etching more non-uniform, which will affect overall uniformity of the

4

film. Target is to get ± 5 nm thickness variation and 0.5 % uniformity after trimming

procedure. However, if the HF vapour etcher will etch non-uniformly it will affect the

trimming result so much that it will make the trimming useless. Hence, methods to

compensate the HF non-idealistic etching was investigated in this thesis. One of these

methods was over-trimming, which reduces the etch rate non-uniformities coming

from the HF vapour etcher.

This work is divided into six sections; introduction, ion beam trimming, applications

of ion beam trimming, fabrication and characterization methods, result and discussion

and conclusions. At beginning of the thesis, trimming and its applications are

introduced. Also, all the fabrication and characterization methods, which are used in

this thesis are introduced. During this thesis new trimming procedure was studied with

dummy wafers. Wafers were grown with LPCVD TEOS oxide using a similar

thickness as a MEMS FPI would use. TEOS oxide trimming procedure was tested with

multiple parameters to find out what kind of problems would occur during the

trimming. Also, ion beam trimmer and HF vapour etcher interoperability was tested to

make sure that the thickness uniformity was at a desired level even after the HF vapour

etching. Test wafers were also tested for contamination. Contamination profile was

obtained with secondary ion mass spectrometry (SIMS) showing how deep the

contaminants penetrate into the oxide and verify that this contamination can be

removed. If the contamination is removed to certain level, trimmed wafers could

continue in principle to other IC classified equipments. Inductively coupled mass

spectroscopy (ICP – MS) tests were also done to make sure that equipment and wafer

carriers do not contaminate the wafers. With these tests, the target was to get enough

information to make decisions to incorporate the fabrication trimming step to existing

FPI chip fabrication.

5

2 Ion beam trimming

Ion beam systems are widely used in different applications, such as preparation of

samples with focused ion beam (FIB) for transmission electron microscopes (TEM),

altering thin film characteristics and atom probe topography (APT) [16]. One

interesting characterization and fabrication method is FIB, which can deposit or etch

3D images on surface. FIB uses highly focused ion beam to bombard the surface. The

effective source size in FIB is 5 nm, which is much smaller than in an ion beam

trimmer, which is in millimeter range. [17], [18] This means that in FIB the

processable area is much smaller than ion beam trimmer is processing. [17]

Ion beam methods include different variety of surface improving methods. In all of

these material is removed from surface for different purposes, such as etching,

trimming, cleaning. [19]–[21] One target is to smoothen the surface with low energy

ion beam. With ion beam assisted surface smoothing the surface roughness is

improved. In this method the surface roughness can be improved even from polished

surface. For example, even 2 nm surface roughness can be improved to under

nanometer roughness. Smoothening is more effective if the surface thickness variation

spatial distances are large (~ 1 µm) compared to small spatial distances (few

nanometer). [21], [22]

Ion beam trimming machine can be integrated with a sputtering system. At the other

chamber the material is sputtered on the wafer and at other chamber ion beam trimmer

will trim the sputtered film uniform with desired thickness. This kind of combined

process is very efficient when fabricating bulk acoustic wave (BAW) filters, because

both operations are done in same machine. [22] Most depositions do not produce

uniform films, but some thickness variation is always present. This can be seen

example in Figure 1, which shows a 375 nm thick TEOS oxide after LPCVD

deposition. Gases will diffuse in the surface at different rates and deposition rate will

differ at different locations on the wafer. Thickness variation is even bigger with

thicker films and can reach above 100 nm for 1 – 2 µm films. As an example, the

TEOS oxide in Figure 1 has over 6 % uniformity difference when comparing the

highest and lowest point on the wafer.

6

Figure 1. Image illustrating the thickness variation across the wafer of LPCVD

deposited TEOS film. Average thickness is 375 nm and variation ± 23 nm.

Ion beam trimming can be seen as ion beam etching, where ions hit the target material.

Plasma is formed by an electrical discharge and ion beam trimming modules usually

utilizes directional argon ions, but other ions can be also used. These colliding ions

will sputter surface atoms away as demonstrated in Figure 2. [1] Focused ion beam is

used to trim non-uniformities from the wafer surface and it is compatible with many

materials. Ion beam trimming is a non-contact process and uses a broad focused ion

beam for trimming. Trimmers use high vacuum to trim in the nanometer scale. Usually

the beam is stationary while the wafer moves and is scanned under the beam. Trimmer

will automatically calculate the desired thickness remove at each location from a

thickness profile map.

7

Figure 2. Illustration of the ion beam trimmer etching process. Argon ions are

accelerated towards the substrate to collide with the surface atoms and sputter them

away. In AMSystems ion beam trimmer, the ion beam is perpendicular to the

substrate. Adapted from [23]

Ion beam power and material has an effect how fast trimmer will etch. Different ion

sources can be used, but for example, AMSystems uses a closed drift ion source,

which is shown in Figure 3. Principle of closed drift ion source is to get electric

discharge between the anode and cathode to create ion beam. Discharge plasma is

created and plasma is accelerated with electric fields. In addition, extra ions are

produced when the electrons collide with atoms of the gas feed. Magnetic layer type

closed drift ion source has ceramic walls in the discharge channel, which have an

important role. The electrons and ions that collide with the ceramic wall, generate

low energy secondary electrons, which enable better continuous electron

acceleration process. Ionization and acceleration happens in ceramic channel and

keeps the electron temperature low in the plasma and helps to create continuous ion

beam. [24] Close drift ion source’s magnetic system contains iron. When ions are

bombarded on the wafer, iron contaminants are implanted at the same time to the

surface from the ion source. This is known problem of the ion beam trimmer’s.

8

Figure 3. Magnetic layer type closed drift ion source. It consist of magnetic system,

ceramic channel, anode and cathode. Principle of closed drift ion source is to get

electric discharge between the anode and cathode to create ion beam. Discharge

plasma is created and plasma is accelerated with electric fields. In addition, extra

ions are produce when electrons collide with atoms of the gas feed. Adapted from

[25].

Spot size of the ion beam trimmer can be few millimetres at full width at half maximum

(FWHM). Trimming can be done two ways, i.e., changing the scanning speed or

power. Thickness profile map is used to accommodate the power of ion source. Wafer

is moving at constant speed and the thicker spots are bombarded with higher power

compared to thinner points. Ion beam stays at the same spot. The ion beam trimmer

can use thickness maps from SCI FilmTek 2000M or Excel files. Trimmer scans the

wafer in xy-direction as shown in Figure 4. Step size (mm) describes the width of the

scanning and step. Trimmer scans the whole wafer multiple times during the trimming

and maintains some degree of overlap between the adjacent scans. [26]

9

Figure 4. Basic principle of ion beam trimming. The wafer is scanned in xy-direction,

while the ion beam stays stationary. Step width is calculated automatically from the

thickness map. Adapted from [27]

Two step trimming has been shown to be effective for many materials [28]. With this

technique less than 0.1% uniformity of thickness has been demonstrated. Two step

trimming means that 80 – 90 % of the target thickness is trimmed with first trimming.

Second trimming then trims to target thickness with the measured thickness map.

Between the trimmings, film thickness is measured enhance the trimming result. S.

Mishin and et al have studied several trimming of metal films, including aluminium

(Al), cobalt (Co), nickel (Ni) and iron (Fe) [28]. Results show that two step trimming

significantly improves the surface uniformity compared to one step trimming. Also,

target thickness can be reached more accurately when using two trimming steps. In

Mishin’s study, after the first trimming the obtained thickness was 5 nm and after

second trimming it was reduced to 0.5 nm. With a two step trimming process, the

uniformity is slightly improved with the first step to make second trimming more

accurate. As a conclusion, first trimming will improve thickness variation factor of 4

so that second trimming will get the uniformity in 0.1 % range. [28]

Trimming accuracy is not only dependent on ion beam accuracy, but other factors will

also affect the uniformity result. For example, the thickness map can be a limiting

factor in trimming process. If the thickness profile is not sufficiently smooth and

continuous, it can ruin the result of the trimming. These problems can occur from the

10

thickness map measurement or if the surface has lots of anomalies. Trimmer can only

be as accurate as the thickness map measurement. Trimmer cannot adapt the beam

power accurately if the surface has large thickness gradients across small portions of

the substrate leading to inaccurate results. Data processing has been shown to help

with trimming performance with large anomalies. For example, AMSystems has a

software, which will smoothen the thickness profile map and helps trimmer to etch

more accurately. [28]

Trimming machines have usually 1 – 3 % limitations to uniformity results across

wafers and same 1 – 3 % limitations on repeatability. It cannot be emphasized enough

that the thickness measurement is a key step in trimming and uniformity result depend

on it. If the material properties change during the deposition, this can cause issues in

the thickness map measurement, because the refractive index may vary. Photoresist or

plasma etches can influence the surface layers etch rate when comparing to bulk

material. This makes the trimming to desired thickness harder and good planning of

process is needed. [28]

2.1 Ion beam trimmer contamination

In essence, all ion beam trimmers will introduce contaminants on the trimmable

material. Contamination comes usually from the machine itself, because plasma on

and ions also bombard the walls and aperture shield of the machine and these will be

sputtered into surface of the trimmed thin film. The manufacturer of AMSystem ion

beam trimmer has stated that their closed drift ion source will sputter iron to the

sample. In addition, the ion beam will hit the aperture plate, which is made from

aluminum and this aluminum will be implanted to the sample. The iron and aluminium

sputtering residues are left around 30 – 50 nm depth of the oxide thin film after

trimming. Contamination depth varies depending how much power is used and what

material is trimmed. Furthermore, ion beam trimming produces two types of damage

to wafer; crystal defects and impurity deposition, which are comparable to reactive ion

etching (RIE). [29] The damage is located on the surface and does not occur deeper in

the film.

11

Metal contamination in silicon and silicon dioxide have a tendency to diffuse, even at

room temperature and especially in thermal processing [30]. For example, if a

trimming would be used in Fabry-Perot processing, there would be many processes

with elevated temperatures and metal contamination could potentially spread into the

IC-line. Solubility of aluminium in silicon is low, so aluminium diffusivity is tested in

literature using boron or phosphorous doped silicon. Test show that aluminium

dopants have high diffusivity in doped silicon above 900 ºC. Aluminium diffuses

through point defects. [31] Iron is common contaminant. Iron has high diffusivity and

solubility in silicon at higher temperatures. Temperature has big effect how much of

iron will diffuse. Below 900 ºC diffusion is not so significant than above 900 ºC [30].

It has been shown that iron has also high diffusivity in silicon dioxide. Iron will diffuse

in silicon dioxide through point defects, i.e., oxygen vacancies and other vacancies.

Negatively charged iron and silicon ion defects will attract positively charged oxygen

defects. [30] Silicon dioxide-silicon interface collects impurities [30], [32]. It has been

shown that when thermal oxide is grown on iron contaminated silicon, iron will

precipitate into the interface and further cluster into particles at the interface [32].

