Valence Electron Energy Loss Spectroscopy of III-Nitride...

Linköping Studies in Science and Technology Dissertation No. 1488

Valence Electron Energy Loss Spectroscopy of

III-Nitride Semiconductors

Justinas Pališaitis

Thin Film Physics Division

Department of Physics, Chemistry and Biology (IFM) Linköping University, Sweden

2012

Cover image

The cover image shows a mirror-reflected experimental Valence Electron Energy

Loss Spectrum line scan obtained across an Al1-xInxN (0≤x≤1) multilayer grown on

Al2O3. The spectrum intensity is projected and represented in a temperature scale.

The bulk plasmon peaks have a green color in In-rich AlInN layers, which gradually

shift downwards towards higher energy and turn to yellow (higher intensity) when

approaching Al-rich AlInN layers and Al2O3.

© Justinas Pališaitis

ISBN: 978-91-7519-746-3 ISSN: 0345-7524

Printed by LiU-Tryck, Linköping, Sweden, 2012

i

Abstract

This doctorate thesis covers both experimental and theoretical investigations of the

optical responses as determined by the material properties of the group III-nitrides

(AlN, GaN, InN) and their ternary alloys. The goal of this research has been to

explore the usefulness of Valence Electron Energy Loss Spectroscopy (VEELS) for

materials characterization of group III-nitride semiconductors at the nanoscale. The

experiments are based on the evaluation of the bulk plasmon characteristics in the

low energy loss part of the EEL spectrum since it is highly dependent on the

material’s composition and strain. This method offers advantages as being fast,

reliable and sensitive. VEELS characterization results were corroborated with other

experimental methods like X-ray Diffraction (XRD) and Rutherford Backscattering

Spectrometry (RBS) as well as full-potential calculations (Wien2k). Investigated

III-nitride structures were grown using Magnetron Sputtering Epitaxy (MSE) and

Metal Organic Chemical Vapor Deposition (MOCVD) techniques.

Initially, it was demonstrated that EELS in the valence region is a powerful method

for a fast compositional analysis of the Al1-xInxN (0≤x≤1) system. The bulk plasmon

energy follows a linear relation with respect to the lattice parameter and composition

in Al1-xInxN layers. Furthermore, the effect of strain on valence EELS was

investigated. It was experimentally determined that the AlN bulk plasmon peak

experiences a shift of 0.156 eV per 1% volume change at constant composition. The

experimental results were corroborated by full-potential calculations which showed

that the bulk plasmon peak position varies nearly linearly with the unit-cell volume,

at least up to 3% volume change.

Employing the bulk plasmon energy loss, compositional characterization was

applied to confined structures, such as nanorods and quantum wells (QWs).

Compositional profiling of spontaneously formed AlInN nanorods with varying In

concentration was realized in cross-sectional and plan-view geometries. It was

established that the structures exhibit a core-shell structure, where the In

concentration in the core is higher than in the shell. The growth of InGaN/GaN

multiple QWs with respect to composition and interface homogeneities was

investigated. It was found that at certain compositions and thicknesses of QWs,

where phase separation does not occur due to spinodal decomposition, QWs

develop quantum dot like features inside the well as a consequence of Stranski-

Krastanov-type growth mode, and delayed In incorporation into the structure.

ii

The thermal stability and degradation mechanisms of Al1-xInxN (0≤x≤1) films with

different In contents, stacked in a multilayer sample, and different periodicity

Al1-xInxN/AlN multilayer films, was investigated by performing a thermal annealing

in combination with VEELS mapping in-situ. It was concluded that the In content in

the Al1-xInxN layer determines the thermal stability and decomposition path. Finally,

the phase separation by spinodal decomposition of different periodicity AlInN/AlN

layers, with a starting composition inside the miscibility gap, was investigated by

thermal annealing and VEELS mapping in-situ.

iii

Populärvetenskaplig sammanfattning

Halvledarmaterial och halvledarteknik baserad på strukturer i nanostorlek har en

stor påverkan på vårt dagliga liv genom ”smarta” elektroniska apparater. Storleken

på halvledarapparater minskar ständigt på grund av behovet av miniatyrisering,

högre processorhastigheter, nya funktioner och lägre kostnader, vilket kontinuerligt

ställer högre krav på materialet som används i dessa apparater.

En viktig grupp hos halvledarmaterialen är grupp III-nitrider, som har unika

fysikaliska egenskaper och som har skapat ett stort intresse för nutida och framtida

tillämpningar inom optoelektronik och transistorer med höga strömmar och

spänningar.

Dessvärre finns det fortfarande en del utmaningar kvar relaterade till grupp III-

nitrider, såsom avsaknad av naturligt substrat, olika tillväxtvillkor, fasseparation,

termisk stabilitet med mera.

För att kunna överkomma dessa utmaningar behöver kontrollen av och förståelsen

för tillväxt- och diffusionsmekanismer tillsammans med kunskap om

sammansättning och struktur öka genom karakterisering av materialet med hjälp av

nya metoder.

För att åstadkomma detta behövs hög rumslig upplösning vilket kan uppnås genom

att använda ett transmissionselektronmikroskop (TEM), där upplösningen för

nuvarande är betydligt bättre än avståndet mellan två atomer. TEM kombineras ofta

med spektroskopiska metoder för sammansättningsanalys såsom energi-dispersiv

röntgenspektroskopi (EDX) och elektron energi förlust spektroskopi (EELS) , vilket

är en metod där energiförlusten hos elektronerna efter att de spridits genom

materialet studeras.

Den här doktorsavhandlingen täcker både experimentella och teoretiska

undersökningar av de optiska egenskaperna, och därmed även materialegenskaper,

hos grupp III-nitriderna (aluminiumnitrid, galliumnitrid och indiumnitrid) och

deras trefasiga legeringar. Målet med forskningen har varit att undersöka om energi

förlust spektroskopi av valenselektroner (VEELS) kan användas för

materialkarakterisering av grupp III-nitrider i nanoskala. Experimenten baseras på

utvärderingar av egenskaperna hos bulkplasmoner i lågenergiförlustområdet av

EEL-spektrumet, eftersom det är väldigt beroende av materialets sammansättning

och spänningar i materialet. Denna metod har flera fördelar såsom snabbhet,

iv

pålitlighet och känslighet. Resultat från VEELS-karakteriseringen bekräftades genom

andra experimentella metoder såsom XRD och RBS (Rutherford Backscattering

Spectroscopy) samt teoretiska beräkningar med Wein2k. Undersökta III-

nitridstrukturer växtes genom MSE (Magnetron Sputtering Epitaxy) och MOCVD

(Metal Organic Chemical Vapour Deposition).

Inledningsvis visades det att EELS i valensområdet är en kraftfull metod för att

analysera sammansättningen av Al1-xInxN-systemet där 0≤x≤1. Energin hos

bulkplasmonerna är linjärt beroende av gitterparametern och sammansättningen i

osträckta Al1-xInxN-lager. Dessutom undersöktes effekten på sträckningar från VEEL-

spektroskopin. Det visades experimentellt att AlN-bulkplasmontoppen flyttades

0,156 eV per procentuell förändring i bulken vid konstant sammansättning. Det

experimentella resultatet bekräftades av fullpotential-beräkningar, vilka visade att

positionen av bulkplasmontoppen varierar linjärt med storleken på enhetscellen,

åtminstone upp till en volymförändring på 3%.

Genom att använda förlusten i bulkplasmonenergin kunde karakterisering av

sammansättningen genomföras på begränsade strukturer, såsom nanorör,

nanohelixar och kvantbrunnar. Sammansättningsanalys av de spontant skapade

AlInN-nanorören/nanohelixarna med varierande In-koncentration genomfördes i

plansnitts- och tvärsnittsgeometrier. Det fastställdes att strukturen uppvisar en kärn-

skalstruktur, där koncentrationen av In i nanorörens/nanohelixarnas kärna är högre

än i skalet. Tillväxten av multipla InGaN/GaN-kvantbrunnar med avseende på

enhetligheten i sammansättning och gränsytan undersöktes. Det upptäcktes av vid

en viss sammansättning och tjocklek på kvantbrunnarna, där fasseparering på grund

av spinodala sönderfall inte sker, utvecklar kvantbrunnarna kvantprickliknande

särdrag inuti brunnen, som en konsekvens av Stranski-Krastanov liknande tillväxt,

där först ett antal atomlager växer och sedan växer ”öar” på dessa lager, och

försenad integrering av In i strukturen.

Mekanismerna för termisk stabilitet och -nedbrytning för varierande In-

koncentration i Al1-xInxN-filmer (0≤x≤1), staplade som multilager, och Al1-xInxN-

supergitter undersöktes genom termisk härdning i kombination med VEELS-

kartläggning in-situ. Det visades att In-koncentrationen i Al1-xInxN-lagret bestämmer

den termiska stabiliteten och -nedbrytningen. Slutligen undersöktes fasseparering på

grund av förändring i lösbarheten i en III-nitrid, genom termisk härdning och

VEELS-kartläggning in-situ.

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Preface

The work presented in this doctoral thesis was conducted from fall 2007 to fall 2012

in the Thin Film Physics Division at Department of Physics, Chemistry and Biology

(IFM) at Linköping University (LiU). The goal of my research was to explore the

capabilities of valence electron energy loss spectroscopy for group III-nitride

semiconductors characterization on the nanoscale. This work was supported by the

Swedish Research Council (VR) through a project and Linnaeus grants, the European

Research Council (ERC) as well as the Swedish Foundation for Strategic research

(SSF) through the Nano-N program and CeNano. This thesis is a continuation of my

Licentiate thesis ‘Electron Energy Loss Spectroscopy of III-Nitride Semiconductors’

(Licentiate thesis No. 1487, Linköping Studies in Science and Technology, 2011).

Being part of a graduate school at LiU was educational and enjoyable experience,

which resulted in my thesis. This would not be possible without contribution from

many people who inspired, guided and assisted me during those years. I would like

to express sincere gratitude to all and special thanks go to my supervisor

Per Persson, co-supervisors Lars Hultman & Jens Birch, co-authors & collaborators,

colleagues at Thin Film, Plasma, Nanostructured & Semiconductor Materials groups

and my family & friends.

Justinas Pališaitis

Linköping, November 2012

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Included Papers

Paper 1 Standard-free composition measurements of AlxIn1-xN by low-loss

electron energy loss spectroscopy

J. Palisaitis, C.-L. Hsiao, M. Junaid, M. Xie, V. Darakchieva, J.F. Carlin, N. Grandjean, J. Birch, L. Hultman, and P. O.Å. Persson Physica Status Solidi – Rapid Research Letters 5, 50 (2011)

My contribution: I performed TEM/STEM-EELS characterization, took part in XRD and RBS data analysis, and wrote the manuscript.

Paper 2 Effect of strain on low-loss electron energy loss spectra of group III-nitrides J. Palisaitis, C.-L. Hsiao, M. Junaid, J. Birch, L. Hultman, and P. O.Å. Persson Physical Review B 84, 245301 (2011)

My contribution: I performed STEM-EELS characterization, took part in EELS simulation and XRD data analysis, and wrote the manuscript.

Paper 3 Spontaneous formation of AlInN core–shell nanorod arrays by ultrahigh-vacuum magnetron sputter epitaxy C.-L. Hsiao, J. Palisaitis, M. Junaid, R.-S. Chen, P. O.Å. Persson, P. Sandström, P.-O. Holtz, L. Hultman, and J. Birch Applied Physics Express 4, 115002 (2011)

My contribution: I performed STEM-EDX/EELS characterization of AlInN nanorods, contributed in data analysis and in writing the manuscript.

Paper 4 Curved-lattice epitaxial growth of chiral AlInN twisted nanorods for optical applications C.-L. Hsiao, R. Magnusson, J. Palisaitis, P. Sandström, S. Valyukh, P. O.Å. Persson, L. Hultman, K. Järrendahl, and J. Birch Manuscript in final preparation

My contribution: I performed STEM-EDX/EELS characterization of twisted nanorods, contributed in data analysis and in writing the manuscript.

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Paper 5 Characterization of InGaN/GaN quantum well growth using monochromated valence electron energy loss spectroscopy J. Palisaitis, A. Lundskog, U. Forsberg, E. Janzen, J. Birch, L. Hultman, and P. O.Å. Persson Manuscript in final preparation

My contribution: I performed STEM-EDX/EELS characterization, analyzed the data and wrote the manuscript.

Paper 6 Thermal stability of Al1-xInxN(0001) throughout the compositional range as investigated during in-situ thermal annealing in a scanning transmission electron microscope J. Palisaitis, C.-L. Hsiao, L. Hultman, J. Birch, and P. O.Å. Persson Submitted to Acta Materialia

My contribution: I performed in-situ annealing experiments, STEM-EELS characterization, analyzed the data and wrote the manuscript.

