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Record W3142089637 · doi:10.1039/d0ra05134a

AlN PEALD with TMA and forming gas: study of plasma reaction mechanisms

2021· article· en· W3142089637 on OpenAlexaff
Mengmeng Miao, Ken Cadien

Bibliographic record

VenueRSC Advances · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsAlberta Hospital EdmontonUniversity of Alberta
Fundersnot available
KeywordsPlasmaAtomic layer depositionMaterials scienceDeposition (geology)Absorption (acoustics)DielectricThin filmLayer (electronics)Analytical Chemistry (journal)ChemistryNanotechnologyEnvironmental chemistryComposite materialOptoelectronics

Abstract

fetched live from OpenAlex

The effect of deposition temperature and plasma dose on plasma-enhanced atomic layer deposition (PEALD) of AlN thin films with forming gas plasma and trimethylaluminum (TMA) has been studied. The temperature has a strong effect on TMA absorption considering the d-TMA absorptions at low deposition temperatures. The plasma effect on AlN growth was studied in terms of three aspects: (1) plasma effect on TMA absorption, (2) plasma effect on the insertion of plasma species and creation of chemical bonds with absorbed surface species, (3) plasma effect on the removal of organic ligands and weakly-bonded surface species. Plasma over-dosing and under-dosing not only affect the film growth rate but also the AlN film properties. A three-effect mathematical model of the plasma effect was built based on the three plasma effects, which is consistent with the AlN experimental growth results. The FTIR and dielectric studies of the PEALD AlN films support the model.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.041
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.248
Teacher spread0.237 · 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 teacher head, 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".

Quick stats

Citations10
Published2021
Admission routes1
Has abstractyes

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