12

3 Applications of ion beam trimming

Ion beam trimming is extensively used in industry, because it provides good

throughput (process time), economical feasibility (improves yield), adjustability

(parameters can be modified), and quality (uniformity and accuracy) [33]. In some

cases, longer processing time is acceptable if yield increases. With powerful ion

sources the etching rate is fast and large amount of material can be etched accurately

in a short time. Even etch rates of 1 µm/min can be achieved, depending on the

trimmable material and from the used ion beam source [28]. Applications, which are

sensitive to thickness variation of layers, will benefit from ion beam trimmer. [1]

For instance, ion beam trimming can be used to improve the yield of bulk acoustic

wave (BAW) filters [16], [34], surface acoustic wave (SAW) filters [16], [34] or

Fabry-Perot interferometers (FPI) [10]. For all these components it is common that

some film thicknesses are crucial to components performance and the thickness

variation needs to be sufficiently small to get good yield from the fabrication. Also, it

is important to control thickness wafer to wafer. [34] Other application fields can be

benefit from ion beam trimming, where accurate control of film thickness is essential.

3.1 Surface acoustic wave filters

SAW filters have been used to guarantee spectral integrity of RF signals [34]. SAW

resonator consist of interdigitated transducer and piezoelectric material, which is

illustrated in Figure 5. Interdigitated transducer structure will convert electrical input

signal to acoustic waves. Interdigitated transducer consist of metal electrodes and they

will reflect and send waves to form standing wave pattern. Interdigitated transducer

generates and detects acoustic waves and performs the filtering function in a SAW

filter. Geometry of the interdigitated transducer’s electrode fingers has an effect to the

signal processing. SAW filters operate below 2 GHz frequency. [35], [36]

13

Figure 5. Basic principle of SAW filter. SAW resonator consist of interdigitated

transducer, which is produced with metal electrodes and piezoelectric layer under

metal electrodes. Adapted from [37]

SAW filters the metal electrode layers is the crucial layer that needs to be smooth and

uniform [34]. It has shown that target frequency level can be achieved at high precision

with trimming. S. Mishin et al. have tested trimming for SAW filters and their result

show that frequency/target ratios are 0.99 – 1 after trimming for different materials,

while before trimming the levels are around 0.96. [38] This means that target

thicknesses over the wafer can be produced in sub-nanometer accuracy.

3.2 Bulk acoustic wave filters

BAW devices can operate at higher frequency than SAW devices, which makes it more

suitable as a filter in 5G. BAW filter usually work above 2 GHz when SAW filter work

below 2 GHz. Same time BAW generates better performance compared to SAW

devices because BAW chip is much smaller than SAW chip. [34], [39] Fundamentally,

BAW is a thin film resonator, where piezoelectric film is placed between metal films

as shown in Figure 6. This structure can efficiently store acoustic energy into the

device and attain high electrical quality factor, which means that narrow bandwidth

can be produced. BAW uses piezoelectric material, such as aluminum nitride (AlN),

which is easy to fabricate and at the same time it has good performance. Two common

14

BAW structures are film bulk acoustic resonator (FBAR) and solidly mounted

resonator (SMR), which can be seen in Figure 6. [39] FBARs have a sacrificial layer,

which is etched to get cavity below the resonator that isolates the resonator from the

substrate. SMR, on other hand, utilize acoustic Bragg reflectors to achieve acoustic

isolation from the surface. Electrodes combined with piezoelectric film form the

resonator structure.

Figure 6. Common BAW structures; film bulk acoustic resonator (FBAR) and

solidly mounted resonator (SMR). FBARs have a sacrificial layer, which is etched

to get cavity below the resonator that isolates the resonator from the substrate. SMRs

achieve acoustic isolation from the substrate using Bragg reflector. Adapted from

[39].

BAW filters work similarly than SAW, but there are performance advantages.

However, BAW filter manufacturing has challenges. [34] For example, BAW devices

have piezoelectric and electrode layers, which need to be at certain thickness to get the

filter to work at desired frequency. Small changes in thicknesses on the wafer and also

wafer to wafer will have massive effect on performance. Only option is to improve

piezoelectric film and metal contact thicknesses to get accurate frequency band. The

required thickness has to be around 0.1 %, while the deposition systems usually

produce 1 % uniformity. [39]

15

3.3 Fabry-Perot Interferometer

FPI is an optical filter, which is used normally in visible or infrared region. The basic

structure of FPI device includes two semi-transparent reflective surfaces (mirrors) that

are parallel to etch other. Reflectors are separated from each other from distance (d)

and light is reflected and transmitted between the reflectors. This produces interference

patterns, which are used to detect for example gases. [10], [11] Both mirrors can be

fixed or other mirror can be moved to change the air gap width, which changes the

band pass wavelength [40]. Figure 7 shows FPI mirror structure and how light is

reflected and transmitted. Transmitted light is again reflected and transmitted and this

multiple reflections continue infinitely. The reflection R and transmission T happen at

every interface and are governed by Fresnel equations. In theory maximum

transmission is happening when there is loss-less reflector (R + T = 1). Theory assumes

that the absorption leading to 100 % transmission. [10], [11]

FPI uses multiple-beam interference and can be used to study spectral lines [41].

Mirrors do not need to have near 100 % reflectivity for signal to exit the filter as narrow

band pass. In other hand, finite transmission is needed. [10] This means that high

transmittance can be achieve when reflections hit from mirror to mirror at same phase.

The phase difference is 2π. [42], [43] Tunable FPI can reject unwanted side bands by

changing gap between the reflectors. Gap changes the band pass wavelength. [44]

These band pass filters are normally tuned to fixed wavelengths [45].

16

Figure 7. Basic principle of the FPI. Two parallel mirrors that are distance d apart

from each other. At every interface reflection and transmission is happening. Mirrors

together create multi-beam interference by reflecting and transmitting the light

multiple times. Adapted from [46]

MEMS FPI includes Distributed Bragg reflector (DBR) with silicon-silicon nitride

multilayer. Example of MEMS FPI structure can be seen Figure 8, where two DBRs

are separated with air cavity. DBR are fabricated by growing altering layers of low

and high refractive indexes. This creates desired reflectance spectrum. [47] DBR

cavity layer thickness has an effect on the wavelength, in which the DBR works and it

need to be tuned to application’s specification [10]. When the reflective indexes are

known, reflectivity of DBR can be calculated [10], [48].

Figure 8. Example of MEMS FPI structure. Distributed Bragg reflector (DBR) are

separated air gap, which is formed with sacrificial oxide. DBR is formed of thin film

layers by altering low and high refractive indexes.

17

MEMS FPI sacrificial oxide is few micrometers thick and thickness varies so much

that only small portion of wafer is inside the desired thickness. Sacrificial oxide

thickness will determinate what wavelength will pass the Fabry-Perot interferometer.

Trimming will make sacrificial oxide film more uniform and increase the usable wafer

area and yield. In reality there are always defects, for instance, mirrors are not perfectly

parallel and these factors will limit the transmission and reflectance of FPI. Gap

between the mirrors is problematic, because it is desired to be at a certain thickness

across the chips. Previously, yield has been a problem in the MEMS FPIs fabrication

and trimming could significantly increase it.

18

4 Fabrication and characterization methods

This section introduces different fabrication and characterization methods used in this

thesis. The basic principles of thermal oxidation, low pressure chemical vapour

deposition, hydrofluoric vapour etching and RCA washing are introduced. Also,

characterization methods utilized in this thesis are demonstrated.

4.1 Thermal oxidation

Thermal oxidation is used produce a thin layer of oxide in furnaces, where many

wafers are processed at the same time. Silicon will oxidise in high temperatures in the

presence of oxidizing ambient. Oxidation temperatures are usually around 1000 ℃ and

oxidizing ambient can be either water (wet oxidation) or pure oxygen (dry oxidation).

[49] These ambients have different chemical reactions, which are presented in

chemical reactions (1) for wet and (2) for dry oxidation [7]

Si (s) + 2 H2O (g) → SiO2(s) + 2 H2 (g) (1)

Si (s) + O2 (g) → SiO2(s). (2)

These ambients will give different times to produce thermal oxide due to different

growth kinetics between them. Model of the oxide growth was introduce by Deal and

Grove and it can be used to estimate how long it takes to grow thermal oxide at certain

temperature and oxidizing ambient [7]. The model is linear-parabolic and at the

beginning, growth is linear, limited only by surface reactions. [50] After the initial

linear regime, the growth will saturate and shift towards to oxidizing ambient diffusion

on silicon-oxide interface. Dry oxidation has a slower deposition rate than wet

oxidation, because the oxygen atoms diffuse slower on the silicon-oxide interface. [7]

The crystal structure of silicon also affects how fast the oxidation occurs and the

growth rate will increase with increasing temperature [7], [49], [50]. In thermal

oxidation, the oxide will grow on both sides of the wafer.

19

Thermal oxide is better quality compared to low-pressure chemical vapour deposition

(LPCVD) or plasma-enhanced chemical vapour deposition (PECVD) oxides, because

thermal oxide’s uniformity and density is better. Thermal oxidation will use silicon

from surface, while LPCVD and PECVD deposits totally new layer of silicon dioxide.

Also, thermal oxide has bigger dielectric constant than CVD oxide. On the other hand,

CVD growth rate is much faster compared to thermal oxidation and that is why it will

form worse quality oxide than thermal oxidation. [7]

4.2 Low-pressure chemical vapour deposition

Low-pressure chemical vapour deposition (LPCVD) is a film deposition method used

to grow solid dielectric materials on both side of the substrate (wafer). Materials are

limited to oxides, polysilicon and nitrides. Mechanics of LPCVD can be seen in

Figure 9. In LPCVD, gaseous reactants are pumped to reactor, where gases react

among themselves and produce solid material on substrate. At the same time

by-products are created and pumped away. The lower pressure of LPCVD improves

film uniformity compared to CVD, because unwanted gas-phase reaction are reduced.

Wafers can be loaded in to LPCVD reactor close together, because it is surface

controlled reaction meaning that wafers surface is the limiting factor of the reaction

and there is excess of source gases. [7]

Figure 9. LPCVD growth mechanics. Gaseous reactants are pumped to reactor,

where gases react among themselves and produce solid material on substrate. At the

same time by-products are created and pumped away. Adapted from [7].