Paper 7 Spinodal decomposition of Al0.3In0.7N(0001) layers following in-situ thermal annealing as investigated by STEM-VEELS J. Palisaitis, C.-L. Hsiao, L. Hultman, J. Birch, and P. O.Å. Persson Manuscript in final preparation

My contribution: I performed in-situ annealing experiments, STEM-EELS characterization, analyzed the data and wrote the manuscript.

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Related Papers, not Included in the Thesis

Paper 8 Room-temperature heteroepitaxy of single-phase Al1-xInxN films with full composition range on isostructural wurtzite substrates C.-L. Hsiao, J. Palisaitis, M. Junaid, P. O.Å. Persson, J. Jensen, Q.-X. Zhao, L. Hultman, L.-C. Chen, K.-H. Chen, and J. Birch Thin Solid Films, in press (2012)

Paper 9 YxAl1-xN thin films A. Zukauskaite, C. Tholander, J. Palisaitis, P. O.Å. Persson, V. Darakchieva, N. B. Sedrine, F. Tasnádi, B. Alling, J. Birch, and L. Hultman Journal of Physics D: Applied Physics, 45 422001 (2012)

Paper 10 InGaN quantum dot formation mechanism on hexagonal GaN/InGaN/GaN pyramids A. Lundskog, J. Palisaitis, C. W. Hsu, M. Eriksson, F. Karlsson, P. O.Å. Persson, U. Forsberg, P.-O. Holtz, and E. Janzen Nanotechnology 23, 305708 (2012)

Paper 11 Microstructure and dielectric properties of piezoelectric magnetron sputtered w-ScxAl1−xN thin films A. Zukauskaite, G. Wingqvist, J. Palisaitis, J. Jensen, P. O.Å. Persson, R. Matloub, P. Muralt, Y. Kim, J. Birch, and L. Hultman Journal of Applied Physics 111, 093527 (2012)

Paper 12 Two-domain formation during the epitaxial growth of GaN (0001) on c-plane Al2O3 (0001) by high power impulse magnetron sputtering M. Junaid, D. Lundin, J. Palisaitis, C.-L. Hsiao, V. Darakchieva, J. Jensen, P. O.Å. Persson, P. Sandström, W.-J. Lai, L.-C. Chen, K.-H. Chen, U. Helmersson, L. Hultman, and J. Birch Journal of Applied Physics 110, 123519 (2011)

Paper 13 Face-Centered Cubic (Al1-xCrx)2O3

A. Khatibi, J. Palisaitis, C. Höglund, A. Eriksson, P .O.Å. Persson, J. Jensen, J. Birch, P. Eklund, and L. Hultman Thin Solid Films 519, 2426 (2010)

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Paper 14 Electronic-grade GaN(0001)/Al2O3(0001) growth by reactive DC-magnetron sputter epitaxy using a liquid Ga sputtering target M. Junaid, C.-L. Hsiao, J. Palisaitis, J. Jensen, P. O.Å. Persson, L. Hultman, and J. Birch Applied Physics Letters 98, 141915 (2010)

Paper 15 Growth and properties of SiC on-axis homoepitaxial layers J. ul-Hassan, P. Bergman, J. Palisaitis, A. Henry, P.J. McNally, S. Anderson, and E. Janzen Materials Science Forum Vols. 645-648, 83-88 (2010)

Paper 16 Macrodefects in cubic silicon carbide crystals V. Jokubavicius, J. Palisaitis, R. Vasiliauskas, R. Yakimova, and M. Syväjärvi Materials Science Forum Vols. 645-648, 375-378 (2010)

Paper 17 Trimming of aqueous chemically grown ZnO nanorods into ZnO nanotubes and their comparative optical properties M.Q. Israr, J.R. Sadaf, L.L. Yang, O. Nur, M. Willander, J. Palisaitis, and P. O.Å. Persson Applied Physics Letters 95, 073114 (2009)

Paper 18 Two dimensional x-ray diffraction mapping of basal plane orientation on SiC substrates J. Palisaitis, J. P. Bergman, and P. O.Å. Persson Materials Science Forum Vols. 615-617, 275-278 (2009)

Paper 19 AlGaN multiple quantum wells and AlN grown in a hot-wall MOCVD for deep UV applications A. Henry, A. Lundskog, J. Palisaitis, I. Ivanov, A. Kakanakova-Georgieva, U. Forsberg, P. O.Å. Persson, and E. Janzen ECS Transactions, Vol. 25, Iss. 8, (2009)

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Paper 20 Stress evolution during growth of GaN (0001)/Al2O3 (0001) by reactive DC magnetron sputter epitaxy M. Junaid, P. Sandström, J. Palisaitis, V. Darakchieva, C.-L. Hsiao, P. O.Å. Persson, L. Hultman, and J. Birch Submitted to Journal of Physics D: Applied Physics

Paper 21 Unexpected behavior of InGaN quantum dot emission energy located at apices of hexagonal GaN pyramids A. Lundskog, C. W. Hsu, J. Palisaitis, F. Karlsson, P. O.Å Persson, L. Hultman, U. Forsberg, P.-O. Holtz, and E. Janzen Submitted to Journal of Applied Physics

Paper 22 Coexistence of 2D/3D growth mode of single GaN nanorods by molecular beam epitaxy Y.-T. Chen, T. Araki, J. Palisaitis, P. O.Å. Persson, L.-C. Chen, K.-H. Chen, P.-O. Holtz, J. Birch, and Y. Nanishi Submitted to Advanced Materials

Paper 23 Liquid-target reactive magnetron sputter epitaxy of high quality GaN(000��) nanorods on Si(111) M. Junaid, Y.-T. Chen, J. Palisaitis, M. Garbrecht, C.-L. Hsiao, P. O.Å. Persson, L. Hultman, and J. Birch Submitted to Nanotechnology

Paper 24 Effect of N2 partial pressure on growth, structure, and optical properties of GaN nanorods grown by liquid-target reactive magnetron sputter epitaxy M. Junaid, Y.-T. Chen, J. Lu, J. Palisaitis, C.-L. Hsiao, P. O.Å. Persson, L. Hultman, and J. Birch Manuscript in final preparation

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Table of Contents

1. INTRODUCTION TO THE FIELD .............................................................................. 1

2. III-NITRIDE SEMICONDUCTORS ............................................................................ 5

2.1 Crystal Structure .......................................................................................................... 5

2.2 Polarity and Polarization .......................................................................................... 10

2.3 Bandgap Engineering of Ternary Alloys ................................................................ 11

2.4 Phase Stability ........................................................................................................... 12

3. III-NITRIDE GROWTH .............................................................................................. 13

3.1 Magnetron Sputtering Epitaxy (MSE) .................................................................... 14

3.2 Metal Organic Chemical Vapor Deposition (MOCVD) ....................................... 15

3.3 Template for Growing III-Nitrides ......................................................................... 16

4. STRESS AND STRAIN IN THIN FILMS ................................................................. 19

5. III-NITRIDE CHARACTERIZATION METHODS ................................................ 23

5.1 Transmission Electron Microscopy (TEM)............................................................. 23

5.1.1 The Principle of TEM .......................................................................................... 24

5.1.2 Resolution Limit and Aberration Correctors .................................................... 25

5.1.3 Arwen .................................................................................................................. 27

5.2 Main TEM Imaging Techniques ............................................................................. 29

5.2.1 Density/Thickness Contrast ............................................................................... 29

5.2.2 Diffraction Contrast (Bright/Dark Imaging Modes) ........................................ 29

5.2.3 Diffraction in TEM .............................................................................................. 31

5.2.4 Selective Area Electron Diffraction (SAED) ...................................................... 32

5.2.5 Phase Contrast (HR-TEM) .................................................................................. 33

5.2.6 Z-Contrast Imaging ............................................................................................. 35

5.3 Analytical Methods in the STEM ............................................................................ 37

5.3.1 High Energy Electron Interaction with Material .............................................. 37

5.3.2 STEM Analysis .................................................................................................... 38

5.3.3 Energy-Dispersive X-ray Spectroscopy (EDX) ................................................. 39

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5.4 Electron Energy Loss Spectroscopy (EELS) ............................................................ 40

5.4.1 Electron Energy Loss Spectrum ......................................................................... 43

5.4.2 Zero-Loss Region ................................................................................................ 43

5.4.3 Low-Loss Region and Valence Electron Energy Loss Spectroscopy .............. 44

5.4.4 VEEL Spectrum Simulations .............................................................................. 50

5.4.5 VEELS Data Post-Processing .............................................................................. 51

5.4.6 Core-Loss Region ................................................................................................ 53

5.5 In-Situ TEM Experiments ......................................................................................... 54

5.6 TEM Sample Preparation ......................................................................................... 56

5.6.1 Conventional Cross-Sectional Sample Preparation ......................................... 56

5.6.2 TEM Samples in Few Minutes ........................................................................... 57

5.6.3 Focused Ion Beam (FIB) Sample Preparation ................................................... 57

5.7 Rutherford Backscattering Spectrometry (RBS) .................................................... 59

5.8 X-ray Diffraction (XRD) ............................................................................................ 60

6. SUMMARY AND CONTRIBUTION TO THE FIELD ............................................ 63

7. BIBLIOGRAPHY .......................................................................................................... 65

INCLUDED PAPERS…….………………………………………………………………..75

1

1. Introduction to the Field

Materials are vital in the process of human evolution. Therefore, the historical

periods carry the names of the major material that was used in everyday life, e.g.

Stone Age [1].

Which material will take a dominant position and be technologically applied in the

near future, greatly depends on developments and discoveries in material science.

Understanding, predicting, and designing the behavior and properties of a material

are few of the major driving forces for development of new technologies.

Materials analysis is the key component in providing knowledge about the material.

The Ancient Greeks ‘characterized’ materials quality, reliability and found defects in

final products by using nondestructive methods based on human senses like

hearing, touching and smelling [2,3]. The industrial revolution changed the way

people lived, worked and produced goods [4], which increased the demand not only

for novel materials but also for modern material characterization methods. This

marks the start of great fundamental discoveries and developments of the material

characterization methods in physics, which served as the basic principles for the

contemporary material analysis techniques. The development of the electronic

industry in combination with the new characterization methods resulted in

shrinking dimensions of device structures and led to the birth of nanotechnology [5].

This would not be possible without constant development of the characterization

methods which firstly were applied to the bulk type materials and later to the

nanoscale based structures. Nowadays nanotechnology is a very diverse field

covering many disciplines from the material science to medicine. As the size is

reduced to the nanoscale, surface and quantum mechanical effects start to dominate

the material properties exceeding classical physics laws.

The growth of nanostructures is achieved by using contemporary growth methods,

which allow a precise control of the growth parameters and lead to production of the

low-dimensionality structures. Artificially fabricated nanostructures are typically

classified according to the number of dimensions in the nanoscale range.

Nanoparticles and quantum dots (QDs) are zero dimensional nanostructures (0D),

nanorods and nanotubes – 1D; quantum wells (QWs) – 2D. Even more complex

structures, like pyramids, capped with other material, contain QWs on side walls

and wall edges as well as QDs on the top, as shown in Figure 1.

Introduction to the Field

2

Figure 1. Electron microscopy images of nanostructures: (a) Au nanoparticle, (b) AlInN nanorods, (c) InGaN/GaN multiple QWs and (d) GaN pyramid capped with InGaN layer.

Semiconductor materials and technology based on nanoscale structures make a huge

impact on our everyday life by supplying us with ‘smart’ electronic devices. The

trend is continuously moving towards miniaturization of the solid-state devices

driven by the need of compactability, higher processing speed, new functionalities

and lower cost, which puts higher requirements on the materials used [6].

An important part of the semiconductor material group is III-nitride

semiconductors, which own the unique physical properties and attract huge interest

due to their applications for contemporary and future optoelectronic and high-

power devices [7-11]. [7,8,9,10,11]

However, there is a number of remaining challenges related to III-nitrides that were

addressed in a number of scientific studies, for example: lack of native substrate,

different growth conditions, phase separation, etc.


3

In order to conquer these challenges, one needs to control and understand the

growth and diffusion mechanisms along with the compositional and structural

information through material characterization with novel methods.

The material analysis is usually performed on a macro and/or nanoscale. Methods,

employing electrons, ions, and photons, take important part among material analysis

techniques. They can be divided into different categories depending on signal

detected, resolution, etc. A short summary of the most common techniques is given

in Table 1.

Table 1. Analysis techniques employing electron, ion and photon beams.

