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Record W7132984477

Reactively Sputtered Aluminum Oxynitride Deposited at Ambient Temperature: A Material Platform for Tunable Optical Applications

2022· dissertation· W7132984477 on OpenAlexaff
Liam McRae

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldMaterials Science
TopicAdvanced ceramic materials synthesis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDeposition (geology)Thin filmCharacterization (materials science)Refractive indexAluminiumMaterial propertiesSputter depositionSputtering
DOInot available

Abstract

fetched live from OpenAlex

The objective of this study is to assess the material system of Aluminum Oxynitride, deposited through a low-temperature reactively sputtered process, as a potential thin film material platform for tunable optical applications across a broad UV-NIR spectral region. A thorough design of experiment assessment of the compositional and optical properties of the thin films is carried out with respect to the deposition parameter space explored herein. The as-deposited films exhibit distinct relationships between the deposition parameters explored and the realized atomic compositions, extending from AlN on the one end to approaching the γ- and spinel- AlON. Moreover, the deposition parameters and compositions obtained correspond strongly to the calculated optical properties, which exhibit a maximum change in refractive index of Δn1550,720=0.4 and a Δn320=0.6. Supplemental electrical characterization was undertaken on samples deposited with and without oxygen, where improved ion interflow is observed in the oxygenated samples. The demonstrated experimental results suggest that the aluminum oxynitride material platform has the potential for broad-spectrum tunable photonic applications.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
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 score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.001

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 head0.018
GPT teacher head0.311
Teacher spread0.292 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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