20

4.3 Hydrofluoric vapour etching

Hydrofluoric (HF) vapour is used to etch silicon dioxide and it very useful in etching

sacrificial oxide in suspended or released MEMS structures. HF vapour etching does

not exhibit stiction that is problem with wet etching. Stiction means that above

structure will permanently attach to underlying layer due to capillary forces. [51], [52]

HF etching can also be used to etch masked profiles. The chemical reaction for HF

vapour etching is shown in Eq. (3) and (4). The etching of silicon oxide with HF vapour

will produce water as shown in Eq. (3). Water will also start HF molecules ionization

and it will react with silicon oxide [52]

SiO2 + 4 HF → 2 H2O + SiF4. (3)

As mentioned earlier, water is not beneficial when doing sacrificial release etching due

to stiction problem. Alcohols, such as ethanol, methanol or propanol can also be used

to ionize HF molecules. [51], [52] Micronova HF vapour tool uses ethanol-water

mixture to ionize the HF. Use of alcohol-water mixture decreases the water

concentration, which lowers stiction risk. Formula (4) presents the chemical reaction

for HF etching process with ethanol (CH3OH). Ethanol will ionize the HF molecules

as shown in formula (4) to HF2− [52]

2 HF + CH3OH → HF2− + CH3OH2

+. (4)

Ionized HF2− is absorbed onto silicon oxide and reacts as show in formula (5) [52]

SiO2 + 2 HF2− + 2 CH3OH2

+ → SiF4 + 2 H2O + 2 CH3O. (5)

The etch rate of silicon oxide in HF will change according how fast is the ionization

reaction. Etch rate decreases with increasing temperature. This is due to the fact that

the amount of water that works as an initiator in the reaction decreases at higher

temperatures. In addition, HF and alcohol partial pressures affect etch rate by

enhancing reactions on silicon oxide interface. [52], [53]

21

Sacrificial layers are used to fabricate more complicated structure, such as cavities,

which release movable parts or separate devices from substrate [50]. HF vapor etcher

can be used to etch either masked profiles or under etch through the holes. Figure 10

shows how HF vapour is etching underlying oxide of FPI structure. Sacrificial oxide

is selectively removed at the locations under the holes. Material, which is on top of the

sacrificial layer is chosen so that it will not be etched with HF. Typically, release etch

is one of the last steps in a process flow, because opened structure is weaker after the

release.

Figure 10. Illustration of etching sacrificial oxide with HF vapour in FPI structure;

a) FPI structure before release, b) small holes are plasma etched to upper mirror

layers, c) HF vapour can diffuse to SiO2 and etch cavity between the mirrors, d)

released FPI structure.

22

4.4 RCA wash

RCA washing is 3-step wafer cleaning procedure, where most of organic material,

metals and particles are removed from wafer surface [7], [49]. It was developed by

electronics company called Radio Corporation of America in 1965 and published in

1970 [54]. First, organic contaminants are removed with alkaline solutions. Oxidizers

are used to control the etching of alkaline solutions and cleaning can be improved in

higher temperatures. [49] Different chemical mixtures are used, but typical mixture

contains deionized water (DIW), ammonia and hydrogen peroxide. This mixture also

referred to as SC-1. Surface of the wafer is oxidized during the SC-1. Also, the

particles zeta potential changes so that particles repel each other in alkaline solutions

due the electrical repulsion effect. [55], [56] At next step, diluted hydrofluoric acid-

water mixture (DHF) is used to remove the thin silicon dioxide layer. This leaves a

hydrophobic surface to silicon and protects it from oxidizing. Finally remaining metal

contamination is cleaned from the surface with hydrochloric acid-hydrogen peroxide-

water mixture (SC-2). This treatment also leaves a passivating oxide layer to surface

to protect against contamination. [49], [56], [57] Temperatures and cleaning times may

vary from room temperature to 80 ºC and from 1 to 20 minutes, respectively [7], [56].

4.5 Spectroscopic reflectometer

Spectroscopic reflectometer characterizes film thicknesses using the reflection of light.

Visible, ultra violet, or infrared light can be used and it is non-contact method. Films

need to be transparent or semi-transparent, for example, only very thin metal films can

be measured [58]. Spectroscopic reflectometer measures the reflectance from a thin

film or a stack of films. Usually, light source and detector are perpendicular to the

sample, but exceptions also exist. Reflectance will provide optical thickness and to

determinate physical thickness, refractive index and extinction coefficient values are

needed from database. [59], [60]

The basic principle of a reflectometeric measurement for simple one layer case can be

seen in Figure 11. Part of the light is transmitted into film and part of the light is

reflected. Transmitted light in thin film undergoes multiple reflections between two

23

interfaces of the media. Film thickness, refractive indices and the angle of incidence

have an effect to the spectral reflectance, from those information physical thickness

can be determined by fitting a physical model to the measured reflectance spectrum.

Also, refractive index can be used as a fittable parameter. Before any measurement, it

is essential to know the physical model. [61] Thicker films will give more signals

intervals compared to thinner films [59], [60], [62].

Figure 11. Spectroscopic reflectometer is a thin film thickness measurement method.

Transmitted light in thin film undergoes multiple reflections between two interfaces

of the media. Spectroscopic reflectometer measures the reflectance spectrum from

the structure and fits the best physical parameters to the given model. Adapted from

[60]

Spectroscopic reflectometer was used to characterize the thickness profile of the oxide

film on the silicon wafer. This thickness map was used to trim oxide and check that

trimming procedure was successful. Thickness profile was measured with FilmTek

2000M reflectometer. 81-point measurement was used according to ion beam trimmer

manufacturer’s specification. Figure 12 shows the measurement point-map, where the

starting point is in the middle. Same coordinates are used with the ion beam trimmer

and this map can be modified in Excel.

24

Figure 12. FilmTek 81-point measurement map, which is used for thickness profile

measurements. Same coordinates are compatible with AMSystems ion beam

trimmer.

4.6 Inductively coupled mass spectrometry

Vapour phase decomposition inductively coupled – mass spectroscopy (VPD ICP –

MS) is a characterizing method, where trace elements are collected to analyse trace

element or their quantity from surface of the silicon wafer. Vapour phase

decomposition (VPD) is sample preparation technique, where wafer is etched with HF

vapour to remove native or thermal oxide. A liquid droplet is pipetted onto wafer

surface and VPD residue is collected to droplet. Droplet is then exposed to ICP plasma,

within will atomize the VPD residue and analysed with a mass spectrometer. Elements

from lithium (Li) to uranium (U) can be detected with mass spectrometer. [63] One

measurement can detect multiple elements, which makes this technique effective. If

thin film which is wanted to analyse is different than silicon, wafer surface scan (WSS)

can be used to collect any sample from wafer surface. So, with wafer surface scan

inductively coupled plasma – mass spectroscopy (WSS ICP – MS) information can be

collected from any type of wafer. Type of surface film does not matter, when detecting

trace metal elements with this method. Similarly to VPD, WSS will collect liquid

sample for ICP – MS to be vaporized, ionized, atomized and extracted with plasma

into a mass spectrometer.

25

In this work, VPD ICP – MS was used to determinate contamination coming from the

tools and the various wafer handling steps by operators. The analysis was done for ion

beam trimmer and HF vapour etcher and those were compared to clean prime wafers,

if the machines will contaminate the backside of the wafer during processing. WSS

ICP – MS was also used to determinate HF vapour and RCA cleaning effect.

4.7 Secondary ion mass spectrometry

Secondary ion mass spectrometry (SIMS) is a widely used trace element analysing

method for solid samples. It is based on bombardment of ions to sample surface, where

secondary ions are extracted back to detector. Secondary ion are collected and mass is

analysed using different methods by separating ions. Quadrupole, magnetic sector or

time of flight methods are usually used to separate the ions. [58], [64] Ion beam sources

usually uses oxygen (O2+, O2-), cesium (Cs+), argon (Ar+), gallium (Ga+) ions [58].

Samples need to be solid and stable in vacuum. Basic principle is shown in Figure 13,

where ion gun bombards primary ions to sample and ions are extracted from sample

to mass analyser and detector. Detector can characterize mass spectrum, 3D image or

depth profile from the sample surface. Wide range of elements can be detected at low

concentrations. Detection limit is part of million to parts per billion. [64]–[66] Depth

profile can be from few angstroms (Å) to micrometers (µm) [65].

In SIMS mechanics, the secondary ion are bombarded to sample and atoms are

sputtered away. Ions are hitting samples surface at high kinetic energies and

collision leads to the extraction of both neutral, negative and positive species from

the surface. These charged atoms are referred to as secondary ions. Collision of the

primary beam can be explained with the collision cascade model. Ions collide with

sample surface atoms and pass energy to target atoms. These target atoms collide

more with other sample atoms in a continuous process. Recoiled target atom will be

extracted to detector of the SIMS. [65], [66] Extracted ions will travel to mass

analyser, where energy of the ions is detected. Secondary ions are controlled inside

the mass analyser with ion lenses and strong magnets. The mass of the ions is

detected with electromagnets by bending ions travel path to let certain ions pass to

the detector. [58]

26

Figure 13. Basic principle of secondary ion mass spectrometry (SIMS). Ion gun

bombards primary ions to sample surface and secondary ion are extracted from

sample. Secondary ions travel to mass analyser and separate the ions. The detector

can obtain mass spectrum, 3D image or depth profile from the separated ions.

Adapted from [65], [66]

SIMS can be operated in two different modes: static and dynamic. Static SIMS is used

detect elemental and molecular information from the top of the surface. Also, low

(primary) ion flux is used and it has low secondary ions yield. Static SIMS gives

surface mass spectrum and 2D surface ion image. Dynamic SIMS removes more

material from surface and detect elemental information, such as depth profile, mass

spectrum and 3D image of the depth profile. [58] In this work, dynamic SIMS was

used to determinate how deep the contaminants from trimmer were implanted. This is

important to know for designing the contamination removing steps. Also, the

contamination level of Fe and Al was studied on trimmed oxide.

27

5 Results and discussion

This section introduces the results and observations of ion beam trimming and cleaning

steps, which will be introduce in Sections 5.1, 5.2 and 5.3. Trimming and HF vapour

etching process flow is also introduced and how trimming affects the HF vapour

etching. Also, methods how to improve uniformity of the TEOS oxide and same time

remove contaminants, which are generated with the ion beam trimmer are discussed.

Trimming was tested with annealed TOES oxide wafers. These tests were used to

monitor what kind of problems and parameters are needed to take in account with

trimming and HF vapour etching. This knowledge can be used to test trimming with

FPI test structures and integrate trimming to the MEMS FPI process platform.

All trimming tests were done with 150 mm p-type wafers that had TEOS oxide

deposited with LPCVD. Aim of trimming was to use as minimum amount of trimming

steps to get best possible uniformity. Two type of oxide thicknesses were tested; thin

annealed TEOS oxide (400 – 500 nm) and thick annealed TEOS oxide (2 µm). LPCVD

oxide growth was done with fully and sparse loading at 710 °C. Thick oxides were

grown with sparse loading and thin oxides were grown with both full and sparse

loading. Thinner oxides were grown in one growing stage and thicker needed three.

All TEOS oxide wafers were annealed at 900 °C for 60 minutes. Thin TEOS oxide

wafers, where first tested to know what kind of problems to expect with thicker TEOS

oxides.

From the thin TEOS oxide tests we found out that maximum power of ion source does

not affect trimming result and higher power just makes trimming faster. Hence the

value for maximum power was set to 300 W. Minimum power what can be used with

AMSystems ion beam trimmer is 5.4 W, because under that power the trimmer’s ion

source cannot produce accurate output. First, 6 W minimum power was tested, but

there were problems after trimming to etch with HF vapour. That is why over-trimming

scheme was introduced, which raised minimum power to 100 W and was used with all

thick oxide test. Actually, AMSystems have stated that minimum and maximum power

ratio should be under 4 and powers what were used with over-trimming bring the ratio

to around 3.

28

Ion beam trimmers scanning width (step) was tested with multiple widths. Small step

(< 0.5 mm) is slow, so optimal step was found to lie around 1 – 1.5 mm. Trimming

takes around 15 – 30 minutes with 1 – 1.5 mm step and result of trimming is good.