Incident

beam

Signal

detected

Technique Probes

Electron Electron

Electron

Photon

Electron microscopy

Auger spectroscopy

X-ray emission spectroscopy

Structure & Chemistry

Chemistry

Chemistry

Ion Ion Rutherford backscattering spectrometry Composition

Photon Photon

Electron

X-ray diffraction

X-ray photoelectron spectroscopy

Structure

Chemistry

Rutherford backscattering spectrometry (RBS) and X-ray diffraction (XRD) are

commonly used for the macroscopic compositional and structural investigations.

However, these methods are not adequate to investigate confined structures, like

QWs, QDs, or single precipitates. In order to achieve this, high spatial resolution is

required, which is possible to reach by using the transmission electron microscope

(TEM) where currently the resolution is below the atomic level. TEM is frequently

combined with spectroscopy methods for compositional analysis such as energy

dispersive X-ray spectroscopy (EDX) and electron energy loss spectroscopy (EELS).

In this thesis, valence (V)EELS is employed as the main technique for investigating

group III-nitride materials in combination with other characterization methods. The

valence electron energy loss spectrum region governed by the dielectric function is

rich in information, and provides a tool for sample characterization.


4


5

2. III-Nitride Semiconductors

The core material of today’s semiconductor industry remains Si, however due to

limitations of the physical properties it cannot meet future challenges in emerging

electronic applications, which require device operation at high temperature, power

and frequency. For such applications high thermal conductivity, high breakdown

electric field, tunable band gap as well as thermal, mechanical and chemical stability

are the main prerequisites. A material group exhibiting such physical properties is

III-nitride semiconductors (AlN, GaN and InN), along with their ternary (e.g.,

AlInN) and quaternary alloys (e.g., AlGaInN). Some of the desired properties are

given by a large electro-negativity difference between the group III elements and N,

and establish strong chemical bonds. Group III-nitrides are the key materials for

contemporary electronic devices such as high-brightness blue and white light

emitting diodes, laser diodes, photovoltaics, full-color displays, traffic lights, high-

frequency transistors, chemical sensors, surface acoustic wave and quantum

structure devices [7,12-20]. 12,13,14,15,16,17,18,19,20

2.1 Crystal Structure

The ideal crystal can be built by arranging atoms, molecules or ions in the regular

manner in three dimensions and by keeping long range periodicity. However, real

crystals are decorated with imperfections like impurities and structural defects,

incorporated during the growth process or post-growth treatment. The material

properties are governed by the crystal structure which is defined by periodicity and

symmetries. In general, one can generate 14 basic crystal structures through different

symmetries, called Bravais lattices, in three dimensional space [21].

Group III-nitrides are compound semiconductors formed by alloying group III

elements with N (situated in group V) and commonly found in three crystal

structures: wurtzite, zincblende, and rocksalt [22-24]. [22,23,24]

Two main III-nitride polytype structures: wurtzite which has hexagonal unit cell,

and zincblende which has cubic unit cell, are shown in Figure 2. Under ambient

temperatures and pressures the thermodynamically stable phase is wurtzite (space

group �6�mc) for all bulk III-nitrides and is the most commonly used structure.


6

Figure 2. Ball-and-stick model of two GaN polytypes: (a) wurtzite (w-GaN), (b) zincblende (z-GaN).

The metastable zincblende-cubic structure (space group �43m) is frequently

reported and can be observed in III-nitride growth on cubic substrates or as a result

of built-in strain in the structure [25,26].

An illustrative example of both crystal structures (wurtzite and zincblende) can be

seen in a GaN nanorod, observed by high resolution TEM (HR-TEM), and is shown

in Figure 3. The small zincblende GaN inclusion is generated after lowering the

growth temperature and results in strain reduction.

Figure 3. HR-TEM image of hexagonal GaN nanorod containing a zincblende GaN inclusion, interfaces are indicated by arrows.


7

In the wurtzite and zincblende structures atoms are tetrahedraly coordinated (e.g.,

one Ga atom is bound to 4 N atoms), but the stacking sequence and bond angles are

slightly different. The stacking sequence for wurtzite is ABAB… along the c-axis i.e.,

[0001] and for zincblende is ABCABC… along the [111] axis.

Furthermore, the high pressure rocksalt AlN structure was predicted theoretically

and stabilized in epitaxial AlN/TiN superlattices [27]. The rocksalt structures have a

face centered cubic unit cell (space group ��3m).

The most common polytype (wurtzite) is the only structure characterized in this

thesis (Papers 1-7).

Conventionally, planes and directions of crystals are characterized using the Miller

indices. A schematic representation of major crystallographic planes and directions

in the hexagonal and cubic (unit cell) systems are shown in Figure 4.

Figure 4. Major crystallographic directions and planes in (a) hexagonal and (b) cubic unit cells.

Based on crystallographic orientations and directions, the crystal exhibits anisotropic

properties and, as observed in the TEM, different atomic coordination. High

resolution scanning TEM (HR-STEM) images of wurtzite AlN, viewed along the

most common hexagonal unit cell crystallographic projections (zone axes) [1100],

[1120] and [0001] together with schematic images (obtained by the JEMS image

simulation software [28]), are shown in Figure 5.


8

Figure 5. The HR-STEM images together with schematic illustrations of wurtzite AlN, as viewed along [11�0] (a-b), [1�00] (c-d) and [0001] (e-f) zone axes.


9

The main physical properties for III-nitrides and substrates, such as the lattice

parameters, bandgaps, etc., are summarized in Table 2.

Table 2. Basic material parameters of III-nitrides, Si, SiC, ZnO and Al2O3 [16,22].

Material

Band gap

[eV]

Lattice

parameter a

[Å]

Lattice

parameter c

[Å]

Thermal

expansion

[K-1]

Thermal

conductivity

[Wcm-1K-1]

w-AlN 6.2 3.11 4.98 4.21·10-6 1.3

z-AlN - 4.36 - 4.56·10-6 2.8

w-GaN 3.44 3.18 5.18 5.59·10 -6 2.0

z-GaN 3.23 4.50 - 4.78·10 -6 1.3

w-InN 0.64 3.54 5.76 - 0.8

z-InN - 4.98 - 5.03·10 -6 -

Al2O3 9.00 4.75 12.99 7.50·10-6 0.3

6H-SiC 3.05 3.08 15.12 4.2·010-6 4.9

ZnO 3.30 3.25 5.20 - -

Si 1.11 5.30 - 3.59·10 -6 1.5


10

2.2 Polarity and Polarization

Atoms in the III-nitride crystals slightly deviate from their ideal lattice positions.

This induces a lack of the central symmetry perpendicular to the c-axis and hence the

hexagonal crystal structure does not experience the highest symmetry available for

this system. As a result of deviation and strong ionic bonding, III-nitrides become

polar crystals along c-axis with induced macroscopic polarization field [29-31]. [29,30,31]

Polarity leads initially to spontaneous, and if strained, to strong piezoelectric

polarization effects. The polarization field direction and surface properties are

influenced by the polarity of the crystal – the bond direction along the c-axis. When

the direction along the c-axis is started from Ga to N, the surface polarity is defined

as Ga-polar, and vice versa – N-polar (see Figure 6).

Figure 6. Two different polarities of GaN shown together with bond orientation (the crystal viewed along [11�0] zone axis).

In the hexagonal system there also are semi-polar r-plane and nonpolar a-plane and

m-plane (see Figure 4), which are of the significant importance as they do not

experience polarization field [32,33].

The polarity of the grown structure depends on the employed growth technique and

conditions as well as used substrate/buffer layer and can be associated with bonding

configurations at the interface [34]. There is a numbers of ways to determine it, such

as etching, converged beam electron diffraction (CBED), EELS [35,36].


11

2.3 Bandgap Engineering of Ternary Alloys

Group III-nitrides are attractive materials for optoelectronic applications due to their

band structure which exhibits a direct band gap spanning from ultraviolet (wide) to

infrared (narrow), or from 6.2 eV for AlN to 0.64 eV for InN at room temperatue,

shown in Figure 7.

Figure 7. Energy band gap of III-nitrides and their ternary alloys as a function of the lattice parameter a.

By alloying InN with AlN and GaN the bandgap can be varied from IR to UV in

ternary as well as quaternary systems. The bandgap, as a function of alloying

composition, follows a linear relationship – the Vegards’s law with a correction

factor (called the bowing parameter), which should be taken into account and treats

deviations from the linear dependence among binary alloys [7,37,38].

In general, the bandgap of AlxIn1-xN can be calculated using the following equation:

��,�� ,�� 1 � ��,�� 1 � ��, (1)

where �� is the bandgap, x is the Al fraction, and b is the bowing parameter.

The values for the bowing parameter are debated in literature [39], as they differ in

the different compositional regimes. The presence of strain has a profound effect on

the bandgap by reducing it [40].

Al0.83In0.17N is particularly attractive since it can be grown lattice-matched to GaN,

which allows realization of stress free heterostructures with tunable bandgap and

high crystal quality [41].


12

2.4 Phase Stability

Alloying two binary wurtzite nitrides (e.g., InN and AlN) results in a ternary

compound (AlxIn1-xN). Material properties, such as bandgap, can be varied with

changing the alloy composition (section 2.3), but this comes at the cost of

compositional homogeneity, crystal quality, phase and thermal stability. Theoretical

calculations show that III-nitrides are prone to phase separation [42], since binary

constituents (e.g. InN and AlN) experience large lattice, thermal and chemical

mismatches resulting in large miscibility gap as well as distant growth conditions.

Synthesis of homogeneous solid solutions though entire compositional range is

therefore a challenge. The phase diagram for AlxIn1-xN alloy is shown in Figure 8.

Phase, presented in spinodal region is unstable, and resultant phase separation is

referred to as spinodal decomposition, where binodal phase is metastable.

Figure 8. Phase diagram of AlxIn1-xN alloys [42].

Typically, phase separation occurs when system is quenched below certain critical

temperature and experiences transformation from initially homogeneous solution to

formation of diffusion driven compositional fluctuations. Another approach to

induce phase separation is to synthesize films inside miscibility gap, utilizing, e.g.,

low temperature growth methods (section 3.1), and initiating phase separation by

annealing. Phase separation evolution can be affected by a number of factors such as:

strain [43-45],[43,44,45]composition [42] and additional confinements present in the system

[46]. In the multilayer structure interface layers are the limiting factor for the vertical

elemental diffusion and the surface directed spinodal decomposition might play the

most important role [47,48].


13

3. III-Nitride Growth

In order to grow a film one applies a flux of atoms from vapor or liquid phase onto a

substrate surface. Thermodynamic and kinematic constrains define the adatom

behavior on the substrate surface and processes like adsorption, desorption, and

diffusion. In any case, the adsorbed atoms strive to minimize their energy by

occupying energetically preferred sites on the substrate surface. The evolution of the

growth is a consequence of minimization of the total energy. Accordingly, the

nucleation and growth process defines the growth mode of the crystal [49].

When a layer of one material is epitaxially grown on a substrate or buffer layer, this

is called hetero-epitaxy. For hetero-epitaxy, the growth mode is primarily influenced

by the lattice parameter differences between the film and the substrate. During

initial stages of growth the first few mono-layers of the epilayer are under tensile or

compressive strain (discussed in 4) in order to adapt to the substrate lattice

parameter. As a result of build-in strain in the film, the film should undergo

transformation to reduce this energy, resulting in different growth modes.

Experimentally, the distinction between the three fundamental hetero-epitaxial

growth modes is well established: Frank-van der Merwe (FM) layer-by-layer growth

(2D), Volmer-Weber (VW) island growth (3D) and Stranki-Krastanov (SK) mixed

growth of layer-by-layer followed by islands formation (Figure 9).

Figure 9. Schematics of three hetero-epitaxial growth modes: Frank-van der Merwe (FM), Volmer-Weber (VW), and Stranski-Krastanow (SK).

Hetero-epitaxial growth modes provide basic understanding, but cannot account for

all factors influencing the growth of novel films. Different strategies can be utilized

to achieve desired structures, e.g., step-flow growth, anisotropic atom fluxes,

catalytic growth.

III-Nitride Growth

14

As discussed in section 2.4, for group III-nitrides it is challenging to achieve a high

crystal quality and homogenous solution through the full compositional range, due

to distant material properties and growth conditions. E.g., InN must be grown at a

lower temperature compared to AlN due to a lower dissociation temperature [50,51].

There are a number of different methods to grow III-nitrides; in this thesis the

investigated III-nitride structures were grown using magnetron sputtering epitaxy

(MSE) and metal organic chemical vapor deposition (MOCVD) techniques.

3.1 Magnetron Sputtering Epitaxy (MSE)

Most of the III-nitride films investigated in this thesis were grown using MSE, which

is a growth method based on the sputtering process [52-55].[52,53,54,55]To initiate the

sputtering process, an inert gas, most often Ar, is introduced into a vacuum

chamber. The basic MSE working principle is shown in Figure 10.

