Charge Transport and low Temperature Phenomena ...

UNIVERSITY OF SURREY

Charge Transport and low Temperature Phenomena in Single Crystal CdZnTe

by Matthew Veale supervised by Dr Paul Sellin A thesis submitted in partial fulfillment for the degree of Doctor of Philosophy in the Faculty of Engineering and Physical Sciences Department of Physics

February 2009

Abstract Cadmium Zinc Telluride (CdZnTe) has been the focus of intense research in recent years and is regarded as the material of choice for the production of the next generation of X-ray and γ-ray detectors. Recently the first commercial CdZnTe based detectors have become available but are still very expensive owing to the poor yield obtained using current growth processes. This work focuses on the characterisation of material produced using the modified vertical Bridgman (MVB) technique and the traveling heater method (THM); a number of key material properties are studied and the effect these have on the detector performance. The crystalline quality and homogeneity of each crystal is evaluated and from these measurements it is seen that the measured inclusion density is directly related to the spectroscopic performance observed at typical X-ray and γ-ray energies. Measurements of the charge transport properties both at room temperature and low temperature show there to be major differences between the MVB-grown and THMgrown materials. The electron transport properties of the MVB material are poorer than those of the THM material; low temperature measurements are used to show this may be related to a donor defect peculiar to the MVB material. Measurements using the PICTS technique also demonstrate an increased number of defects and impurities in the MVB samples leading to the conclusion that the better spectroscopic performance observed in THM samples is due to an increased level of purity.

Acknowledgements I would first like to thank my supervisor Dr Paul Sellin who over years has served as a constant source of help, guidance and encouragement without which the PhD would not have been possible. A special thank you must also be made to my fellow PhD students, past and present, Annika Lohstroh, Andrew Davies, Jamie Parkin, Georgios Prekas, Spyros Gkoumas and Veeramani Perumal; without whose experience and unwavering patience this PhD project might have seemed impossible. Thank you also to the staff and students of the University of Surrey who over the course of the last seven and a bit years have made my time as a student such a fruitful and rewarding experience, I shall be sad to leave! I would also like to thank my collaborators Paul Seller and Matt Wilson at the Rutherford Appleton Laboratory, not only for their time and for the use of facilities but also for their help and suggestions throughout the course of the PhD; I look forward to the coming year! A big thank you also has to be said to all my friends in Surrey and Wales who have stuck by me through thick and thin. I look forward to the next time I’m up the pub and get asked the dreaded question “Have you finished yet?”, finally I can actually say yes I have!! A final very big thank you to all my family who have been a constant source of encouragement, comfort and moral support over each and every one of my 21 years in education! Mum, Dad, Nic, Katie and Jamie without you I’m sure I would never of made it this far!

“We shall not cease from exploration, and the end of all our exploring will be to arrive where we started and know the place for the first time”

T.S.Eliot

ii

Contents Abstract

i

Acknowledgements

ii

Physical Constants

vi

Symbols and Abbreviations

vii

1 Introduction 1.1 Semiconductor Radiation Detectors 1.2 Cadmium Zinc Telluride . . . . . . 1.3 CdZnTe Applications . . . . . . . . 1.4 Thesis Outline . . . . . . . . . . .

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2 Detector Physics 2.1 Radiation Interactions with Matter . . . . . . . . . . . . . . . . . . 2.1.1 The Interactions of Heavy Charged Particles . . . . . . . . 2.1.2 Interactions of Electromagnetic Radiation . . . . . . . . . . 2.2 The Band Gap of Semiconductors . . . . . . . . . . . . . . . . . . . 2.3 Generation of Charge Carriers . . . . . . . . . . . . . . . . . . . . . 2.4 The Shockley-Ramo Theorem - Induced Charge in Semiconductors 2.5 Hecht Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 The Growth of CdZnTe . . . . . . . . . . . . . . . . . . . . . . . . 2.6.1 Bridgman Methods . . . . . . . . . . . . . . . . . . . . . . . 2.6.2 The Traveling Heater Method (THM) . . . . . . . . . . . . 2.6.3 Crystalline Defects . . . . . . . . . . . . . . . . . . . . . . . 2.7 Impurities and Intrinsic Defects . . . . . . . . . . . . . . . . . . . . 2.7.1 Compensation Schemes . . . . . . . . . . . . . . . . . . . . 3 Experimental Methods 3.1 Surface Preperation and Fabrication 3.1.1 Mechanical Polishing . . . . . 3.1.2 Chemical Etching . . . . . . . 3.2 Optical Characterisation . . . . . . . 3.2.1 Infrared (IR) Imaging . . . . iii

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1 2 5 6 8

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10 10 10 12 15 18 19 21 23 23 28 30 35 37

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41 41 41 42 42 42

Contents

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43 45 45 45 47 49 51 55

4 An Evaluation of CdZnTe Crystalline Quality 4.1 Surface Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1 CdZnTe Processing at Surrey . . . . . . . . . . . . . . . . . . . . 4.1.2 External Processing of CdZnTe . . . . . . . . . . . . . . . . . . . 4.2 Crystal Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Inclusion Distributions in Modified Vertical Bridgman CdZnTe . 4.2.2 Inclusion Distributions in Travelling Heater Method CdZnTe . . 4.3 Crystal Homogeneity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Room Temperature Photoluminescence Measurements . . . . . . 4.3.2 Low Temperature Photoluminescence . . . . . . . . . . . . . . . 4.3.3 Atomic Force Microscopy - A Correlation with PL Measurements 4.4 Electrical Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.1 Detector Fabrication . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.2 Material Resistivity . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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56 56 57 61 62 62 66 69 71 75 90 91 94 95 97

5 Charge Transport Properties of Spectroscopic CdZnTe Detectors 5.1 Alpha Pulse Height Spectroscopy . . . . . . . . . . . . . . . . . . . . . 5.1.1 Electron Transport . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.2 Hole transport . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Alpha Pulse Shape Analysis . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1 Electron Drift Mobility . . . . . . . . . . . . . . . . . . . . . . 5.2.2 Hole Drift Mobility . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.3 Carrier Lifetimes . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Charge Transport Uniformity . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Electron Transport . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.2 Hole Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 X-ray and γ-ray Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . 5.4.1 Spectroscopy at the University of Surrey . . . . . . . . . . . . . 5.4.2 Spectroscopy at Rutherford Appleton Laboratory . . . . . . . . 5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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3.3

3.4

3.2.2 Photoluminescence . . . . . . . . . . . . . . . . Electrical Characterisation . . . . . . . . . . . . . . . . 3.3.1 Current-Voltage Characteristics . . . . . . . . . 3.3.2 Charge Transport Measurements . . . . . . . . 3.3.3 Ion Beam Induced Charge Measurements . . . 3.3.4 X-ray and γ-ray Spectroscopy . . . . . . . . . . 3.3.5 Photo-Induced Current Transient Spectroscopy Samples Studied . . . . . . . . . . . . . . . . . . . . .

6 Low Temperature Phenomena in CdZnTe 6.1 Low Temperature Charge Transport Properties 6.1.1 Low Temperature Mobility-Lifetime . . 6.1.2 Low Temperature Mobility . . . . . . . 6.2 The Identification of Material Defect Structure 6.2.1 Low Temperature Resistivity . . . . . .

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Contents

6.3

v

6.2.2 PICTS Measurements . . . . . . . . . . . . . . . . . . . . . . . . . 158 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

7 Conclusions and Future Works 173 7.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 7.2 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175

A

241 Am

- A Self-Attenuation Correction

176

B Published Papers

178

List of Figures

189

List of Tables

195

Bibliography

196

Physical Constants c

=

2.997 924 58 × 108 m.s−1

ε0

=

8.854 187 817 × 1012 F.m−1

e

=

1.602 176 53 × 10−19 C

me

=

9.109 382 6 × 10−31 Kg

h

=

6.626 069 3 × 10−34 J.s

Boltzmann Constant

kB

=

Avogadro’s Constant

Na

=

1.380 650 0 × 10−23 J.K−-1. 6.022 141 5 × 1023 mol−-1.

Speed of Light Electric Constant Elementary Charge Rest Mass of Electron Planck Constant

vi

Symbols and Abbreviations ρ

Resistivity

µd

Trap-Controlled Mobility

µe

Electron Mobility

µh

Hole Mobility

τe

Electron Lifetime

τh

Hole Lifetime

τR

Transit Time

λe

Electron Drift Length

λh

Hole Drift Length

λ

Wavelength

ν

Drift Velocity

σ

Cross section

ψW

Weighting Potential

ACRT

Accelerated Crucible Rotation Technique

AFM

Atomic Force Microscope

CCE

Charge Collection Efficiency

d

Thickness

DLTS

Deep Level Transient Spectroscopy

E

Electric Field Strength

EB

Binding Energy

EC

Conduction Band Energy vii

Symbols and Abbreviations Ee

Photo-electron Energy

EF

Fermi Level Energy

Eg

Band Gap Energy

ET

Trap Energy

EW

Weighting Field

Eγ

γ-Ray Energy

F

Fano Factor

FWHM

Full Width Half Maximum

GDMS

Glow Discharge Mass Spectroscopy

HPB

High Pressure Bridgman

i

Current

IBIC

Ion Beam Induced Charge

IR

Infrared

IV

Current-Voltage

k

Segregation Coefficient

m∗

Effective Mass

MCA

Multi-Channel Analyser

MT-PVT

Multi-Tube Physical Vapour Transport

MVB

Modified Vertical Bridgman

N

Number of Free Carriers

N0

Number of Initial Carriers

NA

Number of Acceptors

NC

Density of States

NDD

Number of Deep Donors

NT

Trap Density

NBEL

Near Band Edge Luminescence

viii

Symbols and Abbreviations ne

Number of Electrons

nh

Number of Holes

PICTS

Photo-Induced Current Transient Spectroscopy

PIXIE

Proton-Induced X-Ray Emission

PL

Photoluminescence

Q

Charge

Q0

Initial Charge

rA

Roughness

STIM

Scanning Transmission Ion Microscopy

T

Temperature

THM

Travelling Heater Method

ToF-SIMS

Time-of-Flight-Secondary Ion Mass Spectroscopy

VEX

Variable Energy X-Ray

Vi

Voltage Offset

W

Pair Creation Energy

XPS

X-Ray Photoelectron Spectroscopy

Z

Atomic Number

ix

Chapter 1

Introduction Since the discovery of the various types of radiation by scientists such as Rontgen, Becquerel and Curie in the late 19th century scientists have searched for ways to detect and measure the various forms of radiation. Initially detectors took on a very simple form, like the phosphorescent screen used by Rontegen to discover X-rays, but over the years different types of detectors have been developed. These detectors may be broadly grouped into three different types, gas filled counters, scintillation detectors and semiconductor detectors. The most common gas filled detector is the Geiger-Muller tube which is used to detect ionising radiations such as alpha and beta particles; the detector consists of a tube filled with an inert gas (typically neon or argon) with electrical contacts at either end. Under normal conditions no current is detected between the two contacts, however, when ionizing radiation enters the detector ions are created in the gas and the resulting avalanche causes a large current to be measured. As one ionizing particle may result in the creation of many ions the G-M tube contains no information of the energy of the original particle so is of no use where spectroscopy is required but are very useful for radiation monitoring. It was during the 1950’s that the first scintillation detectors were developed; the advantages of these detectors are that they are capable of measuring spectroscopic information about the incident radiation. In these detectors a scintillator is coupled to a photomultiplier (PM) tube; the incident radiation enters the scintillator material and interacts with a large number of atoms causing them to enter an excited state. These excited states then rapidly relax resulting in the release of photons of visible or near-visible wavelengths. The photons then enter a photosensitive layer where the photoelectric effect is exploited to produce photo-electrons; these are then multiplied in the PM tube to produce the detected signal. As the amount of light produced in each interaction is roughly constant spectroscopic data about the original interacting radiation can be 1