0.25 – 2 mm step was mainly used during the thick oxide test, because small step is

only option to remove large amount of material even if it takes longer to trim.

HF vapour tool was used to etch approximately 50 nm of oxide from surface. The HF

vapour exposure time was 60 seconds during the recipe that was used with all HF

vapour etchings. Thicknesses of the oxide were measured with SCI FilmTek 2000M

reflectometer. SIMS and WSS ICP – MS contamination tests were ordered from EAG

lab. VPD ICP – MS contamination analysis was ordered from Balazs lab.

SIMS and WSS ICP – MS analysis wafers had 500 nm thick LPCVD TEOS oxide

wafers, which were annealed at 900 °C for 60 minutes. Three wafers were tested with

SIMS. An annealed TEOS oxide wafer was used as a reference. Trimmed wafer was

etched with maximum power (300W) to obtain the maximum penetration depth for the

contaminants. Cleaning reference was also trimmed with 300 W power and then HF

vapour etched and washed with full RCA cycle. SIMS analysis was performed from

the middle of the wafers. Two wafers were tested with WSS ICP – MS. These WSS

ICP – MS analysis were done to annealed TEOS wafer, which were trimmed with

maximum power (300W) and HF vapour etched. Second wafers were identical, but

RCA wash was executed after HF vapour etching.

VPD ICP – MS contamination analysis was done for blank non-operated p-type wafers

to test the contamination coming from tools and manual handling. A clean wafer was

used as a reference. The reference for trimmer was loaded into the trimmer machine

upside down for 60 seconds and no trimming was done. Same procedure was done for

HF vapour etcher reference for 30 seconds.

29

5.1 Trimming and HF vapour etching process flow

The full process flow that incorporates trimming and cleaning steps is shown in

Figure 14 and it includes wafer thickness profile measurement, trimming map creation,

ion beam trimming, HF vapour etching and RCA washing. First, wafer is measured

with spectroscopic reflectometer to get oxide thickness profile. This will be used to

create trimming map in Excel by adding a HF compensating map to the measured

thickness profile map. Trimming map creation is shown in Figure 15 and this

compensating map will create a sloped profile on the oxide surface. This HF

compensating map creation is presented more in Section 5.3.3.

Wafer can be trimmed either one or many times depending how uniform the surface is

required to be. If additional trimmings are used, new thickness map is needed for a

new trimming map. This created thickness profile map is then used as a map for the

next trimming. After the last trimming, oxide is etched approximately 50 nm with HF

vapour to reveal contamination on the surface. After every trimming and HF vapour

etching wafer thickness profile is measured to monitor the results. Finally, the wafers

are cleaned with a full three-step RCA wash.

30

Figure 14. Schematic illustration of trimming process flow. First, thickness profile

is measured for the trimmer. After measurement, HF compensating map is added to

measured thickness profile map. Next, the wafer is trimmed according to the created

map, but trimmer will contaminate the surface and HF vapour etching and RCA

washes are used to clean the contaminants. If additional trimmings are required, a

new thickness measurement is needed for additional trimming iteration.

Figure 15. Trimming map creation from the measured thickness profile map and HF

compensating map. Opposite profile of HF vapour etching is needed to produce as

uniform films as possible after the HF vapour etching. a) Oxide thickness profile is

measured with spectroscopic reflectometer, b) HF compensating map is added to top

of this. HF compensating map is created from HF vapour etch rate profile. c)

Spectroscopic reflectometer thickness profile combined with HF compensating map

is used as trimming map for the trimming process.

31

5.2 Trimmer properties

During the thesis AMSystems cluster tool with trimming module was used to trim the

wafers. As mentioned earlier, the ion beam power and the etchable material will affect

how fast the trimmer will etch. AMS trimming module utilizes argon ion source that

has 7 mm FWHM spot size. Thickness maps from SCI FilmTek 2000M or Excel files

are used to create a trimming map for the ion beam trimmer. AMSystem’s trimmer

will calculate the width of the scanning (step) and minimum power automatically from

thickness profile and set values of maximum power and desired end thickness.

Thickness profile map is used to accommodate the power of ion source, while the

wafer is moving constant speed.

5.2.1 Trimmer operation modes

Trimming can be done with two different methods, which are labelled as normal and

over-trimming. Trimming without over-trimming (normal trimming) is done in such a

way that the etch stops just below the point, which is the lowest measured point on the

wafer as shown in Figure 16a. This is enough to make surface uniform. This normal

trimming removes the minimal amount of material from the surface. Trimmer will

change the power of the ion source to remove different amount of material from

surface, i.e., thicker points need more power compered to thinner points. For instance

in case of Figure 16a, where a large thickness gradient is present, the thinnest point

would probably need only 5 – 10 W and the thickest points would be trimmed with

300 W maximum power output. This creates a situation, where different parts of the

wafer surface are damaged and contaminated to a different degree. Also, manufacturer

has stated that maximum and minimum power ratio should be around 4 or less to

trimmer to work effectively.

To even out the contamination and damage to the surface, over-trimming procedure

was introduced. The difference between normal and over-trimming is illustrated in

Figure 16b, where excess material is removed from the surface. Every point on wafer

surface will suffer almost same amount of ion bombardment making contamination

32

and damage more uniform. This is due to fact that used power at thinnest and thickest

points are closer together.

Figure 16. An illustration of normal and over-trimming: a) Normal trimming, where

trimming is stopped just below the lowest point. Lined area is removed in trimming.

b) Over-trimming will etch away excess material (lined area). This will even the

damage and contamination on surface coming from the ion beam.

5.2.2 Trimmer repeatability

The trimming repeatability was tested using five approximately 400 nm thick annealed

TEOS oxide wafers with same trimming parameters. The TEOS was deposited using

sparse loading scheme. Also, the same HF compensating map was used with all test

wafers. Table 1 shows that all five wafers have the same thickness variation before

and after the trimming and how much is removed TEOS with trimming. Average

TEOS oxide removal and profile of the ion beam trimming can be seen in Figure 17.

Wafers were identical at the beginning; the surface profile and thicknesses of the

TEOS oxide were approximately the same. Also, minimum and maximum thickness

removal are identical across the wafers. Most importantly the average thickness

removal fluctuates under nanometer range in all tests. This means that the thickness

removal is roughly the same for all the trimmings and also the trimming profiles are

quite identical.

33

The obtained results demonstrate that the wanted profile can be created reproducibly.

All the test wafers have same thickness profile after trimming. In this test, HF

compensating map was used and the desired surface profile is thicker at right side of

the wafer compared to left side. Even when the wafers would have a different starting

thicknesses and profiles, the trimmer could produce the desired surface profile. Also,

the trimming map is unique to each wafer, which means that even though the wafers

are different, trimmer can produce same surface profile. The scheme in this test was

harder than in typical trimming, because wafers will continue to HF vapour etching.

Desired profile is not as uniform as possible, but a reversed profile of the HF vapour

etching. When there is no need to use compensating map, the trimming process is even

more uniform and repeatable.

Table 1. Repeatability of ion beam trimmer. Table shows wafers thickness variation

before and after trimming and how much oxide is removed. Thicknesses are in

nanometers and are calculated from spectroscopic reflectometer measurements before

and after each trimming.

Wafer

1

Wafer

2

Wafer

3

Wafer

4

Wafer

5

Starting thickness variation ± 19.7 ± 19.7 ± 19.8 ± 19.9 ± 19.9

After trimming thickness

variation ± 6.8 ± 6.8 ± 6.5 ± 6.4 ± 6.4

Maximum removal 70.5 72.1 71.5 70.8 70.5

Minimum removal 31.7 32.4 31.5 31.4 32.4

Average removal 47.2 48.1 47.3 47.2 47.5

34

Figure 17. Average TEOS removal profile of five wafers, which were trimmed

identically to test repeatability of trimming. Trimming profiles shows how much

oxide is etched across the wafer. The trimmed test wafers exhibited only 1 – 2 nm

difference between them and the trimming profiles were identical.

Trimming could also be done in such a way that the thickness map only for first wafer

would be measured and then all other wafers would use this thickness profile map in

trimming. Wafers thickness differences are few nanometers at begin of the trimming

and thickness profiles are identical. With this repeatability tests all wafers were

measured and every wafer had its own trimming map. Same trimming map would not

affect trimming result significantly, because there is no large difference between test

wafers. Similarly are done in literature, where thickness profile map for first wafer is

used for other wafers as a trimming map [34].

5.3 HF vapour etching

HF vapour etching is used to remove approximately 50 nm of oxide to reveal

contamination in the oxide. This section introduces HF vapour repeatability test and

how trimming affects the HF vapour etch rate. In addition, HF compensating map is

presented in more detail and how it will help to produce more uniform films after HF

vapour etching.

35

5.3.1 HF vapour etch repeatability

Etching uniformity of HF vapour etcher was tested with annealed LPCVD TEOS

oxide and thermal oxide. Thermal oxide was grown at 1050 ℃ with wet growing

step. Both oxides were etched with the same recipe and have similar etching profiles

as shown in Figure 18. HF vapour etches more from right side of the wafer, because

the machine feeds HF vapour from right side. The difference between left and right

side is 10 – 14 nm/min and 1.7 nm/min for TEOS and thermal oxide, respectively.

This is because thermal oxide quality is better resulting in six times slower etch rate

than TEOS oxide. The etch rate for thermal oxide was around 9 nm/min and for

annealed TEOS oxide it was around 50 nm/min.

Figure 18. HF vapour etch rate profiles for thermal oxide and TEOS oxide for the

same etch recipe. TEOS oxide will etch six times faster than thermal oxide due to

worse quality.

Figure 19 shows the average etching profile of the HF vapour etcher. Results show

that the etching is repeatable, but the etching profile is somewhat non-uniform. This

average etch profile, which can be seen in Figure 19 was almost identical in all etches.

This ± 5 nm variation in HF etch rates across the wafer will affect uniformity results

of ion beam trimming. It has been shown in the literature that it is possible to get 5 %

variation in HF vapour etch rate of silicon dioxide [67]. This is slightly better than our

recipe will etch, but it is not uniform enough for the trimming procedure. That is why

HF compensating map is needed to compensate the uneven HF vapour etch. HF

compensating map is introduced in Section 5.3.3.

36

Figure 19. Average HF vapour etch profile of five wafers for annealed LPCVD

TEOS oxide. Thicknesses are measured with spectroscopic reflectometer before and

after HF vapour etching, which is used to calculate the average etching profile.

5.3.2 Trimmer effects to HF vapour etching

If ion beam trimming is done before HF etching, it will affect the HF vapour etching

result. This is because, trimming is damaging the surface of the wafer and the HF will

etch more from the damaged areas. Damage depth will depend on the ion beam

trimmer power. Surface damage will increase the average etching rate of the HF

vapour etcher about 10 nm/min in normal trimming mode. If the average etch rate was

50 nm/min without trimming, with trimming it is 60 nm/min. Similarly, the HF vapour

etcher uniformity will decrease for trimmed wafers. This means that after HF vapour

etching the thickest and thinnest points will have 20 – 60 nm/min etch rate difference

depending on the trimming procedure. It is a significant difference when comparing it

to etch variation of HF etching without trimming, which is 10 – 14 nm/min. It is needed

to point out that the lowest point is in some extreme cases etched only less than 1 nm

and it is just small point on the wafer.