Figure 10. MSE system scheme and fundamental working principle: I - generated plasma, II - sputtering of the target atoms, III - deposition on the substrate.

After igniting the plasma in the vacuum chamber, high (kinetic) energy ions (I) are

accelerated towards one or more targets (II), which are kept at negative potential. In

the sputtering process secondary electrons are generated at the target surface which

helps to sustain ionization of Ar gas. Ions and neutrals are sputtered from the target

towards the substrate surface (III) where a film is grown. Nitrogen (N2) gas is also

introduced into the chamber together with Ar. Nitrogen also acts as a sputtering gas

but reacts with sputtered atoms to form a compound. Compositional variations in

the growing film are achieved by varying the power of the magnetrons. The main

characteristic of the MSE process is that the energy of adatoms is determined by

substrate temperature and kinetic energy of adorbed atom can be varied by applying

III-Nitride Growth

15

a bias to the substrate. Due to the added kinetic energy, growth occurs at non-

thermaldynamic equilibrium conditions.

Al1-xInxN (0≤x≤1) layers and nanostructures studied in Papers 1-4 and 6-7 were

grown in an ultra-high-vacuum (UHV) MSE system (Ragnarök) at LiU. The chamber

has a base pressure of < 4x10-7 Pa. As material sources, high purity 75 mm-diameter

Aluminum (99.999%) and 50 mm-diameter Indium (99.999%) targets were used.

Typically, Al1-xInxN (0<x≤1) growth was performed under pure nitrogen

environment at ambient temperature and AlN at 1000 oC.

3.2 Metal Organic Chemical Vapor Deposition (MOCVD)

MOCVD is the most commonly used growth technique for depositing III-nitrides

[56,57]. This method is based on a thermally induced reaction of gas-phase precursor

molecules on a heated substrate surface [58,59].

In the case of III-nitride growth, the precursors are supplied as metal-organic

molecules. Trimethylaluminum (TMAl), trimethylgallium (TMGa), trimethylindium

(TMIn), and ammonia (NH3) were used as precursors for Al, Ga, In and N,

respectively, with N as carrier gas [60].

The basic principle of MOCVD together with schematics of the reactor scheme is

illustrated in Figure 11.

Figure 11. MOCVD reactor basic scheme and fundamental working principle: I -precursor, II - dissociation, III - deposition and IV - removal of residual gases.

A mix of precursor gas carrying the desired elements flows through the system in

one direction (I). After entering the high temperature reaction zone, molecules are

dissociated by heat (II) and initiates condensation of the species on the substrate

surface (III). The heat is supplied using radio frequency (RF) coils around the

III-Nitride Growth

16

chamber. Compositional variations in the film are achieved by varying the gas flow

ratio (composition of gas). The remaining reaction products are removed from the

reactor (IV). High purity and high structural quality III-nitride semiconductors with

growth rate of ~2 μm/h can be produced using MOCVD. The growth temperature is

close to thermodynamic equilibrium, as the energy of adatoms depends on

temperature only.

Two III-nitride heterostructure samples containing InGaN/GaN QWs were

investigated in this thesis (Paper 5). The samples were grown in a low pressure hot-

wall MOCVD reactor at LiU. The indium content in the grown QWs was changed

using different TMIn flow rates, in the range from 25 ml/min to 75 ml/min. The

thickness of the QWs was controlled by adjusting the growth time. Typical growth

temperature for QWs was ~800 oC [61,62].

3.3 Template for Growing III-Nitrides

The growth of epitaxial III-nitride semiconductor structures is commonly performed

on foreign substrates (hetero-epitaxy) since native substrates (homo-epitaxy) are

expensive and rarely available [63]. This generally results in a degradation of the

crystal quality of the grown film due to the different crystal structure, lattice

mismatch and thermal expansion coefficients (see Table 2). Crystal structure, price,

physical properties, etc., influence the choice of substrate. By using various growth

strategies high quality epitaxial layers can still be fabricated [64,65]. For instance,

thick buffer layers (of GaN or AlN) can be used to minimize stress and defect

densities in the final structure. Most commonly used substrates are Si, sapphire

(Al2O3) and SiC.

Examples of Al0.84In0.16N structures grown using different growth strategies and

techniques (MSE and MOVCD) are shown in Figure 12. The full compositional range

Al1-xInxN layers investigated in Paper 1 were grown on Al2O3 substrate with a 50 nm

thick high temperature AlN layer (Figure 12a). Another set of Al-rich Al1-xInxN layers

were grown by MOCVD on SiC substrates with GaN buffer layers (Figure 12b). In

both cases buffer layers (AlN and GaN) were used to reduce strain and density of

threading dislocations.

It was demonstrated in Paper 2 that the choice of template and growth temperature

affects the lattice parameter of AlN. The investigated AlN layers were found to be in

relaxed (thick AlN layer grown on Al2O3 at 1000 oC) and oppositely strained states

(thin AlN layer grown on Al2O3 and ZnO at ambient temperature).

III-Nitride Growth

17

Figure 12. Same composition Al0.84In0.16N structures grown using different growth strategies and techniques: (a) MSE on AlN/Al2O3 and (b) MOCVD on GaN/SiC.

In Papers 3-4 it was established that the choice of buffer layers (VN or Ti0.21Zr0.79N)

plays an important role in controlling the Al-rich AlInN nanorod growth. By using

different buffer layers it was shown that the film morphology can be changed from

continuous film to nanorods. Under identical growth conditions an epitaxial film

was formed directly on Al2O3 and nanorods on the VN buffer layers (see Figure 13).

Figure 13. Al-rich AlInN grown by MSE under identical growth conditions. Resulting (a) thin film and (b) nanorods morphologies on Al2O3 and VN seed layer, respectively.

III-Nitride Growth

18

III-Nitride Growth

19

4. Stress and Strain in Thin Films

Epitaxially grown hetero-structures experience an adaptive challenge as two lattices

with different physical properties are forced together. Strain is inevitable in modern

electronic devices, which are increasingly integrating structures with dimensions on

the nanoscale, such as optical devices based on quantum wells [17].

As the structures are geometrically scaled down, the impact of strain has a

significant effect on III-nitride characteristics, such as modulation of the band

structure and electronic transport properties, reduced crystal symmetry, defect

formation, polarization effects, composition pulling effect [66-69]. [66,67,68,69]On the other

hand, strain can be exploited for increasing performance, e.g., in SiGe layer devices

[70,71].

Stress and strain are linked to each other by the elastic constant of the material

according to Hook’s law: if material is stressed – forced it will become strained –

displaced. Strain causes the structure atoms to deviate from their natural equilibrium

positions [72]. The stress is defined as internal force (per unit area) trying to bring

atoms to the equilibrium positions produced by balancing external force acting and

distorting the structure:

� � �, (2)

where F is external force and A – area.

Under applied strain two major scenarios are possible. 1) exceeded critical level of

the strain results in nucleation of defects, such as dislocations, phase transformation,

cracking or delamination – plastic response; 2) moderate amount of the strain can

accommodate by slightly distorting the lattice – elastic response.

In the case of the hexagonal crystal structure (thin film) which is coherently strained

on a relaxed structure (substrate), the in-plane and out-of-plane strains can be

expressed as:

"## � "$$ � %&%'%' , (3)

"(( � )&)')' , (4)

where a0 and c0 are relaxed lattice parameters, a and c - strained lattice parameters.

Stress and Strain in Thin Films

20

If a hexagonal crystal experiences biaxial tensile in-plane stress, it becomes tensely

strained in-plain and compressively out-of-plane due to the Poisson effect as shown

in Figure 14.

Figure 14. As a result of strain, the hexagonal unit cell lattice parameters (a and c) deviate from equilibrium (a0 and c0).

The stress and strain are second rank tensors. As the material behavior is anisotropic

and inhomogeneous, and the properties will be different in different crystallographic

directions. The applied force is a vector and it needs nine components in the matrix

notation for the complete description:

�*+ � ,�## �#$ �#(�#$ �$$ �$(�#( �$( �((-, (5)

.*+ � ,.## .#$ .#(.#$ .$$ .$(.#( .$( .((-. (6)

According to the linear elasticity theory, the relation between induced strain in the

crystal and stress can be expressed as:

�*+ � /*+0�"*+ , (7)

"*+ � 1*+0��*+, (8)

where C and S are stiffness and compliance constants, respectively.


21

For a hexagonal crystal the relation between stress and strain finally can be

expressed as:

2334�##�$$�((�$(�#(�#$5

667 �233334

)(2/100000

00000

00000

000

000

000

1211

44

44

331313

131112

131211

CC

C

C

CCC

CCC

CCC

− 566667

2334"##"$$"((2"$(2"#(2"#$5

667

, (9)

where C11, C12, C13, C33, and C44 are elastic stiffness constants.

The origin of strain present in the structure can be lattice mismatch in

heterostructures, different growth conditions, intrinsic stress, and applied external

stress, etc. The film can be found in different strained states (relaxed, partly-relaxed

or strained) resulting in increasing or decreasing unit cell volume. Schematic

examples of differently strained layers are shown in Figure 15.

Figure 15. Schematics showing (a) bulk lattice (substrate and film separated), (b) compressively strained thin film on the rigid substrate and (c) partly relaxed film on the rigid substrate.

Group III-nitrides are typically grown on thermal expansion coefficients mismatched

buffer layers and substrates (see Table 2); the grown structure typically encounters

strain. Three differently strained AlN layers were investigated in Paper 2, the AlN

layers were found to be in relaxed and strained states due to different substrates,

growth temperatures as well as layer thicknesses. AlN grown on different substrates

experiences a lattice mismatch, which for AlN on ZnO and Al2O3 is −4.3% and

+13.3%, respectively.


22


23

5. III-Nitride Characterization Methods

5.1 Transmission Electron Microscopy (TEM)

The properties of a material are governed by its structure and composition, where

both have to be investigated with high accuracy in order to be fully understood. The

optical microscope has been serving as the major material observation tool for a long

time, but its resolution is limited. In fact, Ernst Abbe showed that optical

microscopes have the diffraction limited resolution, which is proportional to the

ratio between radiation wavelength and aperture size [73]. Later his theory was

refined by Rayleigh for the quantitative measure of the minimum resolvable details

and is known as the Rayleigh criterion [74]. The resolution (d) of an optical system is

conventionally defined as:

8 � 0.61 ;�� , (10)

where λ – wavelength, NA – aperture size.

Due to wavelength of the light, optical microscope resolution can only reach down

to ~200 nm. For overcoming this limit other type of radiation should be used.

The existence of the electron was confirmed by Thomson’s experiments and Louis de

Broglie showed the dualism principle between particles and waves, meaning that

particles traveling at high speed have wave characteristics. Based on the imaging

principle of the optical microscope and employing electrons as the radiation source,

the world’s first TEM was built by Ruska and Knoll in 1932 [75-77].[75,76,77]The wavelength

of the electrons depends on their energy. Taking into account relativistic effects, the

electrons accelerated by 300 kV have wavelength of 1.9 pm. Such short electron

wavelength makes atomic resolution feasible in TEM. The resolution of high-end

TEM microscopes can reach down to 50 pm and even beyond. TEM imaging

techniques are extensively used in academia and industry, where characterization on

the atomic level can provide not just imaging, but also spectroscopic information.

Moreover, the TEM offers a wide range of supplementary information

(crystallographic information about defects, strain, interfaces and boundaries, etc.),

which is available as a result of different operation modes and imaging techniques,

such as bright-field (BF), dark-field (DF) (section 5.2.2), selective area electron

diffraction (SAED) (section 5.2.4) and HR-TEM (section 5.2.5). If an electron probe is

formed by focusing electrons into a fine spot which is scanned across the sample, the

instrument is operated in scanning TEM (STEM) mode (section 5.2.6). It enables

III-Nitride Characterization Methods

24

imaging and analysis on the nanometer scale, including precise EELS and EDX

(sections 5.3-5.4).

The typical limitations of TEM include: small sampling volume, electron beam

damage to the material, and interpretation of images and spectra. Moreover, sample

preparation – which is a demanding and destructive process (section 5.6),

Two microscopes were used for studies in this thesis: FEI Tecnai F20 (200 kV) named

‘Galadriel’ and FEI double-corrected Titan3 (300 kV) – ‘Arwen’.

5.1.1 The Principle of TEM

The basic working principle of TEM is similar to that of an optical microscope. Since

the TEM employs electrons, the microscope must operate at high vacuum

conditions. A basic TEM and STEM scheme is shown in Figure 16. The electrons are

emitted from the electron gun, where the most common types include tungsten (W) -

filament, LaB6, field emission gun (FEG), cold-FEG, high-brightness FEG, where each

differs in brightness, spatial coherence and primary beam energy [78-82]. [78,79,80,81,82]After the

electrons are extracted from the tip of the gun, they are accelerated by a significant

potential difference. Typically, the acceleration voltage can be widely varied from

60 kV to 300 kV. Lower voltage is preferential for studying electron beam sensitive

materials like graphite, higher is used for higher resolution, higher brightness.