Introduction

2

extracted from each pulse. By adjusting the scintillating material used different types of radiation may be measured, for example, Sodium Iodide (NaI) may be used to detect γ-rays whereas a common choice for proton and alpha particle detection is Caesium Iodide (CsI). As scintillation detectors rely on a number of different processes to convert the incident radiation into a detectable pulse, some of which can be very inefficient, the absolute energy resolution will always be limited. To achieve better energy resolution new types of detectors were required and this led to the development of semiconductor detectors in the 1960’s. Technically the first demonstration of a semiconductor detector, or a “crystal counter” as it was first described, was completed by Van Heerden in 1945; in his thesis [1, 2] he demonstrated the detection of alpha particles, electrons and γ-rays using AgCl crystals. Figure 1.1 shows Van Heerden’s experimental arrangement and a spectrum taken using his equipment which shows the pulse height distribution of 400keV electrons. However it was not till the 1960’s, with the increasing availability of other high purity materials, that semiconductor detector technologies really took off. In semiconductor detectors radiation is directly converted into electrical pulses through the generation of electron-hole pairs (ehp) with each event generating significantly more carriers than in scintillator detectors; the result is a detector which may achieve exceptional energy resolutions. At present silicon and germanium detectors are the prefered detectors for X-ray and γ-rays and provide the highest achievable energy resolution. Although both provide excellent energy resolutions both have disadvantages; silicon only proves efficient for the detection of charged particles and low energy γ-rays while germanium requires significant cooling to perform well. To overcome these problems new types of semiconducting (and semi-insulating) material are the subject of intense research; in particular the compound semiconductor, Cadmium Zinc Telluride (CdZnTe), has received a lot of attention and it is this material which is the focus of this project.

1.1

Semiconductor Radiation Detectors

Of the radiation detectors described in the previous section each shares a common principle of operation, namely, they rely on the incident radiation to produce ionisation of the detector medium; see figure 1.2. In an ideal detector each event of identical energy would trigger an identical response in the detector; in reality this is impossible as no detector is perfect with the detector material properties strongly influencing the response. Any potential detector material must fulfil a number of prerequisites; firstly it must be capable of operating under high bias voltage with negligible leakage current and secondarily the charge carriers must be formed easily and move through the detector volume unimpeded. While the first criteria describes the properties of an insulator the second is

Introduction

3

Figure 1.1: (Above) The experimental arrangement used by Van Heerden in 1945 in the first demonstration of a semiconducter detector (Below) a typical spectrum collected for 400keV electrons [1]

Figure 1.2: A simple depiction of a basic radiation detector [3]

Introduction

4

the property of a conductor; the use of semiconducting material mean, potentially, both of these prerequisites may be met. Of the semiconductors currently in use silicon (Si) and germanium (Ge) are by far the most widely used. This is owing to their high energy resolutions and, more recently, their relative ease of production; table 1.1 lists the properties of some common semiconducting materials. Although both Si and Ge produce excellent detectors they both have a number of Material Atomic Number Density (gcm−3 ) Bandgap Eg (eV) Pair Creation Energy W (eV) Resistivity ρ (Ωcm) Electron Mobility µe (cm2 V−1 s−1 ) Electron Lifetime τ e (s) Hole Mobility µh (cm2 V−1 s−1 ) Hole Lifetime τ h (s)

Cd0.9 Zn0.1 Te 49.1 5.78 1.57 4.6 1010 1000 3x10−6 10-80 10−6

CdTe 50 5.85 1.50 4.4 109 1100 3x10−6 100 2x10−6

Ge 32 5.33 0.67 3.0 50 3900 >10−3 1900 10−3

Si 14 2.33 1.12 3.6 10−3 480 2x10−3

Table 1.1: A comparison of different detector material properties [4]

disadvantages the most major of these being their low band gaps (1.12 and 0.67eV respectively) and small photoelectric cross-sections at higher X-ray and γ-ray energies. The low band gaps mean that both detectors are susceptible to high dark currents (currents produced due to the thermal creation of carriers in the absence of radiation) and in the case of Ge mean that detectors are cooled to cryogenic temperatures for useful operation. These cooling systems are normally bulky and are a problem if a small, compact detector is required for a particular application. In the case of Si (less so in the case of Ge) the low atomic number presents a problem as the photoelectric absorption coefficient is low at γ-ray energies of only 1 MeV. Figure 1.3 shows the thickness of detector material required to reduce the intensity of γ-rays of energies 10 keV to 100MeV to 1% of the original value. Due to the relatively poor photoelectric absorption observed in Si it would require a thickness of the order 100cm to significantly reduce the intensity of γ-rays of energy 1 MeV in the detector volume; as typical Si detectors are only a few 100 microns thick producing detectors of this thickness this is unrealistic. The result is that very low collection efficiencies are observed at energies in the mega-electron volt range meaning that Si detectors are much better suited to spectroscopy at low X-ray energies. Ideally any γ-ray detector should have a large active volume, good charge transport properties and perform well at room temperature and at energies of the order 1MeV or greater; under these constraints Si and Ge no longer suffice. If these strict constraints

Introduction

5

Figure 1.3: The thickness of material required to reduce the intensity of typical gamma rays to 1% of the original value

are to be met then a new type of semiconductor material is required; these are the compound semiconductors which over the last few decades have been the focus of intense research. Compound semiconductors, unlike the elementary semiconductors, consist of two (binary) or more (ternary etc.) elements with common examples being Gallium Arsenide (GaAs), Cadmium Telluride (CdTe), Cadmium Zinc Telluride (CdZnTe) and Mercuric Iodide (HgI2 ). By careful selection of the elements within the compound it is possible to engineer a semiconductor which has a band gap and absorption coefficient suited to a particular application and its needs. A common problem encountered with all of the compound semiconductors is the extreme difficulty encountered in growing large volume single crystals which are defect and impurity free. It is these problems that at present mean that for many applications compound semiconductors are not commercially viable, of those available CdTe and CdZnTe make up a large proportion.

1.2

Cadmium Zinc Telluride

The binary II-VI compound semiconductor Cadmium Telluride, or CdTe, was first investigated as a γ-ray detector in the 1960’s with encouraging results. Formed from equal

Introduction

6

parts Cd and Te, atomic numbers 48 and 52 respectively, the volume density is more than twice that of Si (5.85gcm−3 compared to 2.33gcm−3 ). This larger density means that, for γ-ray energies, the photoelectric cross-section is larger than that of Si and when coupled with a band gap energy of 1.5eV and reasonable charge transport properties then CdTe becomes an attractive option as a γ-ray detector. The main problems with CdTe are the difficulties encountered in growing large volumes of high purity, single crystal material. These problems can lead to the formation of defects and impurities in the material that have an adverse effect on the detector properties and damage the resolution of the device. The properties of CdTe may be improved by the addition of Zinc to the growth; the ternary alloy Cd1−x Znx Te consists of Zn atoms randomly substituted throughout the crystal lattice for Cd atoms. The addition of the Zn has two main effects; it helps reduce the dislocation density in the crystal and raises the band gap energy (for a 10% Zn fraction the band gap is 1.572eV compared to 1.50eV for CdTe). The increased band gap decreases the number of thermal generated carriers at room temperature resulting in a reduction in the detector noise due to leakage current. The lower dislocation density also improves the charge transport properties by removing sources of trapping in the material. The charge transport of electrons in CdZnTe is good with electron mobilities reported to be of the order 1000cm2 V−1 s−1 and with lifetimes of around 3x10−6 s. As with CdTe the hole transport is considerably poorer than the electron transport in the alloy. Hole mobilities have been found to lie in the range 10-100 cm2 V−1 s−1 and shorter lifetimes have also been observed and are of the order 10−5 to 10−6 s. The poor hole transport places a limit on the resolution of detectors with larger detector volumes showing significant ’tailing’ due to incomplete collection of holes. The poor hole transport is likely to be due to trapping phenomena in the device, possible sources of trapping may be impurities or crystal defects introduced during the growth. The focus of much of the research into CdZnTe at present is the effect these defects and impurities have; if the material is ever going to be realised as a commercially viable product then considerable work is still required in producing high purity, large, single crystal volumes.

1.3

CdZnTe Applications

The desirable properties of CdZnTe mean it has many potential applications, see figure 1.4, the three biggest being in the fields of medical imaging, security and astronomy. At present there is a great demand for medical imaging equipment with ever improving resolution; a good example is the use of CdZnTe detectors in the detection of breast cancers. As the technology becomes viable the move is beginning from old scintillator based systems to CdZnTe systems, one such system is the LumaGEM system produced

Introduction

7

by GM-I inc [5]. Here a CdZnTe based detector consisting of 12,228 pixels is used to image the emission of a Technetium-99 tracer from breast tissue, using CdZnTe a spatial resolution of 1.6mm is achieved a great improvement on the 6-10mm achievable with scintillator technologies. Another large application area with a vested interest in CdZnTe technology is the security sector. Applications in this sector range from real time luggage scanning equipment to spectroscopic personal radiation detectors (SPRD). As with medical imaging equipment the products are gradually coming to the market an example being the Thermo Scientific Interceptor SPRD [6]. The Interceptor SPRD is a handheld CdZnTe detector used for the detection of sources of γ-ray and neutron radiation with its main use being radiation monitoring and homeland security. The detector has a dynamic range of 25keV to 3MeV and can be used to detect a wide range of potentially harmful isotopes. Finally the third area where CdZnTe has been applied is the astronomy sector. By

Figure 1.4: Different application areas of CdZnTe [5, 6, 7]

utilising CZT technology astronomers are able to study a diverse range of phenomena ranging from the study of γ-ray bursts to studying the composition of planets and asteroids. Two examples of the application of CdZnTe in space science are two Nasa missions the Burst Alert Telescope (BAT) onboard the SWIFT satellite and the GRaND instrument onboard the Dawn mission [7]. The BAT has been detecting γ-ray bursts, some of the most violent events in the universe, since launching back in late 2004. The CZT detector arrays onboard are used to provide an initial crude estimate of the position of the event so the satellite can position itself to make the most of the science. With the aid of the onboard CdZnTe detectors in excess of 250 events have been detected to date meaning the mission has been a great success. The GRaND instrument is an integral part of the Dawn mission that hopes to study the conditions and processes that formed the solar system, to do this it will study the two proto-planets Ceres and Vesta located in the asteroid belt between Mars and Jupiter. The GRaND instruments job will be to analyse the composition of these pieces of the early solar system and produce a picture

Introduction

8

of the elements that initially formed the solar system; the job of the CdZnTe detector will be to study emissions from radioactive decay and nuclear reactions in the energy range 0-3MeV. Although CdZnTe is already being used in a wide range of applications the high cost, a typical SPRD costs in excess of $10K, is preventative for many institutions and applications. If the use of CdZnTe detectors is to become widespread then the price will have fall. The most obvious way for this to happen is by improving the yield of the growth processes and limiting the amount of crystal defects and impurities formed. To do this a full understanding of the defect and impurity properties and their effects on the crystal are required.

1.4

Thesis Outline

At present the inability to grow large area, high-purity, single crystal material at a reasonable price is stopping large scale implementation of the detectors. It is well known that impurities and crystalline defects have a negative effect on the performance of CdZnTe detectors but the origin and nature of these defects is still an area of intense research. In this project the aim was to study the properties of CdZnTe material and the effect that defects have on device performance. What follows is a brief description of the chapters that follow this introduction. • Chapter 2 Chapter 2 discusses the theory of operation of semiconductor detectors, specifically CdZnTe. The chapter gives an overview of the interaction processes that occur between radiation and semiconducting material followed by a discussion of charge induction and the formation of detector signals. The chapter closes with a discussion of the different growth techniques of CdZnTe and the effect both intrinsic and extrinsic defects have on the detector properties. • Chapter 3 Chapter 3 focuses on the different experimental techniques used to study the CdZnTe material. The chapter is broken into three sections, the first discusses the preparation of CdZnTe for use as detectors. The second section gives a discussion of the contact-less, non-destructive methods used to characterise both the crystalline quality and homogeneity. Finally details of the experimental arrangements used to study the electrical and defect properties of the CdZnTe is given.