37

With over-trimming the average etch rate is increased to 20 nm/min compared to HF

etching without trimming. In addition, over-trimming will help with the uneven etch

rate across the wafer and decrease the etch variation to 13 – 17 nm/min. This results

in more controlled etching compared to normal trimmed wafers, because the etching

profile is more consistent with a smaller etch rate variation.

AMSystems ion beam trimmer uses 90 degrees bombardment and this will roughen

the surface. A recent study from Debasree Chowdhury et al shows that a low energy

argon ion sputtering will leave the anisotropic, ripple like nano patterns on the surface

[19]. When surface is rougher, there is more area for the HF vapour to diffuse and etch

the oxide. This can explain the increased etch rate of the HF vapour etcher. Debasree

Chowdhury et al study also show that with smaller ion bombardment angles (angles

up to 60 degrees) can smoothen the sputtered surface [19].

5.3.3 HF compensating map

Following section presents the HF compensating map and its significance. HF vapour

etcher etches with different rates compared to the right and the left side of the wafer

and it affects trimming procedure’s thickness variation result. Without HF

compensating map, the surface of the oxide is uniform after trimming. HF

compensating map for trimmer is meant to be the opposite polarity to the HF etching

profile. There is a limit what kind of uniformity can be achieved with trimming when

the HF compensating map is not used. The effect of HF compensating map was studied

using 400 nm thick annealed TEOS oxide wafers. Both wafers were trimmed with

same trimming parameters, but HF compensating map was used only with the other

wafer.

Table 2 illustrates the difference of TEOS oxide trimming and HF vapour etching and

the effect of HF compensating map. Initial oxide thickness profile and variation were

similar with both test wafers. Without HF compensating map, thickness variation of

± 8.1 nm was achieved after trimming. With the compensating map in use, thickness

variation after trimming was ± 6.4 nm. Bigger difference can be seen after HF etching.

The thickness variation is reduced from ± 6.4 nm to ± 4.3 nm, which is a clear

38

improvement to the case when no compensating map was used. Without compensating

map the thickness variation will get worse after HF vapour etching from ± 8.1 nm to

± 11.7 nm.

Table 2. TEOS oxide thickness variation when trimming with and without HF

compensating map. Results are measured with spectroscopic reflectometer before

trimming, after trimming and after HF vapour etching.

Without HF

compensating

map

With HF

compensating

map

TEOS thickness variation (nm) ± 18.5 ± 19.9

After trimming thickness variation (nm) ± 8.1 ± 6.4

After HF etching thickness variation (nm) ± 11.7 ± 4.3

Results in Table 2 clearly show that trimmer and HF vapour etcher together make the

surface more uniform, whereas the uniformity for the wafer without compensating map

decreases. It is noteworthy to observe that the thickness uniformity after trimming is

worse for the wafer without the compensating map. This can be explained due to the

large thickness gradients at wafer edges that cannot be effectively smoothened in one

trimming step.

5.3.4 The effect of over-trimming to HF vapour etching

In Section 5.2.1 two types of trimmer operation modes were introduced. We observed

that the HF vapour etcher was etching unevenly depending on the used trimming mode.

This happened even when trimming was done with the HF compensating map. To

further investigate this, we used 400 nm thick annealed TEOS oxides test wafers. Both

wafers were trimmed two times and cleaned with HF vapour. In the first trimming, the

wafers were smoothened more uniform. In the second trimming, the HF compensating

map was applied. The over-trimmed wafer was etched 5 nm and 20 nm more in the

first and second trimming, respectively in comparison to the reference, normal

trimmed wafer.

39

Figure 20 shows the wafer thickness profiles after trimming and HF vapour etching

without and with over-trimming. The starting situation is identical for both wafers as

can be seen in Table 3. The TEOS oxide thickness variation is approximately ± 21.6

nm and the thickness profiles are roughly the same. In addition after the first trimming,

the thickness variation and the profile are identical for both wafers. However after the

second trimming, differences start to emerge. The wafer that is etched without over-

trimming has bigger thickness variation and the thickness profile is significantly worse

than for the over-trimmed wafer. After HF vapour etching, the normally trimmed wafer

has very high point on the right side of wafer’s flat as seen in Figure 20a. This will

worsen the uniformity to the same level as in the beginning. On the other hand, wafer

with over-trimming has much more uniform thickness profile and the thickness

variation is under ± 4.5 nm compared to ± 20.7 nm of normally trimmed. Similar tests

were done multiple times, to make sure that the observed effect is real.

Figure 20. Wafer thickness profiles of TEOS oxide without and with over-trimming

after HF vapour etching. HF vapour etch quality will be dramatically worsened

without over-trimming compared to over-trimmed wafer. Without over-trimming

uniformity is five times worse and thickness control is poor, because HF will

randomly etch the wafer. Similar tests were done multiple times, to make sure that

the observed effect is real. The wafers are trimmed two times and cleaned with HF

vapour. With first trimming the wafers are trimmed more uniform and with second

trimming the wafers are trimmed using HF compensating map.

40

Table 3. Comparison of the thickness variation with and without over-trimming.

Wafers are measured before trimming, after trimmings and after HF vapour etching.

Without over-

trimming

With over-

trimming

TEOS thickness variation (nm) ± 21.6 ± 21.6

After 1st trimming thickness variation (nm) ± 6.8 ± 6.6

After 2nd trimming thickness variation (nm) ± 8.3 ± 5.6

After HF etching thickness variation (nm) ± 20.7 ± 4.4

Uniformity at beginning (%) 5.76 5.75

Uniformity at end (%) 7.57 1.77

Material removed (nm) 102 126

As we can see from Figure 20a, the highest point (red area) in normally trimmed wafer

is the same point that was trimmed least during the second trimming. Comparing the

thicknesses at the same point, reveal that this points is trimmed just 3 – 6 nm compared

to the average etch depth of 17 nm during the second trimming. If both trimmings are

taken in account the etching amount is same in other points. The same HF vapour

decrease in etch rate was seen when wafers were trimmed only once. The points that

experience least trimming, will etch slower in HF vapour etcher. This HF etch rate

difference was nearly two times faster compared to these untrimmed points on the

wafer.

The interplay between the trimmer and HF vapour etcher is more prominent with one

trimming procedure than two trimmings. The effect of damage was pronounced when

wafer was trimmed three times and then etched with HF vapour. After trimming and

HF vapour etching ± 5.5 nm thickness variation was obtained. As seen earlier, surface

damage will enhance the etching rates. First trimming does not have a major effect to

the HF etch rates, because the second trimming will determine the final damage to the

surface. Over-trimming in the last trimming step has shown to be useful to even the

HF vapour etch rate and enable better uniformity after HF vapour etching, as can be

seen from Figure 20b.

41

5.4 Contamination analysis

AMSystems ion beam trimmer has known a problem of contamination of Al and Fe

that is coming from the machine itself. Aluminum contamination comes from chamber

walls and it will be sputtered to the oxide. Iron contamination is believed to come from

ion sources magnets. Here we present results that the contamination can be effectively

removed with a simple HF etch and RCA wash. The contamination from trimming can

be removed by using HF vapour etching and RCA washing. After trimming,

approximately 50 nm of TEOS oxide is etched with HF vapour etcher and washed with

RCA. The removal of contamination will enable further processing of trimmed wafers

in IC-clean processing equipment.

5.4.1 Contamination depth analysis

Contamination depth analysis were done with SIMS and test wafers were 500 nm

annealed LPCVD TEOS oxide wafers. Contamination depth test included references,

which were compared to trimmed wafers to make sure that they can be cleaned with

HF vapour etching and RCA washes. Three different wafers were tested; annealed

TEOS oxide wafer, annealed and trimmed TEOS oxide wafer, annealed and trimmed

TEOS oxide wafer, which was cleaned with HF vapour etcher and RCA washed.

Cleaning run for annealing oven was used for all TEOS oxide wafers to make sure that

no contamination would be coming from the annealing oven. Tests were done with

SIMS to get most accurate depth profile of the contamination concentration within the

oxide.

Figure 21 shows iron contamination depth profiles for reference (yellow line), trimmed

wafer (red line) and cleaned wafer (green line). In the reference, the surface

concentration of Fe was 3.14 × 1017 atom/cm3 and implantation dose was 1.16 × 1011

atom/cm2 through the whole oxide. As can be seen in Figure 21 and Table 4, the iron

content is significantly higher for trimmed wafer. In the trimming reference, the

surface concentration of Fe was 1.47 × 1020 atom/cm3 and implantation dose was

8.67 × 1013 atom/cm2 through the whole oxide. In addition, cleaning procedure brings

iron contamination levels back to the clean reference wafer level. In the cleaned wafer,

42

the Fe surface concentration was 1.26 × 1017 atom/cm3 and implantation dose was is

4.25 × 1010 atom/cm2 through the whole oxide.

Figure 21. SIMS iron contamination analysis. When annealed TEOS oxide is

trimmed, it will be contaminated significantly with iron. HF vapour etching and

RCA cleaned wafers contamination level back to level of annealed TEOS oxide.

Figure 22 shows aluminium contamination depth profiles for reference (yellow line),

trimmed wafer (red line) and cleaned wafer (green line). The Al contamination trend

exhibits similar kind of trend as for Fe. In the annealed TEOS reference, the surface

concentration of Al was 1.19 × 1018 atom/cm3 and implantation dose was 6.83 × 1011

atom/cm2 through the whole oxide. As can be seen in Figure 22 and Table 4, the

aluminium content is significantly higher for trimmed wafer. In the trimming

reference, the surface concentration of Al was 9.73 × 1020 atom/cm3 and implantation

dose was 8.02 × 1014 atom/cm2 through the whole oxide. In addition, cleaning

procedure brings aluminium contamination levels back to clean reference wafer level.

In the cleaned reference, the Al surface concentration was 1.28 × 1018 atom/cm3 and

implantation dose was is 4.41 × 1011 atom/cm2 through the whole oxide.

1E+14

1E+15

1E+16

1E+17

1E+18

1E+19

1E+20

0 100 200 300 400 500

Co

nce

ntr

atio

n (

ato

ms/

cm3)

Depth (nm)

Annealed TEOS wafer (Reference)

Annealed TEOS + trimming

Annealed TEOS + trimming + cleaning

43

Figure 22. SIMS aluminium contamination analysis. When annealed TEOS oxide is

trimmed, it will be contaminated significantly with aluminium. HF vapour etching

and RCA cleaned wafers contamination level back to level of annealed TEOS oxide.

Table 4. Implantation dose through the 500 nm thick oxide for iron and aluminium

with clean reference wafer (annealed TEOS), trimmed wafer (Annealed TEOS +

trimming) and cleaned wafer (Annealed TEOS + trimming + cleaning). Trimming will

significantly increase contamination on oxide but cleaning steps will reduce it back to

clean reference level.