After leaving the gun, the electrons are focused by a set of electromagnetic lenses.

The first set of lenses the electron beam encounter is the condenser lens system,

which is used to control the illumination of the sample (intensity and intensity

spread). A number of apertures are used to control the coherency, convergence

angle, current, and centering of the beam.

In the conventional TEM, the beam impinges on the top sample surface as a nearly

planar wave and in STEM as converged electron probe. As the electrons interact

with the sample, they are either transmitted or scattered. Different scattering

mechanisms are used for different imaging techniques (section 5.2). As the electrons

emerge from the bottom sample surface they are again focused by the objective lens

to form an image in TEM and diffraction pattern in STEM. This image is transmitted

by the projection system, consisting of intermediate and projection lenses, onto a

fluorescent viewing screen or a CCD camera.


25

Figure 16. Basic outline of the TEM and STEM.

5.1.2 Resolution Limit and Aberration Correctors

Although the wavelength of electrons is on pm range, until recently the resolution of

the microscope was ~1 Å due to technological limitations. The resolution in a TEM is

not diffraction limited as in the case of optical microscopes, but determined rather by

non-ideal imaging characteristics (aberrations) of the lenses, instrumentation

stability, limited source coherence, non-ideal recording devices, inelastic scattering.

For the optical microscope, round lens aberrations can be compensated by

combining convex and concave lenses, however concave electromagnetic lenses do

not exist. Shortly after construction of TEM, it was noted by Scherzer [83] that

rotationally symmetric, free of charge electromagnetic lenses will always suffer from

positive spherical (Cs) and chromatic (Cc) aberrations, which cannot be overcome by

the lens design. Cs aberration results in information spread, since the electrons

scattered with shallow angles to the optical axis are focused in a different plane as

compared to the ones scattered with a high angle to the optical axis. Scherzer also

proposed different ways to compensate for Cs [84]. This led to a long development

and finally commercialization of the multipolar non-rotational symmetric lenses

which are the base for today’s Cs correctors [85-89].[85,86,87,88,89]Cs corrector produces negative

spherical aberration which compensates the positive Cs of objective lens. The image


26

Cs corrector is situated in microscope below lower objective lens, and probe Cs

corrector-above the upper objective lens (see Figure 16). The basic Cs correctors

working principle is shown in Figure 17.

Figure 17. Cs image corrector working principle.

For microscopes equipped with Cs correctors, the spherical aberration can be

compensated below the detection level, or set to any desired value, e.g. negative Cs is

used for negative CS imaging (NCSI). Aberration correction immediately reduces

delocalization of information in TEM, simplifies structure interpretation, improves

contrast, extends the resolution limit. Cs probe corrector allows smaller probes to be

formed with high current which improves the analytical signal efficiency. However,

even after Cs correction, the microscope is not free from lens aberrations, higher

order aberrations are increasingly limiting the resolution.


27

5.1.3 Arwen

By the end of October 2011, the latest generation TEM microscope, named ‘Arwen’,

was inaugurated at LiU (Figure 18b). The microscope is manufactured in Holland by

FEI company and comprises a double-corrected Titan3 platform. Arwen features the

latest generation detectors and spectrometers, which provide superior imaging and

spectroscopic characterization capabilities. Results presented in Papers 4-7 were

acquired using Arwen.

The key features:

• High-brightness FEG and monochromator capable of filtering the energy spread

of the electron beam below 90 meV. High tension can be varied in wide range

between 60-300 kV, providing flexibility in studying beam sensitive materials

at 60 kV and having high resolution and current at 300 kV [81].

• Three-lens condenser system delivers large field of view and parallel

illumination in TEM mode, as well as flexibility in varying convergence angle

and electron current in STEM mode.

• Arwen is equipped with CEOS Cs probe and image correctors. The information

transfer was evaluated to be <50 pm in TEM mode and <60 pm in STEM

mode.

• Wide pole piece gap makes sample tilt to high angle possible, also in-situ

experimental work such as tomography, indentation, or annealing can be

performed.

• Super-X EDX detector has ~5 times bigger collection solid angle, which allows

handling very high count rates, compared to standard Si(Li) detector [90].

Fast electronics allows decreasing pixel dwell times down to 10 μs for fast

mapping (see Figure 28).

• GIF Quantum post-column energy filter is super-fast EELS spectrometer

equipped with the electrostatic shutter which is feasible to acquire up to 1000

spectra/s (see Figure 35). The spectrometer can work in dual EELS mode

allowing simultaneous acquisition of low-loss and core-loss EELS regions

[91].

• Microscope environment stability is of great importance for achieving ultimate

performance and being limited by optical resolution factors of the instrument.

The critical environmental factors are: temperature stability and homogeneity,

vibration-free (mechanical, acoustical), constant humidity and screening from

stray electric fields in the microscope room. For meeting all those requests a

separate building on LiU campus was projected and built – Ångström


28

building. This is the only building at LiU which is dedicated to hosting one

instrument (Figure 18a). In order to maintain environmental stability Arwen

is encapsulated in a box (Figure 18b) and operated remotely through remote

user interface (Figure 18c).

Figure 18. (a) The Ångström building at LiU hosting (b) the FEI Titan3 microscope ‘Arwen’. (c) Microscope control room.


29

5.2 Main TEM Imaging Techniques

Image contrast appears as a consequence of different imaging mechanisms [75,77].

Examples are:

• density/thickness contrast

• diffraction contrast

• phase contrast

• Z-contrast

5.2.1 Density/Thickness Contrast

The sample atoms act as absorbing/scattering centers for the electron beam.

Density/thickness contrast dominates at low magnifications. Heavier atoms and/or

denser material absorb or scatter the electrons stronger, causing this contrast.

5.2.2 Diffraction Contrast (Bright/Dark Imaging Modes)

As the coherent electron beam passes through the sample, it experiences coherent

elastic scattering. The scattering occurs as a result of an interaction of the beam with

the periodicity of a crystal structure and is defined to a first approximation by

Bragg’s law (section 5.8). Coherent and elastically scattered electrons from the same

set of atomic planes (at the same Bragg’s angle) are brought to one diffraction spot in

the diffraction plane (back focal plane of the objective lens). In this way a diffraction

pattern is formed, where the central spot consists of the transmitted beam and other

spots originate from the diffracted beams (Figure 19).

Figure 19. The scattered incident beam is focused by the objective lens to form a diffraction pattern in the diffraction plane and the image in the image plane.


30

It is possible to generate different images by selecting a specific spot or set of spots in

the diffraction plane (transmitted or diffracted electrons). The selection is made by

the objective aperture, which is inserted in the diffraction plane. Depending on

which electrons are allowed to pass through the objective aperture, the image can be

bright field (BF), which contains the transmitted beam (Figure 20a) or dark field

(DF), which does not (Figure 20b). The objective aperture is primarily used to

increase the contrast of the image and to investigate features, where the contrast

depends on the scattering vector of selected electrons, and can be used, e.g., to reveal

dislocations of different character, local variations in strain, bending and thickness

changes in the sample.

Figure 20. Schematics of different image formation mechanisms in TEM: a) bright field and b) dark field.


31

5.2.3 Diffraction in TEM

The diffraction pattern is formed at the same time as the image, and can be viewed

on the screen if the projection system is set to transfer diffraction pattern to the

viewing screen instead of the image. Electron diffraction (reciprocal space) is a

powerful tool for crystal structure determination together with TEM imaging (real

space) from the same area. An electron diffraction pattern of a multilayer Al1-xInxN

(0≤x≤1) grown on Al2O3 substrate is shown in Figure 21.

Figure 21. Electron diffraction pattern from AlxIn1-xN multilayer grown on Al2O3 substrate. Distinct diffraction spots resulting from different composition of AlxIn1-xN layers and the substrate (indicated by ‘s’) can be seen.

The diffraction pattern provides information about the crystal structure, lattice

spacing, orientation. It is also used to orientate the sample to a low-index zone axis,

which is of key importance for HR-STEM imaging.

In Paper 1, diffraction patterns revealed the changing (0002), (1100) and (1120)

diffraction spot position of the different content Al1–xInxN layers, corresponding to

the different a and c lattice parameters. The observed variations were in agreement

with the lattice parameter change obtained by XRD.

In Paper 6, diffraction patterns were used in combination with STEM imaging and

VEELS spectroscopy to provide evidence for pure-In phase formation and material

degradation during in-situ annealing experiments.


32

5.2.4 Selective Area Electron Diffraction (SAED)

SAED is used to obtain diffraction patterns from specific sample areas. The area

selection is made by inserting the SAED aperture in an image plane. This is an

important tool to obtain information from a desired area, for example, from single

grains in polycrystalline sample, precipitate, orientation relationships between

different phases. As an example, a SAED pattern obtained from the Al2O3 substrate

and the first two layers, AlN and Al0.82In0.18N, is shown in Figure 22.

Figure 22. STEM image and SAED pattern taken from Al2O3 and the first two layers of AlN and Al0.82In0.18N (aperture position indicated by circle).

In Paper 4, SAED patterns were recorded from the twisted nanorod structure. A

hexagonal diffraction pattern with semi-arcs implies a [0001] zone axis and slight in-

plane misorientation between these twisted nanorods. By extracting intensity line

profile across one of the semi-arcs center, an asymmetric peak with a long tail

towards the specular center was obtained, revealing a gradient of lattice constant in

the twisted nanorods.


33

5.2.5 Phase Contrast (HR-TEM)

High resolution imaging is used for ‘direct’ observation of the sample lattice (atomic

column projections) in TEM mode. Phase contrast is dominant at high

magnifications (>500 kx) where the electron waves experiences a phase shift as it

interacts with the projected atomic potentials of the sample atoms. After interacting

with the sample, transmitted and scattered electron waves overlap and interfere in

the image plane, forming lattice fringes, an example is shown in Figure 23. More

than one beam is required for phase contrast imaging.

Figure 23. HR-TEM image of GaN. Line intensity profile is indicated (S-F), showing separation between the atomic columns of ~2.8 Å.

In addition to the phase shift due to the crystal potential, the wave is phase shifted

by the microscope phase factor which is a complex function. It depends on many

different parameters, such as: electron wavelength (λ), defocus (C1), different order

lens aberrations (astigmatism (A), spherical aberrations (Cs), coma (B), etc.),

scattering and illumination angles, degree of electron source coherence and is

conventionally defined by the so called phase contrast transfer function (CTF) [85],

which can be expressed as: /<� � =�> ?� @A*; B�CC��D , (11)

where B is aberration function of the microscope and ω is a complex scattering angle (C� is its complex conjugate).


34

The HR-TEM contrast dependence on different lattice spacing’s at certain

microscope settings is given by the CTF. In conventional (non-aberration corrected)

TEM aberration function mainly depends on spherical aberration and defocus:

B�CC�� E@/ECC� � EF/G�CC��@ (12)

For a microscope equipped with a Cs image corrector, Cs can be set to zero. Thus Cs is

no longer a limiting factor, which should result in zero-contrast imaging. However,

this is not the case, since the aberration function is still not cancelled out, but rather

extended in such way that higher order aberrations are limiting the resolution:

B�CC�� HIC� � E@/ECC� � E@HEC�@ � E@J@C@C� � E�H@C�� /��CC��@ �⋯ (13)

CTF serves as a measure of the microscope resolution and information limit of

different instruments. One can optimize the CTF to form broad passbands which

enable the constant transfer under similar phase shift conditions at extended

scattering angles. Galadriel and Arwen CTF’s under optimized defocus values are

compared in Figure 24 [28]. From this, one can easily see that HR-TEM images

obtained by Arwen will contain more information since the CTF is extended to

13 nm-1 and for Gadriel to 8 nm-1. The contrast interpretation in HR-TEM images is

easier for Arwen images as well, since the CTF does not show any contrast reversals

and oscillations, as compared to Galadriel.

Figure 24. Contrast transfer function of Galadriel and Arwen.


35

In Paper 3, HR-TEM lattice resolved imaging was used to investigate AlInN

nanorods in cross-sectional geometry. AlInN nanorods revealed a 23o misorientation

between the c-planes in the rod core and shell.

In Paper 4, AlInN twisted nanorods curved lattice planes were investigated by HR-

TEM imaging.

5.2.6 Z-Contrast Imaging

STEM is a TEM operation mode in which a fine electron probe is formed and

converged on the sample into a small point. The sample is scanned by the probe and

each pixel of the STEM image is generated as the scattered intensity at

corresponding point is recorded. STEM images can be recorded by means of

different detectors: bright field (BF), annular dark field (DF) and high angle annular

dark field (HAADF). The angular collection range of the scattered electrons is

different for each detector (Figure 25a).