Introduction

9

• Chapter 4 Chapter 4, the first of three results chapters, focuses on the results of measurements of the crystalline quality and homogeneity of the samples. A brief discussion of the results of sample preparation is given before an in-depth look at the crystalline defects contained within the samples is made using Infrared (IR) Imaging techniques. The homogeneity of the samples, as well as an early study of the crystal defect content, is then made through use of the Photoluminescence (PL) technique both at room and low temperature. The chapter concludes with a study of the current-voltage (IV) characteristics of each sample after the deposition of electrical contacts. • Chapter 5 Chapter 5 discusses the measurement of the charge transport properties of the different crystals. Through a combination of alpha pulse height spectroscopy measurements and pulse shape analysis both the electron and hole transport properties of the crystals are evaluated and compared. The following section uses the Surrey Ion Beam to study these transport properties on a micro-meter scale providing an insight into the small scale characteristics of these detectors. The final section then focuses on the performance of simple CdZnTe detectors at X-ray and γ-ray energies and compares this to other detector materials; the effect of temperature on the spectral performance of CdZnTe is also studied. • Chapter 6 Chapter 6 is the last of the results chapters and focuses on phenomena that occur at low temperature. To understand the collapse of the spectroscopic performance observed at low temperatures, discussed in the previous chapter, a study of the charge transport properties at reduced temperatures is made. Following these measurements a combination of low temperature IV measurements and the PhotoInduced Current Transient Spectroscopy (PICTS) technique are used to determine the defect content of the CdZnTe material; links between the defect structure and transport properties are then discussed. • Chapter 7 The project concludes with chapter 7 which gives a summary of the major findings of the project and suggestions for future works.

Chapter 2

Detector Physics To understand the behavior of CdZnTe detectors a good knowledge of the interactions that occur between radiation and matter, as well as the processes that create a detectable signal in the detector, are required. In this chapter the interactions of ionising radiations with semiconducting material and the subsequent formation of an induced charge are discussed; this is followed by a brief review of current growth techniques and the effects of impurities and defects on detector performance.

2.1

Radiation Interactions with Matter

All detectors operate on a common principle, that radiation enters the detector whereupon it deposits most, if not all, of it’s energy through interactions with the atoms in the material generating a detectable current pulse. The interactions of heavy charged particles, such as an alpha particle, in the detector material will be different to those of electromagnetic radiations such as X-rays and γ-rays. In the following sections these different interactions are discussed.

2.1.1

The Interactions of Heavy Charged Particles

Radiations such as alpha particles and protons are described as heavy charged particles. Two main interactions govern the behavior of these charged particles, Rutherford Scattering and Coulomb scattering, both arise from Coulomb’s Law that describes the force exerted on one charge by another; see equation 2.1: F =

1 q1 q2 . 4πε0 r2 10

(2.1)

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11

where ε0 is the electric constant, q1 and q2 are the charges on the two particles and r is the distance separating them. In the case of Rutherford scattering interactions occur between the charged particles and the nuclei of the atoms in the detector material but as the nucleus itself only takes up a very small proportion of the detector volume (in a single atom the nucleus fills only 10−15 of it’s volume) the number of interactions that occur via Rutherford scattering is small; by comparison a large proportion of all reactions will occur via Coulomb scattering. In the case of Coulomb scattering it is the atomic electrons that interact with the charged particle rather than the nucleus with it taking many such interactions to completely stop the particle. In each interaction a small amount of energy may be transferred to the electron leaving the atom in an excited state, this then rapidly falls back to the ground state via the emission of characteristic photons. If sufficient energy is transferred to the electron (∼10eV) then it will be removed from it’s associated atom, this results in the formation of free electrons and ions. The rate at which energy is transferred from a particle to a material is called the stopping power and is defined as the change in energy per unit length, equation 2.2. S=−

dE dx

(2.2)

In the 1930’s Hans Bethe derived a theoretical relationship for the stopping power from quantum mechanical considerations of the collision process. The Bethe formula is given in equation 2.3: −

4πe4 z 2 dE = Na B dx me v 2

(2.3)

where: "

2m0 v 2 v2 B = Z ln − ln 1 − 2 I c

!

v2 − 2 c

# (2.4)

and v is the velocity of the charged particle, z is the atomic number of the charged particle, e is the electronic charge, Na is Avagadro’s number (the number of atoms per unit volume), Z is the atomic number of the target, me is the electron rest mass and finally I is the average ionisation energy of an electron in the target material. The Bethe equation demonstrates that it is not only the charge of the incoming particle but also the density of the material that has a large effect on the observed stopping power. In this work both alpha particles and protons are used to investigate detector properties,

Detector Physics

12

Figure 2.1: The specific energy loss of 5.5MeV alpha particles and 2MeV protons in CdZnTe calculated using SRIM [8]

figure 2.1 shows Bragg curves for 5.5MeV alpha particles and 2MeV protons in CdZnTe. The Bragg curve shows the specific energy loss of the particle as it moves through the detector medium. The curves show how initially the energy loss increases slowly but then undergoes a rapid increase close to the end of its path. As the particle slows more and more energy is lost until it has sufficiently decreased such that the particle can pick up atomic electrons. At this point the energy falls off rapidly as the charge is reduced to zero and the coulomb force no longer effects the particle, this is shown in the characteristic sharp decline observed in the curves of figure 2.1.

2.1.2

Interactions of Electromagnetic Radiation

Unlike charged particles electromagnetic radiation, such as X-rays and γ-rays, have no charge and this means that interactions must occur through a series of different processes. Of these interactions three dominate; these are photoelectric absorption, Compton scattering and pair production. The relative strength of each interaction is dependant on the energy of the interacting photon; the relative importance of each interaction in terms of photon energy can be seen in figure 2.2.

• Photoelectric Absorption As seen in figure 2.2 Photoelectric Absorption is the dominate interaction at energies of 100keV or less. In Photoelectric Absorbtion energy is transferred from

Detector Physics

13

Figure 2.2: Attenuation Coefficients in Cd0.9 Zn0.1 Te, calculated using XCOM [9]

the photon to a bound atomic electron, typically a tightly bound inner (K-Shell) electron at γ-ray energies. The inner electron then gains sufficient energy to be ejected from the atom (ionisation); the energy of the photoelectron (Ee ) is then given by equation 2.5: Ee = hv − EB

(2.5)

Where h is Planks constant, v is the frequency of the radiation and EB is the binding energy of the atomic electron. The ejection of the photoelectron leaves the atom in an excited state; usually this excess energy is released by a higher shell electron dropping to the vacancy and in doing so releasing a characteristic photon of an energy equivalent to the difference in the shell energies. To calculate the probability of a photon producing a photoelectron is difficult as no single analytical expression is available, however, an approximation for the probability of an interaction occurring (τP E ) is give in equation 2.6: τP E ∼

Zn Eγ3.5

(2.6)

where Z is the atomic number of the absorber, Eγ is the γ-ray energy and n is an exponent with a value ranging from 3-4. The large dependance of equation 2.6 on the atomic number of the absorber demonstrates why semiconductors with high-Z

Detector Physics

14

are such an attractive option for X-ray and γ-ray detection. Figure 2.2 shows the variation of the photoelectric attenuation coefficient as a function of photon energy, it should be noted that there are a number of discontinuous jumps in the plot at certain energies. These jumps correspond to the binding energies of electrons in specific shells in the atoms, for example the K-Shell binding energies of cadmium and tellurium are 27keV and 32keV respectively.

• Compton Scattering The second of the electromagnetic interactions to be discussed is Compton Scattering; in this interaction energy is transferred from the incident photon to a ‘nearly-free’ atomic electron. Outer shell electrons have a much lower binding energy than the inner shell electrons and as a result are able to participate in scattering interactions. If the electron is considered to be at rest then the incoming photon transfers a portion of it’s energy to the electron resulting in the scattering of the photon through an angle θ and the recoiling of the electron through an angle φ; the interaction is illustrated in figure 2.3. From the conservation of energy and

Figure 2.3: The geometry of Compton scattering

momentum it follows that the energy of the photon after the scattering event (E’) can be calculated from equation 2.7: E

E0 = 1+

E(1−cos θ) m0 c2

(2.7)

where E is the original energy of the photon and θ is the angle through which the photon is scattered, the energy transferred to the electron is simply the difference.

Detector Physics

15

As the interaction mechanism is dependant on there being nearly-free electrons available the probability of the interaction will be dependant on the atomic number of the absorber; hence the attractiveness of high-Z semiconductors as detectors. The variation of the interaction cross-section for Compton scattering can also be seen in figure 2.2.

• Pair Production The third and final interaction mechanism to be discussed here is pair production and is relevant only for higher energy γ-rays. In pair production a γ-ray of sufficiently high energy creates an electron-positron pair and disappears in the process. For momentum to be conserved the reaction requires the presence of the Coulomb field of a nearby massive atom to absorb the initial momentum of the γ-ray (although the actual value is negligible). If energy is also to be conserved in the interaction then equation 2.8 must hold true: Eγ = T+ + m0 c2 + T− + m0 c2

(2.8)

Where Eγ is the γ-ray energy, T+ and T− are the kinetic energies of the positron and electron respectively. There is an obvious limit below which the interaction cannot occur; γ-rays with an energy of less than 2mc2 , 1.022 MeV, will be unable to interact via pair production.

2.2

The Band Gap of Semiconductors

The band gap of any semiconductor describes the separation, in energy, of the valance and conduction bands and is determined by the crystalline structure of the material. In CdZnTe the two main species, cadmium and tellurium, are organised in two interpenetrating face centred cubic (fcc) structures one populated with Cd atoms and the other with Te atoms. This ’Zinc Blende Structure’ is typical of other semiconducting materials such as InSb, GaAs and GaP; the structure is illustrated in figure 2.4. It is the regular arrangement of atoms in the crystal lattice that gives rise to the band structure of semiconductor materials. The size of the band gap will determine the properties of the material, a large band gap results in an insulating material whereas a band gap of less than 5eV results in a semiconducting material. The probability per unit time of an electron-hole pair being

Detector Physics

16

Figure 2.4: The Zinc Blende Structure (ZnS) [10]

produced thermally is given by: 3 2

p(T ) = CT exp

Eg (T ) − 2kB T

! (2.9)

Where T is the absolute temperature, Eg (T ) is the band gap energy which itself is dependant on temperature, kB is the Boltzmann constant and C is a material dependant constant. Hence the thermal generation of carriers is highly dependant on the band gap of the material which has important consequences on the performance of detectors, if a large number of carriers are thermally generated then leakage current in the detector will be high. Figure 2.5 shows the variation of the relative probability of thermal generation of electron-hole pairs with temperature for CdZnTe, Si and diamond. One of the major advantages of compound semiconductors is, unlike the elemental semiconductors, specific material properties may be engineered to match specific applications. CdTe has a nominal band gap energy, at room temperature, of 1.5eV and this is defined by the atomic spacing and electronegativities of the Cd and Te atoms in the crystal lattice. If a certain fraction of Cd atoms are replaced with Zn atoms then the average inter-atomic distance will be decreased and the band gap will be raised. Figure 2.6 shows the effect of the lattice constant on the band gap of a variety of II-VI compounds; two specific cases are highlighted on the diagram and these correspond to CdZnTe with Zn fractions of x=0.1 and x=0.7. As can be seen through manipulation of the Zn fraction it is possible to produce CdZnTe compounds with band gaps ranging

Detector Physics

Figure 2.5: The temperature dependance of the formation of thermally-generated electron-hole pairs, temperature dependant band gap data is taken from O’Donnel et al [11]

from 1.5 eV to about 2 eV.