Iron implantation dose

(atom/cm2 )

Aluminium implantation dose

(atom/cm2 )

Annealed TEOS 1.16 × 1011 6.83 × 1011

Annealed TEOS +

trimming 8.67 × 1013 8.02 × 1014

Annealed TEOS +

trimming + cleaning 4.25 × 1010 4.41 × 1011

SIMS result show that HF vapour etching and RCA washing are very effective to

cleaning trimmed wafers from iron and aluminium contamination. After cleaning, the

trimmed wafers are even cleaner than annealed LPCVD TEOS reference. During the

trimming Fe and Al contaminants are implanted around 100 nm depth. Most

significant contamination level is between 0 – 50 nm. In the HF vapour etching oxide

is removed 50 – 60 nm from surface. It is worth to not that HF vapour will not remove

1E+14

1E+15

1E+16

1E+17

1E+18

1E+19

1E+20

1E+21

0 100 200 300 400 500

Co

nce

ntr

atio

n (

ato

ms/

cm3)

Depth (nm)

Annealed TEOS wafer (Reference)

Annealed TEOS + trimming

Annealed TEOS + trimming + cleaning

44

the contamination, but leave it to surface. Hence, RCA wash is required to remove

metals from surface and this was tested in Section 5.4.2.

Figure 23 illustrates how the amount of contamination varies at different trimming

depths. With normal trimming (Figure 23a) damage and contamination will be more

remarkable at points, which need more trimming. More power is used to etch these

points, because the trimmer moves the wafer at constant speed and only changes output

power. Earlier simulations done at VTT show that for 240 W and 5.8 W power Fe

contaminants will reach depths of 30 nm and 12 nm, respectively. Similarly,

aluminium penetrates deeper to 50 nm and 17 nm with 240 W and 5.8 W power,

respectively. Thus in simulations, the contaminants penetrate more than two times

deeper between the higher and lower ion source power.

Figure 23b schematically illustrates how contamination spreads uniformly with over-

trimming. This is caused by the fact that in over-trimming the minimum and maximum

power outputs are closer together. We did observe that when the ion source minimum

and maximum power values are in same magnitude, surface damage is more uniform

and the HF vapour etcher etches more uniformly. Also, last trimming step has the most

effect in the HF etch quality and determines the overall surface damage, because the

damage from earlier trimmings will be trimmed away with the last trimming. This is

why the last trimming step has the most effect in the HF etching quality.

45

Figure 23. Contamination and surface damage depth has an effect in the HF vapour

etch quality. With normal trimming difference between the minimum and maximum

powers is large and results in damage and contamination differences across the

wafer. More power is used to trim thicker points and at the same time the surface

damage reaches deeper. Thinner points are etched with lower power and the

contamination and damage is much smaller at these points. Over-trimming will trim

excess material from the wafer surface and same time the ion source minimum and

maximum powers are closer together and the damage depth is more uniform across

the wafer.

5.4.2 Surface contamination analysis

To prove our hypothesis that HF vapour etching will etch oxide away and reveal the

metal contaminants on surface, WSS ICP – MS was used to analyse the cleaning effect.

WSS ICP – MS was used to detect surface contamination concentration level. WSS

ICP – MS data is listed in Table 5, where can be seen that aluminium has highest

contamination concentration. Also, iron, chromium, calcium, sodium and copper show

elevated levels of contamination. After the RCA wash almost all metal contaminants

are removed below the ICP – MS detection limit. Aluminium concentration is again

highest, but at the starting point was also the highest. ICP – MS analysis further

elaborates that the metal contaminants revealed by the HF vapour etcher are effectively

removed with RCA wash.

46

Table 5. WSS ICP – MS results of surface contamination. It can be seen that HF vapour

etching will reveal the metal contamination on the surface of the oxide, which can be

removed with RCA wash. The metal content on the surface has a large difference

before and after RCA wash.

Surface concentration (atoms/cm2)

Method

Detection Limit Annealed TEOS +

trimming + HF

Annealed TEOS +

trimming + HF +

RCA

Aluminium 6.00E+09 2.70E+15 1.90E+11

Antimony 4.00E+07 5.50E+08 <DL

Arsenic 1.00E+10 1.00E+10 <DL

Barium 3.00E+07 9.00E+11 <DL

Bismuth 2.00E+07 7.30E+08 <DL

Boron 1.00E+11 4.10E+11 1.10E+12

Cadmium 6.00E+07 2.60E+08 <DL

Calcium 6.00E+09 1.00E+13 <DL

Chromium 1.00E+09 3.30E+12 3.20E+09

Cobalt 1.00E+09 8.00E+09 <DL

Copper 4.00E+08 3.70E+12 <DL

Gallium 6.00E+07 1.80E+11 <DL

Germanium 2.00E+08 4.10E+08 <DL

Iron 2.00E+09 7.80E+13 9.40E+09

Lead 6.00E+07 2.20E+10 <DL

Lithium 1.00E+09 7.50E+11 <DL

Magnesium 2.00E+09 8.30E+13 2.20E+09

Manganese 6.00E+08 3.40E+12 <DL

Molybdenum 4.00E+07 4.40E+10 1.60E+08

Nickel 1.00E+09 2.50E+11 <DL

Potassium 4.00E+09 1.50E+13 <DL

Sodium 4.00E+09 2.20E+14 2.20E+10

Strontium 2.00E+08 1.20E+12 <DL

Tin 6.00E+08 1.10E+09 <DL

Titanium 1.00E+09 3.40E+11 1.60E+09

Tungsten 2.00E+07 9.50E+10 2.10E+07

Vanadium 2.00E+08 3.00E+11 <DL

Zinc 1.00E+09 3.60E+10 <DL

Zirconium 2.00E+08 1.50E+11 <DL

47

Out other concern arise whether the machines would contaminate wafers. This was

tested with blank silicon wafers that were driven in and out of ion beam trimmer and

HF vapour etcher face down. These wafers were measured with VPD ICP – MS and

compered to prime wafer. From the results in Table 6, it can be seen that no significant

contamination comes from wafer handling in the trimmer or the HF vapour etcher.

Boron concentration is high, because wafers are boron doped. Aluminium

concentration is increased, but not significantly. Aluminium will come from the HF

vapour etcher chucks and from the ion beam trimmer’s aluminium carrier rings.

Table 6. VPD ICP – MS results of the wafer handling induced contamination. As a

reference unprocessed clean wafer was compared to wafers, which are driven in and

out face down of the ion beam trimmer and the HF vapour etcher chambers. No

significant contamination from wafer handling inside the machines could be detected.

Surface concentration (atoms/cm2)

Method

Detection Limit

Clean

wafer

Trimmer

in/out

HF

in/out

Aluminium 1.27E+09 2.78E+09 2.71E+10 2.58E+10

Antimony 1.41E+08 <DL <DL 2.17E+08

Beryllium 1.90E+09 1.89E+09 2.28E+09 <DL

Boron 3.17E+09 8.63E+11 8.93E+11 8.75E+11

Calcium 8.54E+08 2.47E+09 1.97E+09 6.77E+09

Copper 2.69E+08 4.41E+09 3.08E+09 2.76E+09

Iron 6.13E+08 1.28E+09 1.60E+09 1.54E+09

Lead 8.26E+07 2.31E+08 2.32E+08 2.40E+08

Lithium 2.47E+09 1.62E+10 2.87E+10 1.48E+10

Nickel 5.83E+08 <DL <DL 5.64E+08

Potassium 8.75E+08 <DL <DL 9.31E+08

Sodium 1.49E+09 1.49E+09 2.24E+09 4.03E+09

Tin 1.44E+08 4.60E+08 5.20E+08 5.85E+08

Zinc 2.62E+08 <DL <DL 7.59E+08

48

5.5 Trimming and HF vapour etching repeatability

The repeatability of the trimming and HF vapour etching was tested with 400 nm

annealed LPCVD TEOS oxide wafers. All five wafers were etched with HF

compensating map and same etch parameters. One over-trimming etch was found to

be enough to make oxide surface uniform, as can be seen in Table 7. Four first test

were identical and oxide removal difference was in few nanometers between the

wafers, but last wafer was etched 15 nm less than other wafers in HF vapour. This

worsened the uniformity compared to other wafers, but it is still better than at the

beginning. That is why the oxide removal is about 10 nm less than the others for the

test wafer 5. After trimming the uniformity was around 2 % for all wafers. HF vapour

etching was the only step, which differentiated these test wafers. Uniformity was

around 1.5 % and standard deviation around 2 for wafers 1 – 4. Last test wafer had

uniformity of 3 % and standard deviation of 3.9. This can be explained by trimming

will effect HF vapour etching and small difference in trimming damage can cause large

difference in uniformity.

Table 7. Trimming and HF vapour etching repeatability test. Uniformity of annealed

TEOS oxide was same after deposition. Same trimming parameters and HF

compensating map were used. Four first test were identical and oxide removal

difference was in few nanometers between the wafers, but last wafer was etched 15

nm less than other wafers in HF vapour. That is why oxide removal is about 15 nm

less than other wafers. Wafer 5 had worse uniformity compared to the other wafers,

but still all the wafers uniformities improved during the repeatability test. Wafer

1

Wafer

2

Wafer

3

Wafer

4

Wafer

5

Annealed TEOS oxide

(Uniformity) 5.20 % 5.18 % 5.20 % 5.24 % 5.22 %

After trimming (Uniformity) 2.06 % 2.04 % 1.96 % 1.91 % 1.92 %

After HF vapour etching

(Uniformity) 1.37 % 1.67 % 1.45 % 1.59 % 3.03 %

Standard deviation after HF

vapour etch 1.46 2.24 1.96 2.09 3.94

Average removed oxide (nm) 107.4 107.9 108.6 106.9 93.0

One step trimming is always harder with HF compensating map, because the surface

needs to be uniform enough and at the same time produce HF compensating profile to

surface. Two trimmings scheme is easier, because first trimming will trim surface

49

uniform and second trimming will create the HF compensating profile to surface on

the oxide.

5.6 Experiment for thick oxide

In this final study, trimming of 2 µm oxide was investigated. The result from this study

are important as the oxide thickness lies in the same range as in actual MEMS FPI

device. It was found that one trimming was not enough to make surface uniform,

because the HF vapour etch did not produce enough uniform results. Mishin et. al.

have shown that a two step trimming process is significantly superior. In their study,

they have stated that a large thickness gradient will cause problems when trimming is

performed only once. [28] Therefore, thicker oxides will need two trimmings, because

the trimmer cannot trim as accurately when the thickness variation is larger causing

large anomalies. This is why a two step trimming process is needed for thicker oxides.

In addition, when trimming thicker oxides another compensating map is needed. This

is due to that AMSystem trimmer is designed to improve smaller thickness gradients.

Wafer middle part is thinner than the edge of the wafer and this can decrease the

uniformity improvement. We discovered from multiple trimmings that the trimmer is

unable to sufficiently etch the edges resulting in poor thickness uniformity. This is

illustrated in Figure 24a and b, where we can see that after trimming the edge is still

high. Surface profile flips around so that middle is thinner before trimming and after

it is left as the thickest point as Figure 24b illustrates. Figure 24c illustrates thickness

profile after trimming with edge compensating map and uniformity is noticeably better

than the wafer, which is trimmed without edge compensating map.