Figure 25. (a) Basic STEM image recording principle by using BF, DF and HAADF detectors (b) Z-contrast STEM-HAADF image obtained from InGaN/GaN QW structure and (c) corresponding intensity profile. HAADF detector is the primary choice for STEM imaging. The amount of scattered

electrons onto the HAADF from each point primarily depends on the local atomic

scattering power, which is defined by the Rutherford scattering cross-section of the

present elements, and at high angles this is the dominating contrast mechanism [92].

As a result, intensity in HAADF-STEM images is sensitive to atomic mass number

(Z) and sample thickness (t) [93] and intensity (I) is proportional to their product:


36

L~N@O. (14)

Higher Z results in more scattered electrons from the atomic columns. The image is

rarely formed by pure mass-thickness contrast (incoherent scattering from atoms),

but contains contributions from diffraction contrast (coherent scattering from lattice),

depending on the camera length (magnification in the reciprocal space). With

smaller camera lengths, only electrons with higher scattering angle reach the

HAADF detector, which significantly reduces the coherent scattering contribution to

the image.

The size of the electron probe defines the spatial resolution in the STEM. Probes can

be made smaller by opening the aperture while also correcting for spherical

aberrations (Cs probe correctors). The major benefit of Cs corrected STEM is HR-

STEM imaging combined with analytical information [94,95]. The use of Cs probe

correctors allows generating smaller beams with more current and may result in

damaging sample, which in turn affects the interpretation of the investigated

structure.

HR-STEM strong Z-contrast image and corresponding STEM-HAADF intensity

profile from InGaN/GaN QW structure is illustrated in Figure 25b and 25c,

respectively. As electron probe scans across InGaN QW the image intensity is much

higher due to presence of heavier In in the structure. Asymmetric QW shape is also

clearly visible in the intensity profile (Figure 25c).

In Papers 2, 4-7, STEM and HR-STEM imaging was extensively employed to study

AlInN multilayers and InGaN QWs in combination with VEELS and electron

diffraction.


37

5.3 Analytical Methods in the STEM

5.3.1 High Energy Electron Interaction with Material

The high energy electrons impinging on the sample may be transmitted or scattered.

When scattered, the scattering event may be elastic or inelastic. After the scattering

event the electron waves may be either coherent or incoherent with other wave [96].

The basic types of interactions with a single atom are shown in Figure 26.

Figure 26. High energy electron interaction with material.

• Electrons can be scattered coherently or incoherently. Elastic scattering is

typically coherent at low angles (when scattered by a periodic array of atoms)

which is used for electron diffraction. Scattering becomes predominantly

incoherent at higher scattering angles (detected by HAADF).

• Elastic scattering is defined as an event where there is no change in the

electron energy (Figure 26–1,3,4), but the electron may changes direction from

the initial path. If the electrons pass closer to the atomic core (Figure 26–3), the

change of direction is much larger due to Rutherford scattering (high angle

elastic scattering). This phenomenon is used primarily for STEM imaging

(section 5.2.6). Electrons that pass far from the atom core and interact with the

1. Transmitted electrons

2. Inner shell inelastic scattering

3. High angle elastic scattering

4. Back-scattering 5. Valence electron

inelastic scattering

I. Electron ejection from inner shell

II. Emission of X-rays


38

electron cloud (low angle elastic scattering) form the basis of the coherently

scattered electrons, which contribute to the diffraction pattern and generate

strong TEM image contrast. The elastic scattering intensity is determined by

the atomic scattering amplitude.

• In the event of inelastic scattering the incident high energy electrons transfers

some energy to the sample atoms by exciting outer shell and/or core electrons

to higher levels. Measuring the energy loss of the high energy electrons forms

the basis for EELS analysis (Figure 26–2,5) (section 5.4). Atom deexcitation

occurs by emission of either an X-ray photon which forms the basis for EDX

analysis (Figure 26–II), or an Auger electron (section 5.3.3).

5.3.2 STEM Analysis

The basis for retrieving analytical elemental information in STEM is the inelastic

scattering of fast electrons by the sample atoms, and the resulting different

measurable physical signals (see Figure 27).

Figure 27. Interaction between electron beam and material.

Generally, not all of the signals are used. In STEM, the typical signals which are

recorded are EDX and EELS. The common principle for analytical STEM is to focus


39

the electron beam into a small probe and perform a line or area scan of the sample,

or keep the beam at one position of interest. For each scanned pixel the spectrum

(EDX and/or EELS) is recorded and a single spectrum or a spectrum image (SI) is

formed (section 5.4). These can later be used for, e.g., compositional analysis of the

investigated region. EDX analysis, in general, is more efficient in collecting

information about heavier elements, while EELS is more sensitive to lighter ones.

Together with EELS and EDX, STEM is capable to deliver information about

composition, bonding, thickness. from each data point, making it an efficient

analytical tool with nm, or even better, resolution.

5.3.3 Energy-Dispersive X-ray Spectroscopy (EDX)

STEM is frequently combined with EDX analysis. The recorded EDX signal gives

information about atoms present in the sample. The signal is affected by elemental

fluorescence yield, sample orientation, detector response, thickness, making precise

elemental quantification challenging. An example of an EDX measurement from a

series of InGaN/GaN QWs is shown in Figure 28. In this thesis, EDX was used as a

comparative method in Papers 3-4 in combination with VEELS studies.

Figure 28. Combined STEM and EDX spectroscopy. (a) STEM image of InGaN/GaN QWs, (b) EDX area map showing In-Lα and Ga-Kα distributions together with the binned In line profile across the structure, (c) Single EDX spectrum acquired from the InGaN QW layer.


40

5.4 Electron Energy Loss Spectroscopy (EELS)

The EELS spectrometer is dedicated for measuring the amount of energy lost (∆E)

per electron in the primary beam (E0) as the electron interacts inelastically with the

sample (see Figure 27). The EELS spectrum can give insight into the composition,

bonding environment and properties of the sample under investigation [96-99].[96,97,98,99]The

TEM can be equipped with a spectrometer which is integrated into the column (in-

column filter) or mounted under the projection chamber (post-column filter). The

electrons entering the EELS spectrometer are dispersed by a magnetic prism

according to the amount of energy lost in the scattering process (see Figure 29).

Higher electron energy loss results in higher deflection angle. The EELS

spectrometer itself is a complex device containing a number of electromagnetic

lenses and deflectors, allowing precise manipulation and focusing of different

energy electrons onto the recording device [91].

The EELS spectrum is captured by a CCD camera, which records different energy

ranges depending on selected dispersion.

Figure 29. Working principle of a post-column EELS spectrometer.


41

Shape and intensity of the EELS spectrum is a characteristic of the elements present

in the investigated structure. There is a number of experimental parameters which

are essential for EELS measurements and data evaluation such as primary beam

energy (E0), energy spread of the primary beam (see Figure 32), convergence semi-

angle of the probe (α), acceptance semi-angle (β) of the spectrometer (see Figure 29),

energy dispersion of the spectrometer, probe size.

The primary beam energy is usually kept constant and is set by the acceleration

voltage of the microscope. The characteristic scattering cross-section and scattering

angle for different elements depends on E0. The energy spread of the primary beam

depends on the gun type and if a monochromator is available and in use. A small

energy spread is crucial for studying fine details of the EELS spectrum as well as a

reliable deconvolution process. The convergence semi-angle α of the probe

determines the angular range of electrons which contribute to the excitation of the

sample as well as the spatial resolution. α is set by the condenser apertures and

lenses. The acceptance semi-angle β defines angular range of electrons which can

enter the spectrometer. β is critical when evaluating the EELS spectrum since the

characteristic scattering angle of different elements is proportional to the energy loss.

Also, with increasing Z, the scattering angle increases. With well chosen β most of

the scattered signal will be collected and a high signal to noise (S/N) ratio will be

achieved. β can be controlled by acceptance apertures of EELS spectrometer and

camera length.

EELS experimental parameters are preferably kept constant for comparative

quantitative analysis. In this thesis, two instruments were used for performing

VEELS analysis with different sets of the experimental parameters which are

summarized in Table 3.

Table 3. Typical VEELS experimental parameters.

Experimental conditions Galadriel (Tecnai F20) Arwen (Titan3)

Acceleration voltage 200 kV 300 kV

Energy resolution 0.8 eV 0.2 eV

Convergence semi-angle (α) 10 mrad 25 mrad

Acceptance semi-angle (β) 1 mrad 8 mrad

Energy dispersion 0.05 eV/channel 0.025 eV/channel

Electron probe size ~1 nm ~1 Å

Dwell time per px 0.03 s 0.005 s


42

EELS spectra are typically recorded using the spectrum imaging (SI) method which

allows area mapping and spatially resolved EELS data. Although in Papers 1-2

single spectra are analyzed, the spectra were extracted from recorded SIs by

averaging to a single spectrum or a line. This provides improved S/N as discussed

later in section 5.4.5. SIs can be visualized by a three dimensional (3D) data cube

containing spatial and energy coordinates, shown in Figure 30.

Figure 30. EELS data cube representing the basic principle of SI.

In SI the electron probe is scanned pixel by pixel across the region of interest and a

single EELS spectrum is recorded from each pixel. Recorded data is a subject to

extensive post-processing. For example, line or singe spectrum can be extracted and

improved S/N by binning or using mathematical algorithms. Same SI principles are

also applied for EDX measurements.


43

5.4.1 Electron Energy Loss Spectrum

A typical EELS spectrum recorded from AlN is shown in Figure 31. The spectrum

can be divided into three main regions: zero, low and core loss, depending on the

energy loss of the electrons. Each region reveals different information about the

sample properties, discussed in more detail in the following chapters.

Figure 31. Typical EELS spectrum recorded from AlN.

5.4.2 Zero-Loss Region

Zero-loss region contains zero-loss peak (transmitted electrons). These electrons do

not lose energy upon interaction with the sample. This is, however, not entirely true

since the loss of energy when creating phonons, Auger electrons, etc. is often smaller

than the spectrometer resolution. The full width at half maximum (FWHM) of the

zero-loss peak in vacuum serves as a measure of the system resolution. The system

energy resolution depends primarily on the initial electron energy spread,

monochromator settings (if available) and the accuracy of the spectrometer as the

total convolution. The system energy resolution in Galadriel was measured ~0.8 eV

and Arwen ~0.2 eV for typical VEELS experiments, as shown in Figure 32.

A better resolution in Arwen is achieved by using a monochromator, its main task is

to filter the beam by removing too slow or too fast electrons, and to make the energy

distribution more narrow and symmetric.

In general, the zero-loss peak provides useful information only when it is compared

with the rest of the spectrum (section 5.4.3).


44

Figure 32. Aligned and normalized zero-loss peaks for Galadriel with FWHM ~0.8 eV and Arwen – FWHM ~0.2 eV.

5.4.3 Low-Loss Region and Valence Electron Energy Loss Spectroscopy

The low-loss EELS (also called VEELS) region contains information about a high

energy electron beam interaction and inelastic scattering by valence electrons (Figure

26-5), as well as characterizes the optical properties and dielectric function of the

material [100]. This region is dominant by bulk plasmon losses and inter-/intra-band

transitions (<50 eV) [101-106].[101,102, 103,104,105,106]A plasmon is a collective oscillation phenomenon

described as a quasiparticle of a certain energy. Furthermore, the low-loss EELS

region can be divided into very low-loss region containing: interface and surface

plasmons, Cherenkov losses, bandgap information. Analysis of the bulk plasmons is

an indirect way to characterize the properties of the sample.

Although VEELS region has not been extensively used for analytical purposes as

compared to the ionization edges (core-loss region), it has been applied for

identifying different phases in materials, through investigation of the shape of bulk

plasmon peak [107], material depletion at grain boundaries [108], precipitates [109]

and plasmon energies were even correlated to mechanical properties [110].

There is an increasing interest in using VEELS as a characterization tool for bandgap

measurements [111,112], surface plasmon excitations [113-115], [113,114,115]phase separation

[116], interface abruptness [117], ultra-thin films [118], graphite [119], quasicrystals

[120], multilayers [121], nanowires [122,123], nanoparticles [124], and correlating

different physical properties at the nanometer scale [125].


45

This thesis concentrates exclusively on exploring the bulk plasmon properties as a

tool for material analysis and will be described in more detail.

The bulk plasmon peak in the EELS spectrum stems from the plasmon resonances,

that are excited in the material when the high energy electron beam interacts with

the weakly bound valence electrons. A simplified model of visualizing bulk plasmon

excitations is shown in Figure 33. The material is considered to be in equilibrium and

have ‘fixed’ atoms – ions and quasi-free electrons. The high energy electrons passing

though such material easily interact with the quasi-free electrons and distort the

equilibrium state by creating areas of excess positive and negative charges, which try

to compensate this imbalance and set themselves in collective oscillation motion. The

quasi-free electrons oscillating in the bulk produce the so called bulk plasmons,

which are treated as quasi-particles of certain energy.