Figure 2.6: The Band Gap energy of II-VI compounds as a function of lattice constant [12]

17

Detector Physics

2.3

18

Generation of Charge Carriers

The interaction of radiation within the detector results in ionisation of the material promoting electrons to the conduction band and producing corresponding holes in the valence band. The number of electron-hole pairs produced is dependant on the properties of the semiconductor material, namely the ‘W-Value’. The W-Value is the energy, in eV, required to produce an electron-hole pair and is largely (although not completely) independent of the radiation energy and type. Figure 2.7 shows a summary, from a

Figure 2.7: W-Values vs Bandgap for a Range of Different Materials [12]

review by Owens et al [12], of the relationship between band gap and W-Value for a large number of materials. If the electron-hole pairs are created in the presence of an electric field then they will start to drift in opposite directions towards the electrodes; this movement of holes and electrons induces a current on the electrodes. The amplitude of the integrated current pulse will be directly dependant on the energy of the ionizing radiation through the W-Value of the material. In an ideal detector the intrinsic efficiency is given by the Fano factor, this describes the observed statistical fluctuations compared to those expected from Poisson statistics alone. If it is assumed that the creation of each electron-hole pair is an independent event then the statistical variation in the signal is simply given by Poisson statistics as described by equation 2.10:

Detector Physics

19

∆E =

Ep Wehp

(2.10)

where ∆E is the Poisson variation in the energy, Ep is the radiation energy deposited and Wehp is the energy required to form an electron-hole pair (W-Value). However, the creation of multiple electron-hole pairs by the incident radiation are not independent events and the variance, as a result, is smaller [3]. The Fano factor gives the relationship between the observed variance (when all other sources of noise are removed) to that of Poisson statistics, in other words: F =

2.4

∆Eobserved ∆E

(2.11)

The Shockley-Ramo Theorem - Induced Charge in Semiconductors

Semiconductor detectors work on the principle that the detected signal is formed from the creation of induced charge on the device electrodes generated by interactions of ionizing radiation within the detector material. In the late 1930’s a theory was developed independently by W. Schockley [13] and S. Ramo [14] that allowed the simple calculation of the induced charge in detectors with complex contact geometries. The theory was originally developed for vacuum tube geometries but in the following years was extended to semiconductors (a recent review can be found in a paper by Z.He et al [15]). The theorem states that the charge Q and current i induced on an electrode by a moving charge is given by: Q = −qψW (x)

(2.12)

~ W (x) i = q~v .E

(2.13)

where v is the instantaneous velocity of charge q. ψW (x) and EW (x) are the so called ‘weighting potential’ and ‘weighting field’ that would exist at the charges instantaneous position, x. The weighting field is defined as: EW (x) =

δψW (x) δx

(2.14)

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20

Physically the weighting potential represents the electrostatic coupling between the moving charges and the induced charge at an electrode. The weighting potential is not related to the physical potential, which describes the carrier velocity and trajectory, but is instead defined as “the potential at position x when the selected electrode is at unit bias, 1V, and all others are at zero potential” [15] and is dependant only on the carrier motion and electrode geometry. The simplest case to consider is that of a theoretical de-

Figure 2.8: (a) A schematic Diagram of a simple planar detector and (b) The weighting potential of the anode [15]

tector consisting of intrinsic material (containing no space charge) sandwiched between two infinitely large contacts. In this configuration the weighting field is simply a linear function of depth from the cathode to the anode; as seen in figure 2.8(b). Combining equations 2.12 and 2.14 it can be shown that: δQ =

q δx d

(2.15)

An ionising event occurring at a depth X in such a detector will create a cloud of charge containing both electrons and holes that are subsequently swept to the anode and cathode respectively. The total charge induced on the contacts will then be given

Detector Physics

21

by equation 2.16: q Q= d

Z

d

Z

!

X

nh dx

ne dx +

(2.16)

0

X

where ne and nh are the number of electrons and holes respectively. In the ideal case the mean drift lengths of both the electrons and holes (λe and λh respectively) will be much greater than the thickness of the device and for each interaction 100% of the carriers created will be collected. In reality this is not the case and the trapping of carriers results in incomplete charge collection; as a result a new term is defined: CCE =

Q Q0

(2.17)

where CCE is the charge collection efficiency of the detector and Q0 is the number of carriers created in the original interaction.

2.5

Hecht Theory

In reality the drift lengths of electrons (λe ) and holes (λh ) will be limited by the effects of carrier trapping, in the case of CdZnTe this is especially bad for holes. If the drift lengths are shorter than the detector thickness then the result will be incomplete charge collection and a reduction in the device CCE. The drift lengths of the charge carriers are defined as: λe = ve τe λh = vh τh

(2.18)

where ve and vh are the drift velocities of the electrons and holes respectively and τ e and τ h are their lifetimes (i.e. the time the carriers travel freely in the material before being trapped). If the drift velocities of the carriers are assumed to be below saturation then the velocity of the carriers will be proportional to the applied field and the carrier mobilities (µe and µh ) as given in equation 2.19: v = µE

(2.19)

It is then possible to define the drift lengths in terms of both the carrier mobility and

Detector Physics

22

lifetime: λe = µe τe E λh = µh τh E

(2.20)

This result means that the drift length of carriers in a material can be limited by one of two factors, firstly by a poor drift mobility or secondly by a short carrier lifetime. From equation 2.20 a fundamental parameter can be defined to describe the quality of the detector material and is known as the mobility-lifetime product or µτ -value. For materials with low values of µe τ e and µh τ h the carrier drift lengths will be small and this will have an adverse effect on the detector CCE. In 1932 Hecht developed an equation relating the detector CCE to the charge transport properties of electrons and holes and the depth of interaction of the ionising event in the material [16]. If it is assumed that traps are distributed equally throughout the material and that the carriers have a mean limited lifetime then the carrier population will be described by equation 2.21:

x N = N0 exp − µτ E

(2.21)

If an interaction occurs a distance x below the cathode then the population of electrons and holes will described by equations 2.22: h (d − x) i ne = n0 exp − µe τe E h (x) i nh = n0 exp − µh τh E

(2.22)

Using the expressions for the carrier concentrations it’s then possible to solve the integral expression given in equation 2.16; the result is the Hecht equation: " !# " !# µe τe E −(d − x) µh τh E −x CCE = 1 − exp + 1 − exp d µe τe E d µh τh E

(2.23)

A special case exists that is of particular use in detector characterisation where the Hecht equation may be reduced to a simpler form. If the interaction depth is very small compared to the carrier drift lengths, x1µm and this must be further reduced. A second stage of lapping is completed using a reduced grain size of 3µm and a plate rotation rate of 5rpm, using these settings a removal rate of ∼5µm min−1 is achieved. The resulting surface still contains considerable damage and to remove this a final processing step is carried out on the CP4000 chemical polisher. The CP4000 works in a similar way to the PM5, however, in this case a nylon pad covers the rotating glass plate and instead of using an abrasive an etchant is fed onto the plate. The action of the samples on the rotating plate gives a more uniform etch and appears to reduce the presence of the features observed during the free standing etch (see figure 4.3). The etchant used contains 0.2% bromine and 3% ethane diol in solution with methanol; the ethane diol was added to increase the viscosity of the etchant this ensures an acceptable surface roughness and slows the removal rate. Using the 0.2% etchant, a sample load of 10g/cm2 , and a plate rotation speed of 5rpm ,a removal rate of 2.5µm min−1 was achieved. After 5 minutes of polishing a uniform mirror finish was observed, a microscope image of the surface can be seen in Figure 4.5. A 200µm line scan gave a surface roughness of ∼1.7nm an improvement on the surface roughnesses achieved during the processing of crystals at the university. In conclusion it has been shown that although it is possible to produce samples with reasonable surface quality using very simple methods to achieve the best possible surfaces the use of advanced equipment is required.

An Evaluation of CdZnTe Crystalline Quality

62

Figure 4.5: Above: An optical image of a CdZnTe surface taken after processing with Logitech equipment. Below: A 200µm line scan

4.2

Crystal Quality

Crystalline defects such as Te precipitates and inclusions have been the focus of much research in recent years. It has been shown by a number of authors that in the vicinity of these inclusions there may be significant reductions in carrier lifetimes as well as modification of the local electric field [21, 37, 81, 82]; these effects will adversely effect the spectroscopic capability of the material. As a result any ideal CdZnTe detector should be free from such defects but in reality it is difficult to completely eliminate them especially in melt grown crystals like those studied. Some reduction in the size of precipitates is possible through annealing of the crystals, this has been shown to be especially effective when carried out under cadmium atmosphere [83, 84], but even this does not completely eliminate the defects. A scanning infrared microscope was used to study the quality of a number of CdZnTe samples (see section 3.2.1). The band gap of Cd0.9 Zn0.1 Te is nominally 1.57eV and as a result the material will be transparent to below band gap light of infrared wavelengths (>800nm). Crystalline defects such as precipitates and inclusions have a lower band gap than the surrounding material (for Te Eg ∼0.3eV) and as a result will not transmit the light and will appear as dark spots on an infrared (IR) image. Images of a number of CdZnTe crystals were taken using a scanning IR microscope (described in section 3.2.1) and the defect distribution measured at a number of depths for each crystal.

4.2.1

Inclusion Distributions in Modified Vertical Bridgman CdZnTe

The first crystals to be studied were grown via the modified vertical Bridgman method (MVB) by Yinnel Tech Inc and received no known post-growth processing. All crystals were seen to contain a large number of Te inclusions of varying shape and size. Figure 4.6


63

shows the IR map for crystal YI-44; the main bulk of the crystal shows a random distribution of inclusions (the red area in the image shows such an area) and many of the inclusions observed appeared to be either triangular or an irregular polyhedron in shape. In the yellow area lines of spatially correlated inclusions are observed, such groups of inclusions have previously been found to decorate grain and twin boundaries [17, 85] (see section 2.6). The number of inclusions and their estimated size were measured for a large portion of the crystal (∼1mm3 ), figure 4.7 shows a histogram of the different inclusion sizes measured for crystal YI-44. The measurement process was repeated for

Figure 4.6: An IR map of crystal YI-44; the red area shows an area typical of the crystal and yellow shows an area of spatially correlated inclusions

a number of other crystals grown via the MVB process, many of which showed inclusion densities higher than that observed in crystal YI-44 including large amounts of spatially correlated inclusions. Figure 4.8 shows IR imaging data taken for sample YI-51, the sample shows two distinct areas. In area (i), taken from an image close to the back surface of the crystal, large running lines of inclusions are observed and this may well represent the presence of either a grain or twin boundary. In area (ii) the inclusion distribution is random and much more like that observed for YI-44 (Figure 4.6). Histograms were taken from the same area of the crystal but at two different focus depths, one near the centre of the sample and the second near to the back surface in the high inclusion density region. The histograms for the two areas are shown in figure 4.9. As shown in (ii) the inclusions near the grain/twin boundary seem to group into two types those with areas less 2µm2 and those with larger areas of 10µm2 or greater, this can clearly be seen in the inset IR image. In (i) the inclusions seem to have a wider distribution of sizes although a large


64

Figure 4.7: Histogram showing the distribution of inclusion sizes in crystal YI-44

amount still have areas 1 which can result in both a reduction in zinc concentration from tip to heel of the boule [21, 27] as well as a radial distribution (see section 2.6). Variations in zinc concentration will result in corresponding variations of the material properties, the most significant of which will be in the band gap value [86]. Hence, by


70

Figure 4.14: A histogram of inclusion distribution in sample RD-13 after image editing

measuring the band gap energy, it is possible to determine the zinc concentration. An effective technique for measuring the band gap of CdZnTe is through the non-contact, non-destructive measurement of the near-band-edge luminescence (NBEL) using the photoluminescence technique (PL) described in section 3.2.2. In the PL technique the sample surface is excited using an above band gap laser, in this case the 532nm line of a YAG laser. The laser light is absorbed at the detector surface generating electron hole pairs which can recombine via one of several mechanisms; in the case of PL radiative recombination is the process of interest. In the University of Surrey PL system samples are mounted in a liquid helium cryostat and placed under vacuum; this allows measurements to be made in the temperature range 10K-300K with, typically, one of three different temperatures, 290K, 80K and 10K studied. The measurements at different temperatures serve different purposes; room temperature measurements are used to study the distribution of zinc concentration in the samples whereas low temperature measurements, due to increased emission intensities, are used to study the material defect structure.