This trimming behaviour can be decreased with introduction of edge compensation

map, which will dampen the differences between the middle and edge. The edge

compensating map is created in such a way that the edges and the middle are trimmed

more to achieve better trimming results. This means that to achieve the best uniformity

for thicker oxides we need to use two types of compensating maps; edge and HF

compensating maps in the first and the second trimming, respectively.

50

Figure 24. Trimming characteristics for 2 µm oxides with large thickness variation

and how edge compensating map improves trimming result. a) Annealed TEOS

oxide thickness profile before trimming, b) thickness profile after trimming without

edge compensating map, c) thickness profile after trimming with edge compensating

map. After trimming thickness profile can flip when thickness gradients are large.

AMSsystems trimmer is designed to trim wafers with small thickness gradient and

this is why thickness profile can flip during the trimming.

Hence, two step trimming was used for thicker TEOS oxides. Results show that first

trimming improves thickness variation to such level that second trimming can produce

HF compensating profile to oxide surface. With two compensating maps, uniformity

can be improved from 2.49 % to 0.29 %. Uniformity improvement after every

trimming step can be seen in Table 8 and Figure 25 illustrating the thickness variation

before and after trimming procedure. The initial large thickness variation of the

LPCVD TEOS oxide can be improved significantly with two trimmings, even with HF

vapour etching cleaning step.

Table 8. Example of thick TEOS oxide uniformity, average thickness and standard

derivation after every trimming procedure’s step.

Annealed

TEOS oxide

After 1st

trimming

After 2nd

trimming

After HF

vapour etching

Uniformity (%) 2.49 0.63 0.44 0.29

Average thickness (nm) 2183 2011 1974 1907

Standard deviation 31.63 5.80 4.17 2.86

51

Figure 25. Thickness variation difference between non-trimmed and trimmed wafer.

Before trimming thickness variation is large (over 100 nm). After trimmings and HF

vapour etching the thickness variation drops significantly (around 10 nm).

52

6 Conclusions and future interests

Many microelectronic devices need good control over film uniformity and thickness

to achieve good yield and economical feasibility [1]. Ion beam trimmer’s primary aim

is to improve film uniformity and trim the film to desired thickness. Trimming has

been used extensively to improve fabrication processes with trimming of bulk acoustic

wave (BAW) filters [16], [34] and surface acoustic wave (SAW) filters [16], [34]. No

previous studies has been found, where ion beam trimming would have been utilized

in the manufacturing process of MEMS FPI. There is a need for thickness variation

control of MEMS FPI as in the case with BAW or SAW devices.

The goal of this thesis was to find out, whether the trimming would be beneficial to

improve uniformity of sacrificial oxide in MEMS FPI processing. During this thesis,

the aim was to find out what needs to be taken into account in the trimming process.

The cleaning step after trimming with HF vapour etching and RCA washing needs to

be planned so that they does not worsen the uniformity of the film. Additionally,

another aim was to remove contaminants from the trimmed wafers to levels that they

can continue fabrication in the IC clean processing line.

The metal contaminants originate from the ion source of the trimmer and from the

aperture plate of the machine. This is a big problem especially when wafers need to

continue to other fabrication steps with IC-clean machines. The cleaning of the wafers

was done with HF vapour etcher and RCA wash. The initial hypothesis how the HF

vapour would behave with contaminants was shown to be correct. The ICP – MS result

showed that HF vapour will remove the most contaminated oxide layer and reveal and

cluster the metal contaminants on the surface. RCA wash will then remove these

revealed metals from the surface. SIMS analysis showed that the contamination levels

will drop after cleaning to the same levels as IC-clean LPCVD TEOS wafer. This

means that contamination can be effectively removed from wafers and in principle

could enable further processing of the wafers with IC-clean machines. If ion beam

trimmer would not contaminate the wafers trimming of FPI sacrificial oxide would be

much easier. Ion beam trimmer chamber and ion source should be designed in such

53

way that they do not contaminate trimmed wafers. For example, chamber walls should

be other material than aluminium.

As demonstrated in this thesis, trimming procedure showed promising signs to be a

valuable fabrication method for FPI and also for other MEMS devices. The uniformity

of thicker TEOS oxide was improved from 2.49 % to 0.29 % and the standard deviation

improved from 31.6 to 2.86. This means that there is no need to get more uniform

deposition of a thin film and precise thickness control can be achieved with ion beam

trimmer. However, process will need excess of material for trimming and this needs

to be taken into account when designing a trimming fabrication step. But keeping that

in mind, desired thickness can be achieved and at the same time trimming can improve

the uniformity of the film.

The trimming procedure that includes the cleaning, is a novel approach to trimming.

Normally, there is no need to clean the wafers after trimming, because other machines

do not contaminate the wafers or there is no need of IC – clean process. Naturally, it

is easier to implement trimming when no cleaning steps are required, because no

compensating map is used. Thus, it is possible to achieve better trimming results and

it is much easier to achieve good uniformity levels. But even with cleaning steps, the

results in this thesis were able to get very good uniformity and wafer thickness control.

Trimming with HF compensating map is a significant contributor in achieving good

uniformity results after HF vapour etching. Other processes which need oxide metal

contaminant cleaning can benefit from HF vapour etching and RCA washing cleaning

steps.

There was a big problem with HF vapour etching due to the uneven etch profile of the

trimmed wafers. This is due to the fact that the trimmer will bombard surface with ions

and damage it. Damage across the wafer is not uniform, because thicker points on

wafer suffer larger dose of ion bombardment compared to thinnest points on wafer.

Non-uniform surface damage affects the HF vapour etching and that is why over-

trimming was introduced. Over-trimming evens the damage on the surface and also

stabilizes the HF vapour etch rate. Sometimes uneven HF vapour etch rates occur after

54

trimming. This happens rarely, but exact cause remains unknown what causes the

uneven etch rate, although over-trimming was used. One explanation is that sometimes

HF vapour does not diffuse correctly or alternatively LPCVD TEOS oxides quality

can differ between the wafers and cause lower etch rate compared to others. Also, it

can be so that ion beam trimmer will damage the surface differently and cause different

HF etch rate. This needs more investigation to say what causes occasional changes of

HF vapour etch rate. In addition, HF vapour etching seems to have large etch rate

differences and more uniform diffusion of vapour would enable better etch uniformity.

Other etch machines have dedicated shower heads, which will diffuse vapour/gas

evenly to wafer surface and improve etch uniformity.

Uniformity improvement from 2.49 % to 0.29 % level will improve yield of the MEMS

FPI significantly. The results presented in this thesis will provide important knowledge

of the trimming and how it could be utilized for MEMS FPI development. Next logical

step is to test trimming with actual FPI test structures. Trimming would bring

important improvement to MEMS FPI economic feasibility as the yield improves. If

the uniformity improvement is similar to the results presented in this thesis, trimming

would be implemented into the MEMS FPI fabrication process.

55

Reference

[1] M. Nestler, M. Demmler, T. Dunger, D. Rost, and M. Zeuner, “Yield

improvement by localized trimming in semiconductor and MEMS

manufacturing,” IEEE - 2011 Semicond. Conf. Dresden Technol. Des. Packag.

Simul. Test, SCD 2011 - Int. Conf. Work. Table-Top Exhib., vol. 49, no. 0, pp.

1–4, 2011.

[2] J. W. Judy, “Microelectromechanical systems (MEMS): fabrication, design and

applications,” IOP Publ. Ltd, vol. 10, pp. 1115–1134, 2001.

[3] H. Fujita, “Microactuators and micromachines,” Proc. IEEE, vol. 86, no. 8, pp.

1721–1732, 1998.

[4] K. B. Lee, Principles of Microelectromechanical Systems. John Wiley & Sons,

2011.

[5] Yole Développement, “MEMS for Cell Phones & Tablets to 2017,” 2017.

[6] R. F. Wolffenbuttel, “MEMS-based optical mini- and microspectrometers for

the visible and infrared spectral range,” J. Micromechanics Microengineering,

vol. 15, no. 7, pp. 145–152, 2005.

[7] S. Franssila, Introduction to Microfabrication, 2nd ed. John Wiley & Sons,

2010.

[8] Yole Développement, E. Mounier, and J. Eloy, “Status of the MEMS industry

2018,” Eur. Semicond., vol. 26, no. July, p. 31, 2018.

[9] M. E. Motamedi, MOEMS: Micro-opto-electro-mechanical Systems.

Bellingham: SPIE press, 2005.

[10] M. Tuohiniemi, “Silicon-based surface micromachined interferometers for

infrared wavelengths,” Aalto University School of Chemical Technology, 2015.

[11] J. M. Vaughan, The Fabry-Perot Interferometer: History, Theory, Practice and

Applications, 1st ed. CRC press, Taylor and Francis Group, 1989.

56

[12] C. F. R. Mateus, M. C. Y. Huang, and C. J. Chang-Hasnain, “Micromechanical

tunable optical filters: General design rules for wavelengths from near-IR up to

10 μm,” Sensors Actuators, A Phys., vol. 119, no. 1, pp. 57–62, 2005.

[13] D. Landgrebe, C. Haake, T. Höpfner, S. Beutel, B. Hitzmann, T. Scheper, M.

Rhiel, and K. F. Reardon, “On-line infrared spectroscopy for bioprocess

monitoring,” Appl. Microbiol. Biotechnol., vol. 88, no. 1, pp. 11–22, 2010.

[14] C. K. Liu, K. T. Cheng, and A. Y. G. Fuh, “Designs of high color purity RGB

color filter for liquid crystal displays applications using Fabry-Perot etalons,”

IEEE/OSA J. Disp. Technol., vol. 8, no. 3, pp. 174–178, 2012.

[15] N. Neittaanmäki-Perttu, M. Grönroos, T. Tani, I. Pölönen, A. Ranki, O. Saksela,

and E. Snellman, “Detecting field cancerization using a hyperspectral imaging

system,” Lasers Surg. Med., vol. 45, no. 7, pp. 410–417, 2013.

[16] PR Newswire, “Ion Beam Technology Market Filter, Surface Trimming of

SAW Filter, Thickness and Pole Width Correction of Thin Film Recording

Head, and Coating of Dielectric Film - Global Industry Analysis, Trend, Size,

Share and Forecast 2017 - 2025,” 2017.

[17] C. A. Volkert, A. M. Minor, D. P. Adams, M. J. Aziz, and Y. Fu, “Focused ion

beam micromachining,” MRS Bull., vol. 32, pp. 389–399, 2007.

[18] A. Peltonen, H. Q. Nguyen, J. T. Muhonen, and J. P. Pekola, “Milling a silicon

nitride membrane by focused ion beam,” J. Vac. Sci. Technol. B, Nanotechnol.

Microelectron. Mater. Process. Meas. Phenom., vol. 34, no. 6, pp. 1–6, 2016.

[19] D. Chowdhury and D. Ghose, “Fabrication of nanoscale topographies on

Ge(100) surface by low energy Ar ion sputtering,” Nucl. Instruments Methods

Phys. Res. Sect. B Beam Interact. with Mater. Atoms, vol. 409, pp. 197–201,

2017.