Figure 33. Schematic illustration of distorted quasi-free electron plasma when high energy electrons pass through the material and generate volumes of positive and negative charge.

The energy of the bulk plasmon loss primarily depends on the valence electron

density. Bulk plasmon oscillations run through the crystal as a longitudinal

collective electron wave of loosely bound electrons with a characteristic frequency,

creating volumes of varying electron density. The plasmon oscillations are quickly


46

damped, in order of femtoseconds, and are localized to a few nm. The bulk plasmon

peak is the next most intense feature in the EELS spectrum (see Figure 31), providing

a strong signal which can be efficiently recorded and carries characteristic

information about the investigated material. Bulk plasmon loss electrons are

strongly scattered forwardly and, as a result of the narrower angular distribution,

even for a small acceptance angle most of the signal is easily collected.

Analyzing the intensity of the zero loss peak together with the intensity of the

inelastic scattering contribution, mainly from the low-loss EELS region, is a well

established and straightforward procedure to estimate the relative sample thickness.

Poisson statistics provide an expression for number of n (integers) plasmon

excitation probability (Pn) in a sample of the thickness (t):

�� E�! QR;S� =&TU � �V�T , (15)

where In is the number of counts in the nth plasmon peak, It is the integrated number

of counts throughout plasmon spectrum, λ is the mean free path.

By setting n=0, a measurement of the inelastically scattered (low-loss region) versus

unscattered (zero-loss peak) intensities gives an indication of the sample thickness

by using the log-ratio method [75]. This is performed by taking ratios of the

integrated intensities of the entire spectrum and the zero-loss peak:

R; � WX �T�' , (16)

where t is the sample thickness, λ – the mean free path, IT – the integrated spectrum

area, and I0 is the area under the zero-loss peak.

Figure 34 shows a typical VEELS spectrum recorded from an AlN sample at

different thicknesses and normalized with respect to zero-loss intensity. With

developing sample thickness inelastic scattering contributions increase – the bulk

plasmon peak height increases. The sample thickness does not affect the position of

the bulk plasmon energy, hence more signal can be collected by recording VEELS

from thicker areas. Multiple scattering slightly affects the shape of the bulk plasmon

peak and, for data analysis, it should be removed by deconvolution procedures,

discussed more in detail in section 5.4.5.


47

Figure 34. Low-loss EELS spectrum recorded from different thickness areas of AlN.

In order to describe the bulk plasmon energy, a mathematical description of valence

electron oscillations is given by the Drude model [21], which gives the free electron

plasma energy. In this model valence electrons are treated as free particles, and

damping in the electron plasma is not taken into account. The only parameter

influencing the plasma oscillations is the valence electron density. If the number of

valence electrons is constant, only the lattice parameter will affect the plasma

frequency. This model works well for metals.

In mathematical treatment [75,100,126], if the beam of high energy electrons is

considered as a time varying electric field which causes the ‘quasi-free’ electron

movements, the equation of motion must be satisfied:

� YZ#YRZ ��Г Y#YR � �=�, (17)

where m is electron mass, x – displacement, Г – damping constant, e – electron

charge, and E – oscillation field.

For an oscillating local electric field, the solution of this equation is given by:

� � \]̂_Z`*Г_ , (18)

The ‘quasi-free’ electron displacement produces polarization in the medium:

� � �=X� � "IB� , (19)

where n is number of electrons per unit volume, and B – electronic susceptibility.


48

From the equation (19):

B � Ca@ Q E_Z`ГZ � &*Г_∙�_Z`ГZ�S . (20)

The response of the medium by the induced electric field is governed by the complex

dielectric response function:

" � "E � c"@ � 1 � B , (21)

where ε is the dielectric function, ε1 is its real part, and ε2 – imaginary part.

Electron losses can be described by differential cross-section characteristics of the

bulk loss function in the free electron approximation:

YZdYRZ ~lm?� Ef�g�D , (22)

where YZdYRZ is the differential cross-section.

In the free electron model the dielectric function of a material is given by:

"�C� � 1 � Ca Q E_Z`*Г_S , (23)

where ωp is the plasma frequency.

The frequency of the bulk plasmon oscillations according to the Drude model can be

expressed as:

Ca � h�iZj'k , (24)

where m is the electron effective mass, n – the valence electron density per unit

volume and .I – the permittivity of free space.

Forcing quasi-free electrons to oscillate is equivalent to creating a particle with

energy Ep:

�a � lCa . (25)

This model provides a reasonably accurate estimate of the plasma frequency for

many solids, except for transition metals and rare earth elements, due to their more

complex electronic structure.


49

However, in other crystals additional factors affect the appearance and shape of the

bulk plasmon energy such as band structure, momentum transfer, chemical bonds.

Moreover, a ‘plasmon’ response can be observed in insulators, showing that the

Drude model does not account for all phenomena present in materials. More

advanced Drude-Lorentz model, Lindhard models, and other approximations can be

used to account for additional factors mentioned above [126].

Alloying different elements alters the valence electron density in the system, which

affects the bulk plasmon peak shape and position. A peak shift in binary compounds

is commonly observed as linear empirical relation in the form:

�a�� a�0� � � QYmnY# S , (26)

where Ep(x) is bulk plasmon energy of the alloy, Ep(0) – bulk plasmon energy of the

one of the constituents, x – fraction of the alloy, and YmnY# – slope of linear dependence.

In Paper 1, a linear relation was experimentally established for the ternary AlxIn1-xN

system by investigating layers of different composition:

�a�HW#LXE&#o� � 14.78 � 5.69� . (27)

In Paper 2, it was demonstrated by a combination of experimental and simulations,

that the VEELS spectrum is affected by the strain state in group-III nitrides.

In Papers 3-5, VEELS was employed as the main tool for nanostructure

characterization on the nanoscale. High resolution bulk plasmon energy surface plot

of high-In content InGaN/GaN QW is shown in Figures 35. The dimensions

represent area (x,y) and Ep (z). The sharp onset of the well can be seen along with the

slower recovery and additional features inside QW (for more details see Paper 5).

In Papers 6-7, the decomposition processes and thermal stability of different

composition AlxIn1-xN layers and AlxIn1-xN/AlN multilayers were investigated by a

combination of monochromized VEELS, STEM imaging, and electron diffraction

during in-situ annealing from 750 oC to 950 oC.


50

Figure 35. Bulk plasmon energy surface plot of high-In content InGaN/GaN QW.

5.4.4 VEEL Spectrum Simulations

As discussed previously, VEELS provides complex information about the dielectric

response of a material, its composition and strain. For this reason, modeling is vital

in order to increase the understanding of experimental VEELS results [127]. To

retrieve the energy loss function and the optical properties of a material by

theoretical means, full potential simulations of the dielectric function can be

performed. One software package for such simulations is Wien2k, which is based on

quantum mechanics using density functional theory (DFT) [128], within the

generalized gradient approximation (GGA). In this package, the interaction between

electrons is treated as a series of one-electron Kohn-Sham partial differential

equations. The Wien2k simulation package employs the linearized augmented plane

wave (LAPW) method and has been established as one of the most exact methods to

compute the electronic structure of solids.

In Paper 2, Wien2k was employed to calculate effect of the strain on VEELS response

in AlN layers. The optical properties were calculated using the OPTIC subroutine in

Wien2k, which yields the dielectric function from which the energy-loss function is

obtained. Since AlN has the wurtzite structure which is anisotropic, the dielectric

function is described by a tensor. Because of this, two components (xx and zz) are

calculated simultaneously. For this investigation the xx component is of main

interest, as it is excited by the electron beam in the cross-sectional sample. For most

calculations of the loss function, a Gaussian broadening of only 0.1 eV was applied

to achieve a high level of detail in the energy-loss spectra. For final comparison of

the calculated and experimental spectra, a broadening of 1.0 eV was employed in


51

order to reflect the energy resolution of our STEM at the applied experimental

conditions in Galadriel.

As an example, the simulated VEELS spectra of AlN, where the unit cell volume was

linearly increased while a/c ratio was kept constant, are shown in Figure 36.

Figure 36. Simulated VEELS spectra of AlN by changing unit cell volume (-3% to +3%) for xx component and keeping a/c ratio constant.

5.4.5 VEELS Data Post-Processing

The EELS spectrum is sensitive not only to experimental parameters as discussed in

section 5.4, but also to data post-processing routines. Keeping identical experimental

parameters and post-processing routines allows a generation of reliable VEELS data

and for performing quantitative analysis.

Data post-processing starts with fitting zero-loss peaks in each pixel of SI by a non-

linear least-squares (NLLS) fit and correcting for energy drift. In order to improve

data quality by minimizing S/N ratio and enabling bulk plasmon peak position

determination with high accuracy, binning should be applied. An example of a

single spectrum and 300 binned spectra is given in Figure 37.


52

Figure 37. Comparison of a single spectrum and noise reduced spectrum obtained by averaging 300 spectra.

VEELS spectrum is preferably recorded from a sample where it can be treated as a

single scattering event; for bulk plasmons optimum is around 1 mean free path

thickness of the sample. Since in most cases, plural scattering contributions are still

present, VEELS spectrum must be deconvoluted by the Fourier-log method. This is

done by using routines available in the Digital Micrograph software. As typical for

all data treatment procedures, plural scattering removal routines should be used

with caution, since it can introduce artifacts in the spectrum, e.g., in the case of high

noise level. Finally, considering a single Gaussian function of the VEELS spectrum,

the bulk plasmon peak is again fitted by NLLS curve-fitting method in a ~2 eV

window centered around the most intense part of the plasmon peak in order to

determine the bulk plasmon energy (Figure 38).

Figure 38. Raw VEELS spectrum is deconvoluted from plural scattering and fitted with Gaussian shape peak to determine the exact bulk plasmon energy in AlN.


53

5.4.6 Core-Loss Region

The core-loss region (ionization edges with fine structure) contains information

carried by the electrons interacting with core shell electrons of a specimen atom,

causing their excitation to higher unoccupied levels, in the range from 50 eV up to

>>1000 eV. These excitations appear in the form of edges in the EELS spectrum. The

signal intensity compared to the low-loss region is weaker due to the smaller

ionization cross-section. As an example, characteristic N K-edge evolution in

different composition Al1-xInxN layers (0≤x≤1) is shown in Figure 39.

Figure 39. N (K-edge) of different composition Al1-xInxN layers.

The fine features of the spectra are sensitive to the Al1-xInxN alloy composition. The

fine structure of the edge provides information about the chemical environment of

the atoms. While the fine structure is usually significantly different, it can be used to

determine the compound (from a library of fine structures). Core-loss EELS is the

preferred technique for characterizing light elements present in the sample, like O, C

or N, etc.


54

5.5 In-Situ TEM Experiments

TEM provides capabilities to characterize samples with high spatial resolution

imaging together with reciprocal space and chemical information. This static analysis

is performed on samples which are synthesized or processed before they are

analyzed in TEM. Possibility to follow the sample evolution inside the microscope

under changing conditions enables the study of dynamic processes in materials with

high accuracy and provides additional information about the physical mechanisms

at the atomic level. The samples can be subjected to different triggers, such as

temperature, gas, strain, which will have an effect on the sample structure. This is

usually achieved by using dedicated specimen holders (annealing, indentation) or

specialized microscopes (environmental TEM). As a result, the sample will react to

the applied process and this can be followed live though imaging, diffraction and

spectroscopy techniques. The electron beam current effect on electron dose sensitive

materials can be regarded as the simplest in-situ TEM experiment.

In this thesis, in-situ annealing experiments were performed using a furnace type

double tilt heating holder (Gatan Model 652) shown in Figure 40. The heating holder

allows investigation of phase transformations, material disintegration, at

temperatures up to 1000 oC.

Figure 40. Double tilt heating holder tip.

Some concerns apply to high temperature annealing experiments. The sample

support material (grid) should withstand high temperature (titanium, molybdenum)

and not react with the heating furnace (tantalum). The same applies to the sample

itself. A high temperature glue (e.g., Gatan G1) must be used for traditional cross-

sectional sample preparation (section 5.6.1).


55

In Papers 6-7, the thermal stability and decomposition paths of Al1-xInxN layers were

investigated by STEM imaging, electron diffraction, and VEELS during in-situ

annealing from 750 oC to 950 oC. STEM images of Al0.3In0.7N/AlN multilayer structure

evolution during in-situ annealing experiment are shown in Figure 41a-d as time

series.

Figure 41. STEM images of AlInN/AlN multilayer evolution during in-situ annealing experiment.