4.3.1

71

Room Temperature Photoluminescence Measurements

For PL measurements taken at room temperature there exist in the literature a number of empirical relationships relating the measured band gap energy and the zinc concentration. Two of the most cited equations in the literature are equation 4.2 [87] and equation 4.3 [88], figure 4.15 shows plots of the two equations. For these measurements

Figure 4.15: The variation of band gap energy with zinc fraction as calculated by Tobin et al [87] and Olego et al [88]

the empirical relationship used by Tobin et al is used (equation 4.2).

Eg = 1.505 + (0.631x) + (0.128x2 )

(4.2)

Eg = 1.510 + (0.606x) + (0.139x2 )

(4.3)

Using the PL system at Surrey it is possible to map [89] the characteristic luminescence across the sample surface using an X-Y stage; such a room temperature map was collected for MVB sample YI-02 using a scan resolution of 200µm. Figure 4.16 shows a map of the measured luminescence wavelength as a function of sample position. As the image shows, the wavelength only varies by a few nm across the image demonstrating good material uniformity. From the measured emission wavelength the band gap energy was calculated at each pixel and then, using the empirical relationship devised by Tobin et


72

al [87] (equation 4.2), the map was converted into zinc concentration; the results of the transform can be seen in figure 4.17 a histogram of the zinc concentration determined for each pixel in the image is included. A gaussian fit to the histogram gives an average

Figure 4.16: Room temperature PL mapping of sample YI-02 and example spectra

value of 7.1% for the zinc concentration and a FWHM of 0.3% again demonstrating the good material uniformity. Mapping measurements were also made at room temperature for sample YI-51; the mapped area also included data from samples YI-44 and YI-50 and the results can be seen in Figure 4.18. The zinc concentration for all three of these samples is ∼10% and each displays a FWHM of 0.5% again demonstrating the good material uniformity.


73

Figure 4.17: Spatial variations of zinc concentration in sample YI02, inset graphs show a line scan across the sample and the statistical distribution of the zinc concentration

Sample YI-44 YI-50 YI-51 YI-52 YI-58 RD-13 RD-14

λ (nm) 789 791 790 800 800 804 795

Eg (eV) 1.571 1.567 1.569 1.549 1.550 1.543 1.560

Zn Fraction (%) 10.3 9.6 9.9 6.9 7.1 6.0 8.5

Table 4.2: Band gap and zinc concentrations calculated for MVB and THM samples from room temperature PL data

Zinc concentration was also measured for a number of other samples but this time without mapping of the whole surface, instead the zinc concentration was measured from spectra taken for a few points on the surface. A summary of the measured zinc concentrations for each sample is give in table 4.2.


Figure 4.18: Above: A PL map of the distribution of Zn concentration for sample YI-51 and areas of YI-44 and YI-50, Below: the statistical distribution of Zn

74


4.3.2

75

Low Temperature Photoluminescence

More information can be gathered from the PL technique if the sample is cooled to either liquid nitrogen (80K) or liquid helium (4K) temperatures. At room temperature there are a number of competing recombination mechanisms, some of which are non-radiative, that do not contribute to the luminescence from the sample; by cooling the detector these processes are minimised. At high temperatures the thermal distribution of carriers also broadens the PL spectral peaks by a factor of approximately kT/2 although in reality the measured spectral resolution is limited more by the limitations of the experimental arrangement. The PL system at Surrey is capable of cooling to 80K using liquid nitrogen (LN2 ) or down to ∼10K using liquid helium (LHe). Samples are mounted in the cryostat using a zinc oxide thermal putty to ensure good thermal contact between the sample and the cryostat cold plate.

• PL at Liquid Nitrogen (80K) Temperatures

A number of samples were mounted in the cryostat and cooled. During the cooling from 290K to 80K spectra were taken at the same point on two of the samples to see the evolution of the PL spectrum with temperature. Figure 4.19 shows the changing PL spectrum for MVB samples YI-44 and YI-52. As the samples are cooled the NBEL energy increases consistent with an increasing band gap energy at low temperature, this has been described previously for many semiconducting materials including CdZnTe [11, 90, 91, 92, 93]. As the samples are cooled the thermal vibrations of the crystal lattice decrease and as a result the interatomic spacing contracts raising the band gap energy. An empirical relationship proposed by Varshni et al [94] is widely used to fit temperature-dependant band gap data; the relationship is given in equation 4.4 where Eg (0K) is the band gap at 0K, α is an empirical constant and β is related to the Debye temperature of the material. Eg (T ) = Eg (0K) −

αT 2 β+T

(4.4)

Using equation 4.4 a fit was attempted to the band gap energies determined for samples YI-44 and YI-52 at varying temperatures; the results are shown in Figure 4.20. The fits to the data are very good and the fitting parameters compared well to those in the literature [91, 95]; table 4.3 summarises the fitting parameters and compares them to the literature values. As the temperature of the samples


76

Figure 4.19: The evolution of PL spectra with decreasing temperature for (i) YI-44 and (ii) YI-52; vertical scales are the same for all temperatures

Variable Zinc Fraction Eg (0K) (eV) α (eV/K) β (K)

YI-44) 0.10 1.641 3.6x10−4 173

YI-52 0.07 1.628 4.0x10−4 170

Prokesch[95] 0.10 1.649 4.5x10−4 264

Table 4.3: Fit parameters for the temperature dependance of CdZnTe band gaps


77

Figure 4.20: Variation of the NBEL luminescence energy and fit to equation 4.4 for samples YI-44 and YI-52

is decreased the width (FWHM) of the NBEL is also seen to decrease consistent with the reduction in thermally generated statistical fluctuations; figure 4.21 shows the reduction of the FWHM with temperature for the two MVB samples. As the

Figure 4.21: The reduction of NBEL peak width at low temperatures

sample temperature is decreased so the luminescence intensity increases due to the reduction of thermally excited non-radiative transitions; figure 4.22 shows the variation of the integrated intensity of the NBEL luminescence with temperature.


78

The variation of the luminescence intensity can be exploited to extract informa-

Figure 4.22: The variation of the integrated luminescence intensity with sample temperature

tion about the thermal activation energy of the quenching process [90, 92, 96, 97]; equation 4.5 was used to fit the experimental data: I(T ) =

I(0K) 1 + CA exp(− kEBAT )

(4.5)

where IT is the integral intensity of the luminescence at a given temperature, I0K is the intensity at absolute zero, CA is a constant fitting parameter and EA is the thermal activation energy controlling the quenching process. In the case of the samples studied a fit could only be made to experimental data for sample YI-52 (the data for YI-44 showed significant scatter); the attempted fit gave values of CA =86 and an activation energy of EA =0.05eV. The value of EA is consistent with the presence of shallow donor levels [41, 59, 96], in particular indium, suggesting the strongest luminescence observed is that of the donor-bound exciton (D0 ,X). At the low temperatures the increased luminescence intensity means a second emission, other than the NBEL, becomes apparent; figure 4.23 shows a log plot of spectra at 80K for both of the Yinnel samples. The emission appears in a band between 1.35eV and 1.55eV (or 0.l0-0.25eV if measured from the band edge) and is most likely due to the defect known as an ’A-Centre’ (a cadmium vacancy complexed with a shallow donor impurity), which has previously been seen in PL measurements on CdZnTe [98, 99]. At 80K the intensity of the 1.45eV band is


79

still low and to fully study the defect structure of the samples further cooling is required.

Figure 4.23: PL spectra at 80K for samples YI-44 and YI-52 displaying a defect band emission

• PL Studies of Redlen THM CdZnTe at 80K PL measurements were also made on the Redlen THM samples RD-13 and RD-14 at 80K. Like the Yinnel material the uniformity of the measured band gap energy across the sample is good and this can be seen in Figure 4.24. The mean band gaps for samples RD-13 and RD-14 at 80K were found to be 1.596eV and 1.601eV respectively. Histograms of the band gap energies measured for each pixel gave FWHM of 0.16% for RD-13 and 0.17% for RD-14; the values of the FWHM observed are comparable to those measured with Yinnel samples (see figure 4.17). If individual spectra taken from the Redlen PL maps are studied at different temperatures they prove to be very different to the emissions observed for the Yinnel material. Figure 4.25 shows both the room temperature luminescence and the 80K luminescence for both the Redlen samples. Although the band gap energy has shifted by ∼50meV, similar to that observed in the Yinnel samples, there has been no significant increase in the luminescence intensity. In the Yinnel samples spectra taken at 290K and 80K showed a 20-fold increase in the luminescence intensity compared to an observed increase of only 2.5x in the Redlen samples; it is also worth noting that no defect band at lower energies is observed in the Redlen samples.


Figure 4.24: Maps of the band gap energy determined from the Near Band Edge Luminescence (NBEL) at 80K for (i) RD-13 and (ii) RD-14; (iii) shows histograms of the band gap energy at each pixel

80


Figure 4.25: The Near Band Edge Luminescence (NBEL) at 292K and 80K for (i) RD-13 and (ii) RD-14

81


82

As mentioned earlier the Redlen samples have undergone post-processing annealing after growth the first stage of which was under cadmium atmosphere. A second stage of annealing was also performed this time in a hydrogen plasma; the effect of this annealing step is to passivate both intrinsic defects and impurities. Many studies have been made into the effect of hydrogen passivation in CdTe [100, 101, 102, 103] with a few studies focusing on the application of the technique to CdZnTe [52, 104] effecting both the sample surface and, in the case of extended annealing, the bulk material. Studies have shown that the hydrogen plasma interacts with intrinsic defects, extrinsic impurities and the crystal structure to form neutral closed pairs. Figure 4.25 shows no defect band in either sample and this may a direct result of the effect of the hydrogen plasma. An A-Centre defect, as stated previously, is attributed to a complex of a cadmium vacancy and shallow donor (for example indium); these vacancies will contain dangling bonds which will rapidly terminate with the hydrogen in the reaction 4.6 [104]. 0 0 + H − → (InH) + VCd InVCd + H 0 → In+ + VCd

(4.6)

Similar reactions will also preferentially neutralise shallow acceptor level impurities in the CdZnTe forming chemically stable closed pairs; such reactions will remove centres around which the (A0 ,X) excitons may form resulting in a reduction in the intensity of the luminescence as observed in the Redlen samples. Figure 4.26 shows data taken by Lmai et al [52] that shows a similar reduction in PL luminescence intensity in a purposely damaged CdZnTe surface after hydrogen annealing. As a comparison PL spectra were taken at 80K on an earlier Redlen sample that hadn’t undergone the hydrogen annealing step (other than this it is assumed the producer has processed the sample surfaces in a similar manner) the results can be seen in Figure 4.27. In this sample there is a marked increase in the signal intensity (an increase of ∼2.5x) compared to samples RD-13 and RD-14 as well as the presence of a clear defect band in the un-annealed sample. These results suggest that the sample annealing maybe responsible for the removal of the defect band and reduction of luminescence intensity.