[20] F. Frost, R. Fechner, B. Ziberi, J. Völlner, D. Flamm, and A. Schindler, “Large

area smoothing of surfaces by ion bombardment: Fundamentals and

applications,” J. Phys. Condens. Matter, vol. 21, no. 22, 2009.

57

[21] F. Frost, R. Fechner, B. Ziberi, D. Flamm, and A. Schindler, “Large area

smoothing of optical surfaces by low-energy ion beams,” Thin Solid Films, vol.

459, no. 1–2, pp. 100–105, 2004.

[22] T. Arnold, G. Böhm, R. Fechner, J. Meister, A. Nickel, F. Frost, T. Hänsel, and

A. Schindler, “Ultra-precision surface finishing by ion beam and plasma jet

techniques-status and outlook,” Nucl. Instruments Methods Phys. Res. Sect. A

Accel. Spectrometers, Detect. Assoc. Equip., vol. 616, no. 2–3, pp. 147–156,

2010.

[23] Q. Wang, S. Kishimoto, Y. Tanaka, and K. Naito, “Fabrication of nanoscale

speckle using broad ion beam milling on polymers for deformation analysis,”

Theor. Appl. Mech. Lett., vol. 6, no. 4, pp. 157–161, 2016.

[24] V. V. Zhurin, H. R. Kaufman, and R. S. Robinson, “Physics of closed drift

thrusters,” Plasma Sources Sci. Technol., vol. 8, no. 1, pp. 1–20, 1999.

[25] W. K. Choi, “Superhydrophilic polymer surface modification by low energy

reactive ion beam irradiation using a closed electron Hall drift ion source,” Surf.

Coatings Technol., vol. 201, no. 19–20 SPEC. ISS., pp. 8099–8104, 2007.

[26] AMSystems Inc, “Trimming Process with the AMSystems 215 Trimming

module,” pp. 1–21, 2015.

[27] C. C. W. Ruppel, “Acoustic Wave Filter Technology-A Review,” IEEE Trans.

Ultrason. Ferroelectr. Freq. Control, vol. 64, no. 9, pp. 1390–1400, 2017.

[28] S. Mishin, Y. Oshmyansky, and F. Bi, “Practical issues with ion beam milling

in acoustic wave resonator technologies,” IC NanoTech, pp. 1–8, 2010.

[29] H. R. Cuomo, Jerome J. Rossnagel, Stephen M. Kaufman, Handbook of Ion

Beam Processing Technology - Principles, Deposition, Film Modification and

Synthesis, Reprint. Westwood: Noyes publications, 1989.

[30] D. A. Ramappa and W. B. Henley, “Diffusion of Iron in Silicon Dioxide,” J.

Electrochem. Soc., vol. 146, no. 10, pp. 3773–3777, 1999.

58

[31] O. Krause, H. Ryssel, and P. Pichler, “Determination of aluminum diffusion

parameters in silicon,” J. Appl. Phys., vol. 91, no. 9, pp. 5645–5649, 2002.

[32] A. De Luca, A. Portavoce, M. Texier, N. Burle, and B. Pichaud, “Dynamic

segregation of metallic impurities at SiO2/Si interfaces,” J. Phys. Conf. Ser.,

vol. 471, no. 1, 2013.

[33] A. Rosenkranz, “Ion beam sources for surface modification,” Meyer Burg. ST

MicroSystems, pp. 1–16, 2015.

[34] R. Aigner, “SAW and BAW technologies for RF filter applications: a review

ofthe relative strengths and weaknesses,” Proc. - IEEE Ultrason. Symp., pp.

582–589, 2008.

[35] P. Varshney, B. S. Panwar, B. Rétornaz, P. Rathore, S. Ballandras, B. François,

G. Martin, and J.-M. Friedt, “Theoretical and experimental analysis of high Q

SAW resonator transient response in a wireless sensor interrogation

application,” IEEE Int. Freq. Control Symp. Proc., pp. 1–6, 2012.

[36] P. V. Wright, “A review of SAW resonator filter technology,” IEEE 1992

Ultrason. Symp. Proc., no. 1, pp. 29–38, 1992.

[37] M. F. Elkordy, M. M. Elsherbini, and A. M. Gomaa, “Modeling and simulation

of unapodized surface acoustic wave filter,” African J. Eng. Res., vol. 1, no. 1,

pp. 1–5, 2013.

[38] S. Mishin, M. Gutkin, A. Bizyukov, and V. Sleptsov, “Improving frequency

control of temperature compensated surface acoustic wave devices,” 2013 Jt.

Eur. Freq. Time Forum Int. Freq. Control Symp. EFTF/IFC 2013, pp. 111–113,

2013.

[39] S. Mahon and R. Aigner, “Bulk Acoustic Wave Devices – Why, How, and

Where They are Going (Film Bulk Acoustic Resonator),” Cs Mantech Conf.,

pp. 15–18, 2007.

59

[40] H. Khan, “Fabry-Pérot Interferometer; construction, calibration and

development,” University of Jyväskylä, 2015.

[41] P. Hariharan, Basics of Interferometry, 2nd ed. Elsevier Inc., 2007.

[42] D. Sadot and E. Boimovich, “Tunable optical filters for dense WDM networks,”

IEEE Commun. Mag., vol. 36, pp. 50–55, 1998.

[43] F. Pérennès, P. C. Beard, and T. N. Mills, “Analysis of a low-finesse Fabry–

Perot sensing interferometer illuminated by a multimode optical fiber,” Appl.

Opt., vol. 38, no. 34, pp. 7026–7034, 1999.

[44] S. D. Smith and O. S. Heavens, “A tunable infra-red interference filter,” J. Sci.

Instrum., vol. 34, no. 12, pp. 492–496, 1957.

[45] M. Blomberg, M. Orpana, and A. Lehto, “Electrically tunable Fabry-Perot

interferometer produced by surface micromechanical techniques for use in

optical material analysis,” US Pat. 5561523, 1996.

[46] J. Kuhn, N. Bobrowski, P. Lübcke, L. Vogel, and U. Platt, “A Fabry-Perot

interferometer-based camera for two-dimensional mapping of SO2

distributions,” Atmos. Meas. Tech., vol. 7, no. 11, pp. 3705–3715, 2014.

[47] M. Ebermann, N. Neumann, K. Hiller, M. Seifert, M. Meinig, and S. Kurth,

“Tunable MEMS Fabry-Pérot filters for infrared microspectrometers: a

review,” Proc. SPIE, vol. 9760, pp. 1–20, 2016.

[48] E. Garmire, “Theory of quarter-wave-stack dielectric mirrors used in a thin

Fabry-Perot filter,” Appl. Opt., vol. 42, no. 27, pp. 5442–5449, 2003.

[49] V. Lindroos, M. Tilli, A. Lehto, and T. Motooka, Handbook of silicon based

MEMS materials and technologies, 1st ed. Elsevier Inc., 2010.

[50] M. Liu, P. Jin, Z. Xu, D. A. H. Hanaor, Y. Gan, and C. Q. Chen, “Two-

dimensional modeling of the self-limiting oxidation in silicon and tungsten

nanowires,” Theor. Appl. Mech. Lett., vol. 6, no. 5, pp. 195–199, 2016.

60

[51] J. Anguita and F. Briones, “HF/H2O vapor etching of SiO2 sacrificial layer for

large-area surface-micromachined membranes,” Sensors Actuators, A Phys.,

vol. 64, no. 3, pp. 247–251, 1998.

[52] W. I. Jang, C. A. Choi, M. L. Lee, C. H. Jun, and Y. T. Kim, “Fabrication of

MEMS devices by using anhydrous HF gas-phase etching with alcoholic

vapor,” J. Micromechanics Microengineering, vol. 12, no. 3, pp. 297–306,

2002.

[53] A. Witvrouw, B. Du Bois, P. De Moor, A. Verbist, C. A. Van Hoof, H. Bender,

and C. Baert, “Comparison between wet HF etching and vapor HF etching for

sacrificial oxide removal,” Int. Soc. Opt. Eng., pp. 130–141, 2000.

[54] W. Kern, “The Evolution of Silicon Wafer Cleaning Technology,” J.

Electrochem. Soc., vol. 137, no. 6, pp. 1887–1892, 1990.

[55] M. Itano, F. W. Kern, M. Miyashita, and T. Ohmi, “Particle Removal from

Silicon Wafer Surface in Wet Cleaning Process,” IEEE Trans. Semicond.

Manuf., vol. 6, no. 3, pp. 258–267, 1993.

[56] W. Kern, Handbook of semiconductor wafer cleaning technology. New Jersey:

Noyes publications, 1993.

[57] Y.-P. Han, “HF Vapor Etching and Cleaning of Silicon Wafer Surfaces,”

Massachusetts Institute of Technology, 1999.

[58] J. H. Gross and P. Roepstorff, Mass Spectrometry, A Textbook, 2nd ed., vol. 68,

no. 12. Springer-Verlag Berlin Heidelberg, 2011.

[59] M.-G. Kim and J.-Y. Kim, “Measurement of two-dimensional thickness of

micro-patterned thin film based on image restoration in a spectroscopic imaging

reflectometer,” Appl. Opt., vol. 57, no. 13, pp. 3423–3428, 2018.

[60] S.-W. Kim and G.-H. Kim, “Thickness-profile measurement of transparent thin-

film layers by white-light scanning interferometry,” Appl. Opt., vol. 38, no. 28,

pp. 59–68, 1999.

61

[61] K. Kim, S. Kwon, and H. J. Pahk, “Fast analysis of film thickness in

spectroscopic reflectometry using direct phase extraction,” Curr. Opt.

Photonics, vol. 1, no. 1, pp. 29–33, 2017.

[62] J. Vodák, D. Nečas, M. Ohlídal, and I. Ohlídal, “Determination of local

thickness values of non-uniform thin films by imaging spectroscopic

reflectometer with enhanced spatial resolution,” Meas. Sci. Technol., vol. 28,

no. 2, 2017.

[63] J. Wang and M. K. Balazs, “Analytical Techniques for Trace Elemental

Analyses on Wafer Surfaces for Monitoring and Controlling Contamination,”

in 19th Annual Semiconductor Pure Water and Chemicals Conference, 2000,

pp. 1–9.

[64] A. Benninghoven, F. G. Rüdenauer, and H. W. Werner, Secondary ion mass

spectrometry: basic concepts, instrumental aspects, applications and trends.

New York: Wiley, 1987.

[65] C. M. Mahoney, Cluster Secondary Ion Mass Spectrometry : Principles and

Applications. Hoboken: John Wiley & Sons, 2013.

[66] P. van der Heide, Secondary Ion Mass Spectrometry : An Introduction to

Principles and Practices, 1st ed. John Wiley & Sons, Incorporated, 2014.

[67] Y. Ma, M. L. Green, L. C. Feldman, J. Sapjeta, K. J. Hanson, and T. W.

Weidman, “Vapor phase SiO2 etching and metallic contamination removal in

an integrated cluster system,” Am. Vac. Soc., vol. 13, no. 4, pp. 1460–1465,

1995.