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Record W4395476333

Point defects in Aluminium Nitride for quantum technologies

2023· dissertation· fr· W4395476333 on OpenAlexfundno aff
A. Aghdaei

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2023
Typedissertation
Languagefr
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundUniversité de Sherbrooke
KeywordsAluminium nitrideAluminiumNitridePoint (geometry)Computer scienceMaterials scienceNanotechnologyMetallurgyMathematics
DOInot available

Abstract

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Point defects strongly affect the electronic and optical properties of semiconductors: a better understanding of the impact of these defects on the performance of devices based on these materials is therefore of great technological interest. Over recent years, point defects have been shown to possess properties of interest for applications related to quantum computing, sensing, and communication. Point defects in AlN recently attracted considerable attention due to their ability to act as a qubit for quantum applications. Indeed, negatively charged nitrogen vacancies, group IV impurity (Ge, Sn, Ti, and Zr)–vacancy pairs, and, more recently, large metal ion (Y, La, Zr, and Hf )–vacancy pairs in AlN, have been theoretically reported as promising qubit candidates. This thesis presents the result of the study of various new point defects in AlN for quantum technology applications. The main goal of this exploratory project is to determine the influence of different implantation species and different thermal annealing conditions on the creation of point defects in AlN. Two types of AlN films were studied in this thesis, namely, single crystal AlN on the sapphire substrate and polycrystalline AlN layer on a highly-doped silicon substrate. First, we studied the formation of defects in AlN films (on the sapphire substrate), subjected to high-energy hydrogen and titanium ion implantation followed by thermal annealing under argon atmosphere at different temperatures. X-ray diffraction and Raman spectroscopy show that ion species and the implantation process could alter the amount of local strain in AlN films. Electron spin resonance spectroscopy reveals resonance peaks with g-value higher than that one of a free electron (2.0023) for both H-implanted and Ti-implanted AlN films after annealing for 1h at 1050 ◦C. The origin of these peaks is attributed to different types of point defects. For the Ti-implanted film, in addition to the central peak, a half-field resonance peak has been detected and assigned to spin-triplet (S=1), which might be interesting for quantum applications. The optical properties of defects in H-implanted and Ti-implanted AlN films were studied using a conventional PL setup exciting at 532 nm and 266 nm. It should be noted that the PL studies of the samples revealed a broad background, which could be associated with the sapphire substrate. This broad peak could potentially mask the PL peaks originating from point defects in AlN. Therefore, our subsequent studies will focus on the AlN films grown on highly doped Si substrates. Consequently, we have not examined the effects of Zr and Hf implantation on these AlN films. AlN on the silicon substrate films were implanted with hydrogen, titanium, zirconium, and Hafnium ions. To partially repair the structural damage caused by ion bombardment, the implanted samples were annealed at different temperatures and under different atmospheres including argon, nitrogen, and forming gas (FG, 95 % nitrogen + 5 % hydrogen). Our results show that the photoluminescence spectra of most of the annealed samples and the as-grown AlN films are very similar, which demonstrates that no new defects were introduced in AlN. The only exception was the Zr-implanted AlN films. For the AlN films subjected to high-energy Zr ion implantation, the X-ray diffraction, Raman spectroscopy, scanning electron microscopy, and atomic force microscopy measurements show that the structural and morphological properties of the Zr-implanted AlN films depend on the annealing gaseous environment. Post-implantation annealing under argon atmosphere yields the lowest structured surface roughness with increased grain size while the samples annealed under the forming gas atmosphere showed a high level of damage recovery and the lowest amount of oxygen in close proximity to the surface. Photoluminescence spectroscopy revealed multiple point defects and defect complexes related to emission bands in the visible range. A series of absorption bands have been observed using photoluminescence excitation spectroscopy. Compare to as-deposited AlN film, new emission and absorption peaks at 1.7 eV (730 nm) and 2.6 eV (466 nm), respectively, have been identified and attributed to the (ZrAl − VN )0 defect complexes. To study the emission from (ZrAl −VN )0 defect complexes, we designed a micro-PL setup whitin our research team. Using this setup, the optical properties of the emitters in Zr-implanted AlN films were studied. The study aimed to investigate the potential of these point defects for single photon emitter, applications. Hence, we chose the samples annealed under forming gas atmosphere due to their lower structural damage and the lowest level of oxygen at the surface. Our results reveal micrometer-sized bright spots with ZPL at 4 K at 685.5 nm (1.808 eV) and a lower energy phonon sideband around 700 nm. Based on our previous studies these spots are assigned to the (ZrAl−VN )0 defect complexes. Our results showed a relatively high Debye-Waller factor of around 18.5% at 4K, which might be interesting for quantum single-photon source applications. However, to investigate the potential of these defects as single-photon emitters an antibunching g(2)(τ) measurement is highly recommended. Our investigations into Hf and Ti-implanted AlN films on highly doped Si, did not reveal the emergence of any new PL peaks. Additionally, no ESR signal was detected in these samples. This lack of signal could be attributed to the relatively low annealing temperature employed in our study, which may not have been sufficient to facilitate the complete recovery of the AlN films from the damage caused by implantation. The different crystal structures of the AlN film may have also played a role in the absence of an ESR signal. Furthermore, the low concentration of paramagnetic defects present in the samples could have also contributed to the lack of signal. It is important to note that our study did not entirely rule out the possibility of PL peaks or ESR signals appearing with higher annealing temperatures or different implantation parameters. Further investigation into the effects of varying these parameters on the properties of Hf and Ti-implanted AlN films could provide valuable insights into the behavior of these materials under different conditions. Taken as a whole, the findings of this study underscore the importance of manipulating point defects in AlN for the purpose of advancing quantum applications and the development of optoelectronic materials. However, further refinements are necessary to enhance the density of these point defects, while concurrently minimizing the incidence of defect clusters and the occurrence of a high broadband PL signal level. Such improvements will be vital in ensuring the optimal performance of AlN-based devices for various applications, including sensing, photonics, and quantum information processing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.236
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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