• PL at Liquid Helium (10K) Temperatures By cooling to temperatures below 80K it is possible to look at the band structure of the samples in more detail. In total five MVB samples and one of the earlier Redelen samples were studied at 10K; example spectra from samples YI-51 and RD-09 (the un-annealed Redlen sample) are shown in Figure 4.28. In both samples at the


Figure 4.26: PL measurements by Lmai et al [52] on damaged CdZnTe surfaces (a) before hydrogen annealing and (b) after hydrogen annealing

Figure 4.27: A comparison of the PL emission at 80K from sample RD-09 (no passivation) and RD-14 (hydrogenated)

83


84

Figure 4.28: PL Spectra at 10K for samples (i) YI-51 and (ii) RD-09

lower temperature more features are visible with the spectra showing a well defined defect band (A1,A2 and A3) as well as evidence of both the dominant donor-bound exciton (D0 ,X), as determined from the previous temperature dependant luminescence intensity measurements, and acceptor-bound exciton (A0 ,X). However, at these temperatures the resolution of the spectrometer becomes the limiting factor with the width of the (D0 ,X) peak approaching that of the reflected YAG line at 532nm with FWHM of ∼19meV and ∼17meV respectively, figure 4.29 shows a typical CdZnTe PL spectrum and reflected YAG line. This limit means that some of the fine structure described by other authors [26, 97, 105], see figure 4.30, will not be resolvable using the current system. Table 4.4 gives a summary of the


Figure 4.29: A comparison of the widths of the reflected YAG (532nm) and CdZnTe (D0 ,X) peak at 10K

Figure 4.30: High resolution PL spectrum of the near band edge region at 4.2K [26]; the (D0 ,X) peak has a FWHM of ∼3meV

85


86

Sample No.

D0 ,X (eV)

FWHM (meV)

A0 ,X (meV)

A1 (meV)

A2 (meV)

A3 (meV)

YI-44 YI-50 YI-51 YI-52 YI-58 RD-09

1.652 1.633 1.649 1.632 1.645 1.642

19 24 20 17 17 16

23 30 24 29 15 19

156 160 136 155 149

181 181 166 177 175

246 228 224 231 225

Table 4.4: Energies of defects determined from 10K PL data

energies of the different peaks observed in the LHe spectra for all of the samples studied. These energies are calculated from the difference between the measured defect energy and the position of the main (D0 ,X) emission. This defect energy may contain a small error as the binding energy of the exciton has not been taken into consideration (as it was not possible to resolve the free exciton emission), any such error will be of the order +/-10meV. From the LHe measurements it appears that the defect band observed at 80K between 0.1 and 0.25eV contains three discreet levels (and most likely their phonon replicas, although these aren’t resolvable at the current system resolution) A1 (140-160meV), A2 (165-180meV) and A3 (225-245meV). Defect energies similar to all three of these levels have previously been measured using both PL and the Photo-Induced Current Transient Spectroscopy (PICTS) technique. Yang et al [98, 99] observed, using PL, a defect band very similar to that observed in figure 4.28 with defect levels very similar in energy to A1 and A2; these were attributed to vacancies and their complexes or A-Centres as they are more commonly known (see figure 4.31). Investigations using the PICTS technique by Cavallini et al [61, 106] have also observed levels similar to A1 and A2 and again attributed them to A-Centres. Interestingly in the same papers Cavallini also observes level A3 and speculates its origin to be Zn-related as it is only seen in CdZnTe samples and not in CdTe. Using the PL mapping technique it is possible to map the spatial distribution of these defects for each sample. Such an analysis has to be performed with care and the assumption is made that the defect concentration is related to the strength (amplitude) of the defect emission. Due to variations in the surface quality and reflectivity as well as variations in the energy per pulse of the laser the relative amplitude (the ratio of the defect amplitude to that of the (D0 ,X) emission) of the defect is mapped. Figure 4.32 shows the spatial distribution of the defects for sample YI-44. For all three defects the concentration is observed to be higher around the edges of the sample than at the centre where a circular area of low defect band emission intensity is observed; this distribution of defects is repeatedly seen for all the MVB samples. The distinctive shape of the distribution leads to the


87

Figure 4.31: The defect band observed by Yang et al [98] in indium doped CdZnTe

suspicion that this may be an artifact of the sample processing; the PL technique is very sensitive to the surface condition (as above band gap light is used) and if any damage does remain from the surface processing then it may well effect the emissions that are seen. It is known that if the sample is lapped for too long or under too little pressure then a common effect is that the sample surface becomes domed. If such a domed sample was then chemi-mechanically polished it could result in an incomplete etch in certain areas of the crystal surface leaving behind an excess of defect states. As a comparison the same data was taken for Redlen sample RD-09 who’s processing was completed by Redlen Technologies rather than at Surrey. The results of the measurement can be seen in figure 4.33. In the case of the Redlen sample the defect band is observed but it appears that there is an even distribution across the sample surface rather than the circular distribution seen for sample YI-44; there is an increased defect luminescence at the extreme edge of the sample but this originates from the chipped edge of the sample that remains from dicing. This result lends weight to the argument that the observed distributions are a result of the surface processing; to further investigate this the sample surfaces were studied using an AFM.


Figure 4.32: The spatial distribution of defects (i) A1, (ii) A2 and (iii) A3 in sample YI-44

88


Figure 4.33: The spatial distribution of defects (i) A1, (ii) A2 and (iii) A3 in sample RD-09

89


4.3.3

90

Atomic Force Microscopy - A Correlation with PL Measurements

To test the theory that some of the PL results may be correlated to the surface quality the samples surfaces were studied using an Atomic Force Microscope (AFM), located in the Materials Science Department of the University of Surrey, with the kind help of I.Jurewicz. Sample YI-44 showed a strong spatial correlation of the PL defect band and so was chosen for an in-depth study. Areas of the sample surface were studied in a number of different positions to try and detect differences in the surfaces. In total eight positions were studied, five positions at the sample edges, two at the sample centre and one in the sample corner. Figure 4.34 shows topographic representations of the surface at the sample centre and edge. The surface roughness was measured for a total of 8 positions on the sample, figure 4.35 shows histograms of the sample height for the two positions showed previously in figure 4.34. The surface roughness (rA ) in each case is evaluated from the width of the distribution of the sample height (Z) and was found to be ∼9nm at the sample centre and ∼6nm at the sample edge. Figure 4.36 shows the eight different positions examined with the AFM as well as the roughness measured at the position. The data shows that, in general, the centre of the sample appears to have the roughest surface; this seems to confirm the suspicion that the sample was domed during the surface processing but the fact that the position also corresponds to the lowest intensity emission of the PL defect band seems strange. If other recombination processes are considered it may be possible to explain the low defect emissions seen at the sample centre. It has been shown in the literature [75, 76] that the surface condition can have a strong effect on surface recombination. It seems reasonable to assume that at the surface there may be a greater concentration of defects that can lead to non-radiative recombination of carriers. If there is a variation in the surface quality then this could also result in variations in the relative strength of the different recombination processes; suggesting that there may be a greater number of defects at the sample centre that lead to an increase in non-radiative recombination events. Measurements, for comparison, were also made on the early Redlen sample (RD-09), figure 4.37 shows a topographic representation of a 50µm2 area at the centre of the crystal surface and a histogram displaying the distribution of sample height. Across the whole surface of RD-09 a high degree of flatness is observed; an exceptional surface roughness of ∼1nm is also measured at both the sample centre and edge. This uniformity of the surface and the low surface roughness correspond well with the PL observations of a low intensity defect band. The AFM results appear to confirm that the surface conditions of the samples have a large effect on the PL observations, which is no surprise considering the use of above


91

Figure 4.34: Topographic representations of 100µm2 areas of the crystal surface at (i) the sample centre and (ii) the sample edge

band gap light as the excitation source, and that the PL results must be treated with caution as they may not reflect the defect structure of the bulk crystal.

4.4

Electrical Performance

If useful detectors are to be produced from CdZnTe material then careful consideration must be given to the electrical properties of the crystal after contacting as a device that


Figure 4.35: Histograms of the surface height and the corresponding surface roughness at the sample centre and edge

Figure 4.36: AFM scan positions for sample YI-44 and associated surface heights and roughness

92


Figure 4.37: Above: A 50µm2 topographic image of the centre of sample RD-09 and Below: A comparison of height distributions

93


94

shows high leakage (dark) currents under bias will not be useful as a spectroscopic detector. Care has to be taken when investigating the source of leakage current in CdZnTe detectors, it can be difficult to separate the bulk electrical properties of the crystal, such as the material resistivity, from those of the surface and contacts. In recent years much effort has been made to understand the current-voltage (IV) characteristics of CdZnTe devices. Extensive works by Bolotnikov et al [107, 108] have modeled CdZnTe detectors and their contact properties and successfully reproduced measured IV curves. The conclusions of their work was that the IV curves can be split into two regions; below ∼0.5V the measured current is limited by the bulk resistance of the CdZnTe and increases linearly with voltage following Ohms law. Above 1V it is the contact properties that dominate the measurements and as a result these high voltage regions of the IV curves are not suitable for evaluating the material resistivity. It is also important to note that in many cases it is the properties of the contacts and material surface that will define the bulk leakage currents and not the bulk resistivity; in other words the CdZnTe material can be of high quality but, if the fabrication is poor, high leakage currents may limit the performance of the final detector.

4.4.1

Detector Fabrication

Before it’s possible to make any electrical measurements contacts must be made to the sample surface. For this study the contacts were deposited on the CdZnTe via thermal evaporation of gold to produce devices with a simple planar configuration (monolithic contacts back and front with no guard ring); the sample sides in the case of the Yinnel material appeared to be in a rough ‘as cut’ condition whereas all the Redlen material had received a 6-side polish from the crystal grower. Once the gold was deposited an initial measurement of the device IV characteristics was made using the arrangment described in section 3.3.1. Figure 4.38 shows the IV curves of three of the Yinnel samples. Under reverse bias the devices show very similar behaviour with all three displaying a leakage of 0.3 nA/mm2 at a field strength of 60 V/mm−1 , however, when the bias direction is reversed the response of the devices are very different. Under a positive bias of 60 V/mm−1 devices YI-44 and YI-51 show a leakage of 0.3nA/mm2 and 0.2nA/mm2 respectively and have almost symmetric IV curves, this is in stark contrast to sample YI-50 which shows a leakage of 3nA/mm2 an order of magnitude higher. All samples underwent exactly the same preparation and were contacted in the same thermal evaporation so explaining why the IV curve of YI-50 is so different is difficult. As only a simple contact structure has been used the sides of the samples may contribute a large amount to the measured leakage current. To combat this effect after the initial IV


95

Figure 4.38: The IV curves of Yinnel samples directly after fabrication

measurements were made the samples underwent a passivation step. Passivation of the samples was completed by dipping in 30% H2 O2 for 30s followed by a wash in deionised water and then dried. The passivation is used to produce a uniform non-conducting oxide (TeO2 ) layer around the sample edges which reduces the contribution of the side leakage to the measured bulk leakage current. Figure 4.39 shows the effect of the passivation on samples YI-44 and YI-50. In both samples there is a marked decrease in the measured current for both bias polarities of on average ∼50% although an asymmetric IV curve is still observed in the case of sample YI-50.