56

5.6 TEM Sample Preparation

For bulk samples to be used in TEM analysis the thickness requirement is the most

critical, since sample must be electron transparent. This is achieved by reducing

sample dimensions from mm to μm and then to nm. Typical requirements for a

‘perfect’ TEM sample: thin over a large area, contains little or no artifacts from the

sample preparation process, represents the entire sample, clean and free from

contamination products, preferably conductive and non-magnetic. If the sample is

thick and has experienced considerable surface damage, dynamic scattering and

multiple interference might complicate the interpretation of the TEM results.

The choice of the sample preparation method depends on the sample itself (single

crystal, biological, nanoparticles, homogeneous etc.) and the desired projection (zone

axis). The typical zone axes in hexagonal crystals are parallel to the c-axis (plan-

view), and perpendicular to the c-axis (cross-section), see Figure 4.

5.6.1 Conventional Cross-Sectional Sample Preparation

Most TEM samples studied in this thesis were prepared conventionally by using

‘sandwich’ approach (few days of work). The major assumption done using this

method – the sample is homogeneous, since TEM sampling volume is rather small.

Detailed ‘sandwich’ approach procedure is illustrated in Figure 42. Initial sample (a)

is cut with low speed diamond saw into small 1.8 mm x 0.8 mm pieces (b) mounted

into Ti grid (c) which has standard 3 mm diameter fitting into microscope holder.

Figure 42. TEM sample preparation procedure: initial sample (a) cut to small pieces (b) and put in Ti grid (c) which is glued (d) polished and ion milled from both sides until final TEM sample (e) is ready, (f) overview TEM image from this sample.

The Ti grid is glued for ~2 h at 180 oC by using Arelite glue (d). In the case the

samples are subjected to in-situ annealing treatment, high temperature glue (G1)

should be chosen instead. The sample is mechanically polished by diamond

polishing papers with different grain sizes (e). The polishing is typically finished


57

when the sample thickness is ~50 μm. The final sample polishing is done by argon

ion milling (PIPS-Gatan) at 5 keV. The final step in milling is performed at low

energy (2 keV), which reduces the amorphous layer on the sample surface. After all

these treatment, sample is finally ready to be inspected in TEM (f).

5.6.2 TEM Samples in Few Minutes

TEM sample preparation is commonly accepted as long, joyful, and complicated

process. However, if the samples are in form of powder or nanostructures, like

nanorods – the TEM sample preparation is rather straightforward. Powder or

substrate-free nanorods (removed by scratching) are dispersed on Cu grid mesh

which contains amorphous carbon layer acting as support for particles. This type of

sample preparation was used to study individual AlInN nanorods in Papers 3-4.

5.6.3 Focused Ion Beam (FIB) Sample Preparation

FIB is another TEM sample preparation method applied in Paper 1 (B-series) and

Paper 4 (plan-view) by using FIB Carl Zeiss Cross-Beam 1540 EsB system. This

method was chosen since some samples were too small for conventional sample

preparation procedure.

The main advantage by using FIB is the selectivity of area from which the TEM

sample could be prepared. The FIB working platform is based on the scanning

electron microscope principle, with an additional Ga-ion column, which is used

mainly for sample milling and deposition. Gas injection system (GIS) is used for

depositing protective layer and manipulator is needed for sample lift-out (see Figure

43a). The disadvantage with FIB is that sample surface is affected by implanted Ga

ions. Additionally, FIB operation cost is rather high.

Standard FIB sample preparation procedure starts with identifying area of interested

by using SEM. This area is covered by e.g., platinum (Pt) layer where typical

thickness of Pt layer is around 1 μm. In order to lift out lamella protected by Pt,

trenches are milled using high ion current (~2 nA) around this lamella. For lift-out

procedure, a manipulator is inserted and welded to lamella by Pt (see Figure 43b).

Lamella is cut loose from the bulk sample and placed on half-moon Cu grid, where

the final thinning to electron transparency is performed.


58

Figure 43. (a) FIB system basic scheme and (b) SEM image of a sample ready for lift-out procedure.


59

5.7 Rutherford Backscattering Spectrometry (RBS)

Rutherford backscattering spectrometry is a routine technique for compositional

analysis on macroscopic scale of thin films [129]. The investigated material is

bombarded with high energy light ions (e.g., He), which are incident almost

perpendicular to the surface of the analyzed sample. The He ions interact with atoms

in the sample. Consequently, some ions are backscattered from the sample atoms

through elastic collisions. Compositional analysis is based on the interpretation of

the energy spectrum of backscattered ions through conservation of momentum. The

energy loss of backscattered ions depends on the elements present and the energy

dependent scattering cross-section. Experimental and simulated spectra of analyzed

Al0.66In0.34N sample are shown in Figure 44.

Figure 44. Experimental and simulated RBS spectra from Al0.66In0.34N sample grown on Al2O3 substrate with AlN buffer layer. In order to determine the elemental composition of the AlInN, 2.0 MeV 4He+ ions

were used at an incident angle of 7o off from the surface normal to avoid channeling

effects in the crystalline structure [130], and back-scattered 4He+ ions were detected

at a scattering angle of 172o. Experimental data was analyzed using the SIMNRA

code (version 6.05) [131] to obtain the exact film composition.

In Paper 1, the compositional information obtained by RBS was correlated with Ep

values and used for calibration as a function of alloy composition.


60

5.8 X-ray Diffraction (XRD)

X-ray diffraction is a result of the wave nature of X-rays (λ=1.54 Å, Cu Kα1), which

allows them to diffract and interfere constructively upon interacting with the

periodic structure of the crystal. As an example, the semiconductor crystal exhibits a

lattice periodicity of a few Å (a=3.11 Å and c=4.98 Å for AlN). Diffracted waves

provide information of the crystallographic structure, orientation, composition,

strain state, etc. of the materials [132-134].[132,133,134]Bragg’s law describes the condition for

constructive interference, i.e., the maximum intensity of scattered X-rays from the

crystal:

Xλ � 28sinx , (28)

where n is an integer number, λ – the wavelength, d – the lattice spacing and θ – the

diffraction angle.

Bragg’s law states that the maximum(-a) of the scattered intensity is(are) found

when the incident and scattered angles are θ for the periodic lattice spacing d (in the

crystal). Since λ and θ in an experimental setup are known, d can be calculated. This

is schematically illustrated in Figure 45. Fulfilling Bragg’s law is, however, not

enough for obtaining scattered intensity, since the scattering intensity is also related

to the structure factor of the investigated material. The structure factor takes into

account atomic positions and scattering powers in the unit cell, making some

reflections appear stronger, weaker or be completely forbidden.

Figure 45. The schematic principle of X-ray diffraction according to Bragg’s law is shown

in the HR-STEM image, indicating lattice spacing d as well as incident and diffraction

angles θ.


61

In the simplest XRD experiment incident and detection angles are varied

simultaneously and X-ray intensities recorded. This is the basis of a θ/2θ

measurement, which is a routine method for identifying crystal phases and

extracting lattice spacings parallel to the sample surface. As an example, a θ/2θ

measurement from Al0.24In0.76N(0002) grown on an AlN(0002) buffer layer is shown

in Figure 46, with distinct peaks representing different lattice parameters.

Figure 46. θ/2θ XRD measurement of Al0.24In0.76N(0002) grown on an AlN(0002) buffer layer.

In Paper 1, the c lattice parameters were obtained from θ/2θ XRD measurements and

were correlated with the bulk plasmon energy values and RBS compositional data.

In Paper 3, obtained c lattice parameter was used to estimate composition as

determined by Vegard’s rule using bulk AlN and InN lattice parameters [135].

In order to evaluate the crystal quality, strain, relaxation, coherency, in-plane and

out-of-plane lattice parameters, so called, reciprocal space maps (RSM), can be

recorded. RSM scans record continuously varying θ and ω to form an area image

around given reciprocal lattice points. The desired information is extracted from

position, shape and orientation of those reciprocal space peaks.

In Paper 2, the a and c lattice parameters were obtained from RSM measurement by

examining the symmetric (0002) and asymmetric (1015) reflections and were used to

estimate the unit cell volume and strain state of AlN layers grown on different


62

substrates and growth conditions. RSM representing the symmetric (0002) and

asymmetric (1015) reflections of AlInN multilayer samples are shown in Figure 47.

Figure 47. RSM from AlInN multilayer sample showing (0002) and (10��5) reciprocal lattice points.

Summary and Contribution to the Field

63

6. Summary and Contribution to the Field

The research presented in this thesis is focused on exploring and applying VEELS

capabilities for characterization of group III-nitride semiconductors with highest

spatial and energy resolution. VEELS is an indirect method to access the material

composition and strain: both experimental and theoretical investigations were

performed to obtain this information (Papers 1-2).

In the first study (Paper 1), a standard-free method to retrieve compositional

information of AlxIn1-xN thin films by employing STEM-VEELS was demonstrated.

Two series of samples were grown by MSE and MOCVD, covering together full

composition range 0≤x≤1. Complementary compositional measurements were

obtained using RBS and the lattice parameters were obtained by XRD. It was shown

that bulk plasmon energy follows a linear trend with respect to composition and lattice

parameter between the alloyed constituents from AlN to InN. This allows a

straightforward compositional analysis by a single measurement of the bulk

plasmon energy.

The effect of strain on the low-loss response of III-nitrides was evaluated

experimentally by STEM-VEELS and theoretically by full potential simulations using

Wien2k (Paper 2). Three AlN layers were grown by MSE using different growth

schemes. AlN layers were found in relaxed, tensile and compressive strained states

as was shown by RSM. The different strain states were the outcome of different

growth conditions with substrates, growth temperature and thickness. The tensile

strained AlN resulted in a red shift (-0.17 eV) of the bulk plasmon peak position,

while the compressively strained was blue shifted (+0.25 eV) with respect to the

strain-free AlN (20.46 eV). To support the experimental findings, a number of

simulations were performed, where the strain state of AlN as well as GaN and InN

was continuously changed. Experiments and simulations revealed that the bulk plasmon

peak position varies linearly with unit cell volume (0.156 eV per 1% volume change). It was

concluded that strain should be taken into account as an additional factor when

interpreting VEELS data.

The above methodology was applied in the investigation of confined structures such

as nanorods and InGaN/GaN QWs (Papers 3-5).

In Papers 3-4, spontaneously formed self-assembled AlInN core–shell nanorods and

twisted nanorods were realized by MSE method. The grown structures exhibited

hexagonal cross-sections with preferential growth of the c-axis along the rod-length

Summary and Contribution to the Field

64

direction. The microstructure and compositional homogeneity in cross-sectional and

plan-view geometries were examined by STEM-VEELS and EDX mapping. The

compositional analysis showed higher In concentration in the core of the nanostructures than

in the surrounding shell, revealing phase separation which occurred during the growth.

The early stages of InxGa1-xN/GaN QW growth for In-reduced conditions were

investigated in Paper 5. The QW thickness and composition was varied during the

growth. The high spatial resolution analytical information was obtained by

monochromated STEM-VEELS spectrum imaging. It was found that QW beyond a

critical thickness (> 8 nm) and composition (x > 0.08) develop QD like features inside the

well as a consequence of Stranski-Krastanov-type growth mode, and QDs were buried by

continued growth of GaN while residual In was incorporated in the structure.

Finally, the thermal stability and degradation mechanisms of Al1-xInxN layers with

different In content and different periodicity AlInN/AlN layers were investigated

(Papers 6-7).

In Paper 6, the thermal stability of Al1-xInxN (0≤x≤1) layers was investigated by

combination of STEM imaging, monochromated VEELS and electron diffraction

during in-situ annealing from 750 oC to 950 oC. The results show two distinct

decomposition paths for the In-richest layers that independently lead to transformation of the

layers into a porous, nanocrystalline, In-deficient structure. The In-richest layer

(Al0.28In0.72N) decomposes at 750 oC, and the decomposition process is initiated by

forming In clusters at the grain boundaries. VEELS mapping clearly indicated

clustering of In with the presence of a sharp resonance peak at 11.4 eV. For the

Al0.41In0.59N layer, continues In desorption was initiated at 800 oC, while no In clusters

were observed. Al-rich Al1-xInxN layers resisted the thermal annealing.

Paper 7 reports the spinodal decomposition, as observed in-situ by STEM-VEELS,

during thermal annealing in AlxIn1-xN/AlN multilayer films with original

composition inside the miscibility gap. The original layers were grown by MSE at

room temperature, which suppressed the decomposition into a metastable state. It

was found that the decomposition process initially occurs by surface directed spinodal

decomposition. The poor thermal stability of the formed In-rich domains was further

confirmed by the desorption of In from the layers, from the surface of the thin TEM

cross-sectional samples, while In was also found to diffuse into the ambient AlN.

65

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