4.4.2

Material Resistivity

If instead of measuring currents generated under high voltages those at voltages of +/0.5V and below are studied then it is possible to determine the bulk crystal resistivity. For all the IV curves the low voltage region was found to be very linear and followed Ohms law allowing the calculation of the bulk resistivity from the gradient of a linear regression to the data using equation 4.7. ρ=

AV Id

(4.7)

Where A and d are the contact area and the device thickness respectively. Figure 4.40 shows the the IV curves measured for the highest resistivity sample and lowest resistivity


96

Figure 4.39: The effect of passivation on the IV curves of (i) YI-44 and (ii) YI-50

sample used in this study and the results of a fit to equation 4.7 for both positive and negative bias. For most of the samples there is a small difference in the resistivity evaluated under the two different bias directions; table 4.5 gives a summary of the results. For all the samples measured the resistivities are in the range expected for CdZnTe material. The results can also be compared with the zinc concentrations measured previously from the room temperature PL data. Figure 4.41 shows a plot of zinc concentration against measured resistivity, the data points show some scatter but there is a clear correlation between the two values.


97

Figure 4.40: The evaluation of resistivity for samples YI-44 and RD-13 Sample

No. YI-44 YI-50 YI-51 YI-52 YI-58 RD-13 RD-14

Resistivity (Ωcm)

+VE Bias 1.5x1010 1.2x1010 1.2x1010 0.5x1010 0.7x1010 0.5x1010 1.3x1010

-VE Bias 1.8x1010 1.4x1010 1.4x1010 0.8x1010 1.4x1010 0.5x1010 0.6x1010

Mean 1.7x1010 1.3x1010 1.3x1010 0.6x1010 1.1x1010 0.5x1010 0.9x1010

Table 4.5: Sample resistivities under positive and negative bias

4.5

Summary

In this chapter techniques for the preparation of CdZnTe detectors have been investigated and these were complimented with a number of non-destructive characterisation experiments used to study crystal properties. In the first section it was shown that although adequate preparation of the crystal surfaces using simple equipment was possible; if high quality surfaces were required then advanced processing equipment was needed. Using simple processing equipment at the University of Surrey a final surface roughness of ∼3nm was achieved although it was shown that the etching stage produced a number of undesirable surface features thought to be a result of Te inclusions in the bulk crystal (see figure 4.3). Through the use of the advanced processing equipment bought under


98

Figure 4.41: The correlation between measured zinc concentration (PL) and measured material resistivity (IV)

the Hexitec collaboration the surface roughness was further reduced to ∼1nm and the resulting surfaces displayed none of the features observed in those crystals processed by the simple technique, this is thought to be an advantage of the chemi-mechanical polish (see figure 4.5). Following the surface preparation the samples were studied using IR imaging equipment; images of the MVB (Yinnel) grown material revealed the presence of Te inclusions in all of the samples. In some of these samples, such as sample YI-51, the inclusions were shown to gather in spatially correlated groups along what are thought to be grain or twin boundaries (see figure 4.8). The inclusions were typically triangular in shape and were found to have areas of between 1-40µm2 ; along the observed boundaries they appeared in two groups those of areas ∼10µm2 and those of ∼2µm2 . In sample YI-52 inclusions were observed and were accompanied by extended defects known as pipes running through the sample. Inclusion densities for the Yinnel samples were typically between 400 and 600mm−3 . Samples grown via the THM (Redlen) method were also studied; these samples had received extended post-processing involving a number of annealing steps. The THM samples showed very few inclusions (see figure 4.11), an initial measurement of the inclusion density gave a value of 16mm−3 over an order of magnitude less than the MVB samples. After image-processing (to increase the contrast) a number of smaller inclusions were observed and the measured inclusion density increased to 90mm−3 which was still considerably less than those measured in the other samples. The reduction in the inclusion densities in the Redlen samples is thought to be the result of the extra cadmium annealing step that the samples underwent.


99

Room temperature photoluminescence measurements were used to study the distribution of zinc concentration in a number of the CdZnTe samples. The samples studied were all produced with nominally 10% zinc concentration, the PL measurements showed that the actual zinc concentration varied significantly between samples in the range 6-10%. Although the zinc concentration varied from sample to sample the small scale variation for each individual sample was found to be 6x10−3 cm2 V−1 (see table 5.1). Digital pulse shape data was taken and used to determine the carrier mobilities. In the case of the Yinnel material the electron mobility was found to vary between 550-770cm2 V−1 s−1 which is lower than the generally accepted value for CdZnTe of 1000 cm2 V−1 s−1 (table 5.2). The low electron mobility may be due to an increased defect concentration in comparison to the Redlen material which displays electron mobilities similar to that of the literature. Measurements of the hole transport properties were also attempted. As expected, for those samples where it was possible to measure them, the hole transport properties were significantly poorer than those of the electrons with µh τ h ∼5x10−6 cm2 V−1 (see figure 5.4) and µh ∼20 cm2 V−1 s−1 (see figure 5.9). Both the mobility-lifetime and mobilities of the holes compare well to previously published values although it should be noted that the estimated lifetimes of holes in the Yinnel material are found to be almost an order of magnitude less than those published. These decreased lifetimes may again be related to a large concentration of impurities and defects in the Yinnel material.

Charge Transport Properties of Spectroscopic CdZnTe Detectors

135

To study the uniformity of detector response the micro-focus proton beam at the University of Surrey Ion Beam Centre was used to map the transport properties of detector YI-06. An area of 2.5mm x 2.5mm was studied using 2MeV protons with a beam size of ∼5µm. Maps of the electron transport properties showed a uniform response across the area studied (see figure 5.12) which was in contrast to that of the holes which showed large spatial distributions of mobility-lifetime (see figure 5.16). It was deduced that these variations in the mobility-lifetime were the result of fluctuations in the hole lifetime as the hole mobility was found to be uniform in the area studied (see figure 5.19). These variations in the lifetime are likely to be the result of spatial distributions of crystal defects and impurities. It has been known for a long time that hole transport is poor in CdZnTe but the fact that there is a distribution of the hole transport properties may also have an effect on the spectroscopic performance of detectors especially at higher γ-ray energies where the effects of hole transport become significant. Finally spectroscopic measurements were made for a range of photon energies with a large spread in resolutions observed. These variations showed some correlation to the measured inclusion densities and zinc concentrations of each crystal (see figures 5.22, 5.23). Of those detectors measured the best performance was observed in detector RD-13 which displayed a FWHM of 7.5keV at an energy of 60keV. Measurements showed that the spectroscopic resolution of detectors at Surrey were limited by the electronic noise of the measurement system. A number of commercial detectors, with properties similar to those at Surrey, were studied at RAL using a low-noise, high-resolution spectroscopy system (see figure 5.26). Using the RAL system higher resolution was achieved with a Yinnel detector demonstrating a FWHM of ∼5keV compared to the ∼8keV seen with similar detectors at Surrey for the 60keV peak of 241 Am. X-ray measurements were also made at reduced temperatures in the range 290K-200K for two CdZnTe detectors. In both cases the energy resolution was degraded at the lower temperatures (see figure 5.27) and this is though to be due to variations in the charge transport properties linked to the defect structure of the crystals.

Chapter 6

Low Temperature Phenomena in CdZnTe In the previous two chapters a number of effects have been observed when the temperature of CdZnTe detectors is decreased; one major observation was that on reducing the temperatures of the detectors a degradation of the spectroscopic resolution was observed. Such low temperature phenomena are intrinsically tied to the defect structure of the material with crystal defects and impurities influencing the behavior of detectors both at high and low temperatures. In this chapter the effect of temperature on the transport properties of CdZnTe will be investigated more thoroughly and then using both low temperature current-voltage measurements and the PICTS technique attempts will be made to identify those defect levels responsible for these effects.

6.1

Low Temperature Charge Transport Properties

A number of authors have investigated the effect of temperature on the properties of CdZnTe, some have shown a reduction in the spectral performance of detectors [121, 122] at reduced temperatures while others have shown how the carrier transport properties change as the temperature is lowered [71, 97, 116]. In the following section alpha particle spectroscopy and pulse shape data will be used to investigate how the transport properties of the Yinnel and Redlen materials change in the temperature range 120K-320K.

6.1.1

Low Temperature Mobility-Lifetime

The same experimental set-up was used as discussed in section 3.3.2 with the cryostat temperature controlled between 120K and 320K using liquid nitrogen; a period of an 136

Low Temperature Phenomena in CdZnTe

137

hour was allowed between each temperature to allow the detector and cryostat temperatures to stabilise. Like the previous room temperature measurements the 5.5MeV alpha particle of an

241 Am

source was used to excite the detector. A large shaping time of

10µs was selected to try and avoid ballistic deficit resulting from increased pulse lengths (for some detectors) at low temperatures. For this set of measurements only the electron transport was studied as, like at room temperature (see section 5.1.2), the transport of holes in the detectors was very poor and became worse with the decreasing temperature. • Yinnel Samples Measurements were made for three Yinnel samples YI-44, YI-50 and YI-58. For each temperature, typically, spectra were collected for 10 or more different voltages and then used to extract the electron mobility-lifetime via a Hecht analysis. Figure 6.1 shows Hecht plots for a number of different temperatures taken with device YI-44 as well as example spectra taken under a bias of 300V. Close to room temperature (320K-270K) not much change is observed in the response of the detector, however, below 270K the mobility-lifetime begins to drop; this fall is repeated in all the Yinnel samples studied. Figure 6.2 shows the evolution of µe τ e with temperature for the three Yinnel detectors; each device shows a drop in µe τ e below 240K ranging from 20% for YI-50 to 5% for YI-44. Interestingly all three devices appear to approach a similar mobility-lifetime of ∼5x10−4 cm2 V−1 around 120K and this may suggest that a common factor is limiting the electron transport in all the samples. • Redlen Samples Using the same setup measurements were taken for the two Redlen samples RD-13 and RD-14. The analysis of the data proved more difficult than that collected with the Yinnel devices with both RD-13 and RD-14 showing unexpected effects at temperatures below 270K. In the case of sample RD-13 the device adheres to the single charge carrier Hecht equation in the temperature range 270K-320K, however, below 270K the standard Hecht equation will no longer fit the data points. To fit this data a third variable must be introduced to the Hecht equation, a voltage offset (Vi ), as seen in equation 6.1. " µe τe (V − Vi ) 1 − exp CCE = d2

d2 − µe τe (V − Vi )

!# (6.1)

Figure 6.3 shows a plot of the data taken at 210K along with fits using the standard form of the single charge carrier Hecht equation and equation 6.1. The use of an


Figure 6.1: (Above) Hecht analysis of alpha pulse height spectra taken with sample YI-44 at different temperatures (Below) Alpha Spectra at different temperatures under a bias of 300V

138


Figure 6.2: The variation of µe τ e with temperature for devices YI-44, YI-50 and YI-58

Figure 6.3: Data taken at 210K with device RD-13 and fits using a standard and modified Hecht equation

139


140

offset such as that shown in figure 6.3 has previously been required to fit low temperature data taken with commercial Yinnel detectors and was the focus of a paper published by the author [123]. Vi is an internal voltage that represents a build up of space charge in the device which apposes the applied bias polarising the device. This results in an effective voltage (V’) where V’=V-Vi , this is a simplistic model and in reality any polarisation effect will be dependant on many factors such as depth of interaction, exposure rate and operating temperature, but as an approximation the use of Vi fits the data well. Using the modified fit µe τ e was calculated for each of the temperatures measured. Figure 6.4 shows how the Hecht plots vary with temperature and the effect on the spectra taken at 300V. From these plots it is obvious that the response of the detector at low temperatures is much more complicated than at room temperature with large voltage offsets ranging from 30-100V required to fit some data sets. The use of a voltage offset is also accompanied by a second peak in the alpha particle spectra whose origin is unknown but is likely to be a result of non-uniformities of either the electric field or charge transport properties at the low temperatures. In the case of detector RD-14 time-dependant polarisation proved to be a problem with significant changes visible in the pulse height spectra over a timescales of a minute for temperatures of 240K and below suggesting a variation in the magnitude of Vi with time; no such effect was observed in sample RD-13. Figure 6.5 shows the shift in the alpha pulse height peak position over the course of 100s in 1000 pulse intervals, the peak CCE is seen to move from ∼40% to 20%. To avoid the polarisation effect data acquisition was stopped at each voltage as soon as the peak began to shift noticeably, in most cases this worked but at temperatures around 240K this proved tricky as the device polarised quickly. Figure 6.6 shows how both the peak shape and Hecht analysis changes at low temperatures for device RD-14. Below 300K a clear change in the behavior of the detector can be observed with the peaks shifting to lower CCE’s corresponding to a decrease in µe τ e , peak amplitudes are low as the number of counts taken was limited by the varying polarisation effect. Interestingly there seems to be a recovery of both the spectroscopic resolution and mobility-lifetime at 150K, the reason for this is unknown, it should also be noted that no voltage offset was required for fitting the data taken with RD-14. For both RD-13 and RD-14 the electron mobility-lifetime was calculated at each temperature and the results may be seen in figure 6.7. The data for the two samples show some difference in the absolute measured values of µe τ e but the general trends observed are similar. In the case of sample RD-13 there is an initial rise in the mobility-lifetime to a maximum value of 3x10−2 cm2 V−1 (one of the highest values published) at 270K after which there is a fall of over 70% before a


Figure 6.4: (Above) Analysis of low temperature data taken with RD-13 (Below) Spectra at a fixed bias of 300V at different temperatures

141


Figure 6.5: Alpha pulse height spectra of RD-14 for successive intervals of 1000 pulses over the course of 100s at 240K

142


Figure 6.6: (Above) Analysis of low temperature taken with RD-14 (Below) Spectra at a fixed bias of 300V at different temperatures

143


144

Figure 6.7: The variation of µe τ e with temperature in Redlen samples RD-13 and RD-14

small recovery at 150K. In the case of sample RD-14 there is a small rise in µe τ e between 320-300K after which there is a fall of ∼80% followed by a small recovery, as with RD-13, at 150K. It is interesting that in both the Yinnel and Redlen samples, independent of the absolute value of the mobility-lifetime at room temperature, there is always a fall in µe τ e below 270K suggesting that the origin of the reduction is the same in all of the CdZnTe samples studied. This may suggest that it is due to defect levels of a similar energy common to all the materials that causes the internal voltage offset.

6.1.2

Low Temperature Mobility

Although the low temperature alpha pulse height data shows polarisation effects below 240K above this temperature the response of the devices appeared to follow the Hecht equation; this suggests that at these temperatures there is no significant change to the electric field in the samples. If the electric field is assumed to be constant then the variation in the µe τ e values observed in the temperature range 240-320K must be due to some other effect. To investigate these variations in µe τ e pulse shape data was collected in tandem with the alpha pulse height spectra and were used to calculate the electron mobility at the reduced temperatures as described previously (see section 5.2).


145

• Yinnel Samples Measurements were made for the three Yinnel samples with all three showing similar trends. Figure 6.8 shows typical pulse shapes seen at low temperatures for voltages of 80V and 300V. For temperatures in the range 270K-320K the pulse

Figure 6.8: Typical pulse shapes observed at low temperatures at biases of (i) 80V and (ii) 300V

shapes display a linear drift, however, for temperatures of 240K and below pulses contain a slow component which becomes more pronounced at low voltages. Such slow components may be due to the thermal release of charge from traps and are


146

independent of the applied bias voltage and so do not represent the drift of the primary charge carriers in the applied field. To evaluate the electron mobility only the linear drift of the carriers must be considered, the slow component makes this analysis difficult. Figure 6.9 shows histograms of the pulse rise times calculated using a 10-90% algorithm in the temperature range 240K-320K for voltages of 80V and 300V. A distinct change in the histograms at both voltages can be seen

Figure 6.9: Pulse rise time histograms at different temperatures for applies biases of (i) 80V and (ii) 300V

between 240K and 270K with a much broader distribution of rise times observed at the lower temperature. These rise times will inevitably include a portion of the


147

slow component leading to the broadening of the distribution, for this reason the data taken below 270K is unsuitable for calculation of µe . For temperatures greater than 240K the slow component either isn’t apparent or only represents a small part of the drift and, as such, a calculation of the mobility is possible. Figure 6.10 shows the variation of mobility between 270K and 320K for the three Yinnel devices, errors are taken from a Chi-Squared fit to the rise time data. In all three detectors a decrease in the mobility is observed at the lower

Figure 6.10: Variation of µe in the temperature range 320K-270K for Yinnel detectors

temperatures, this is in contrast to previous reports by Suzuki et al that describe an increasing electron mobility at low temperatures [71, 97]. In the Suzuki papers to accurately describe the variation of mobility with temperature a trap-controlled mobility (µd ) was introduced as defined by equation 6.2: " µd = µ0

NT ET 1+ exp NC KT

!#−1 (6.2)

where NT and ET are the density and energy of the defect level respectively, NC is the effective density of states and µ0 is the mobility calculated from scattering mechanisms alone. In Suzuki’s data, see figure 6.11, the variation of the electron mobility with temperature is described by a trap of energy ET =23meV below the conduction band with a concentration of NC =1.4x1016 cm−3 . The data for the Yinnel detectors suggests that either a higher concentration of the level described by Suzuki et al or a different, higher energy, level limits the transport of the electrons.


148

Figure 6.11: Low temperature electron mobility data measured by Suzuki et al [71]. The curves indicate the contributions of polar optical scattering (µpo ), alloy scattering (µal ) and ionised impurity scattering to the overall mobility (µo ) as determined by simulations by Suzuki. The line denoted µd is the trap controlled mobility proposed by Suzuki

Some information on the energy of the defect levels active over this temperature range can be gained from an analysis of the slow components observed [124, 125]. If the slow components are thermally activated then the measured charge (Qt ) at any time in the drift will be given by equation 6.3. " Qt = Q0 + Q1 1 − exp

t − τT

!# (6.3)

Where Q0 and Q1 are the amplitudes of the fast and slow components respectively and τ T is the time constant of the release of charge from the traps. The time constant itself will depend on both the ambient temperature and the trap properties and this relationship is given by equation 3.4. A strong slow component was observed for sample YI-50 and so data was taken between 225K and 245K (where the component was strongest) in 5K steps allowing


149

an hour at each step for the system to reach thermal equilibrium; at each temperature 5,000 pulses were recorded. To extract the de-trapping time (τ T ) pulses were logged and a linear fit to equation 6.4 applied to the slow component of the pulse observed after the initial fast transport is complete. ln[Q − Q(t)] = ln(Q1 ) −

t τT

(6.4)

Figure 6.12 shows a pulse taken at 235K and includes a linear regression to the slow tail as shown. This process is repeated for each of the 5,000 pulses at each

Figure 6.12: A logged waveform taken with device YI50 at 235K, a linear fit is made to the slow component of the pulse

temperature to produce histograms of evaluated time constants; to ensure that only pulses demonstrating a strong exponential tail are accepted only the strongest fits are accepted (R2 >0.99). An average value of the time constant at each temperature is then extracted from histograms using a gaussian fit. Using equation 3.4 it is then possible to extract both the trap energy and cross-section from an Arrhenius analysis of a plot of 1/T against ln(T2 τ T ). The upper image of figure 6.13 shows time constant histograms for a number of temperatures and the lower image shows the resulting Arrhenius plot. The


Figure 6.13: (Above) Histograms of de-trapping time constants at different temperatures (Below) an Arrhenius analysis of the time constant data

150


151

Arrhenius analysis made to equation 3.4 gives a trap energy of 0.20eV and a crosssection of 2x10−15 cm−2 over the temperature range 220-250K. Traps of this energy have already been observed in PL data at low temperatures in the Yinnel material, see table 4.4, and the low temperature pulse shape transient data suggests the level to be a donor defect (electron trap). • Redlen Samples Digital pulse shapes at low temperature were also taken for the two Redlen samples and, like in the previous section, both showed very different responses. In the case of RD-14 two effects made the analysis of the low temperature mobilities difficult; the first was the problem of polarisation (discussed in the previous section) that limited the amount of useful pulses that could be taken. The second effect was the presence of ’non-uniform’ pulse shapes; figure 6.14 shows two example pulses taken under a bias of 80V with device RD-14. It is clear from the figure that

Figure 6.14: Strange pulse shapes observed in sample RD-14

the pulses do not demonstrate uniform carrier drift with a clear kink present in the pulse shapes; the drift after these kinks doesn’t appear to be exponential and so it is unlikely to be the result of de-trapping events. Pulses like these became more varied at the low temperatures and resulted in multiple peaks in rise time histograms; for these reasons only the mobilities close to room temperature were


152

calculated and these are shown in figure 6.15. Like the Yinnel samples a decrease in the mobility is seen suggesting that in the case of RD-14 the transport is affected by either a deeper level, or higher concentration of levels, than that suggested by the model of Suzuki et al [71, 97]. In the case of sample RD-13 the analysis of the pulse shape data was found to be

Figure 6.15: Analysis of electron mobility at two different temperatures for RD-14, (inset) calculated mobility values

much easier with pulses displaying linear drift at all temperatures, example pulse shapes at 300V can be seen in figure 6.16. As the pulse shapes displayed uniform drift for all temperatures it was possible to calculate mobilities over the whole range studied. Figure 6.17 shows example rise time histograms taken at a bias of 300V for a number of temperatures as well as the analysis of the drift mobility at those temperatures. Unlike the previous Redlen and Yinnel samples µe is actually seen to increase at the lower temperatures; this is shown in figure 6.18. The observed trend more closely resembles that observed by Suzuki et al and suggests that, in the case of RD-13, the electron mobility is either less strongly influenced by shallow traps compared to the Yinnel samples or that their relative concentration is reduced.


153

Figure 6.16: Alpha pulse shapes taken with device RD-13 under a bias voltage of 300V for varying temperatures

6.2

The Identification of Material Defect Structure

In previous chapters it has been suggested that a number of the observed device properties are related to the material defect structure. In chapter 4 it was suggested that defects were responsible for emissions seen in low temperature PL measurements and then in chapter 5 the variation in detector charge transport properties were explained by variation in the defect content from device to device. Most recently it has been shown that defects effect the spectroscopic performance of devices at low temperatures through both trap-controlled transport properties and de-trapping events. In this next section two different techniques will be used to identify the material defect structure and the traps that may be responsible for some of the effects observed.

6.2.1

Low Temperature Resistivity

A materials resistivity is related to the free carrier concentrations which in turn is related to those intrinsic and extrinsic defect levels present in the material [126]. Like any other trap related property the carrier concentrations will be highly temperature dependant and this leads to a thermally activated resistivity [127, 128, 129]. The dependance of the material resistivity on temperature can be described using equation 6.5 assuming only one level is active.


Figure 6.17: (Above) Rise time histograms collected at 300V for different temperatures with RD-13, (Below) calculation of the electron drift mobility at the same temperatures

154


155

Figure 6.18: The variation of electron drift mobility with temperature for device RD-13; arrow indicates order in which measurements were made

ρ(T ) = ρ0 exp

ET − kT

! (6.5)

Where ρ0 is the material resistivity at 0K. If the material resistivity is measured as a function of temperature then it is possible to determine the activation energy of the controlling defect. In reality there may be a number of levels that contribute to the resistivity values and the measured energy may not be indicative of an individual level but is instead related to the position of the fermi level in the band gap [129]. Measurements were made using the setup described in section 3.3.1 with the devices mounted inside the cryostat and under vacuum. Temperatures were varied between 250K-320K in 10K steps waiting an hour at each temperature for the system to stabilise; lower temperatures were not measurable due to the extremely small currents generated (

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