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Record W3006531459 · doi:10.1002/pssa.201900885

Emerging Applications of III‐Nitride Nanocrystals

2020· article· en· W3006531459 on OpenAlexaff
Xianhe Liu, Faqrul A. Chowdhury, Srinivas Vanka, Sheng Chu, Zetian Mi

Bibliographic record

Venuephysica status solidi (a) · 2020
Typearticle
Languageen
FieldMaterials Science
TopicMXene and MAX Phase Materials
Canadian institutionsMcGill University
FundersArmy Research OfficeDivision of Electrical, Communications and Cyber SystemsNational Science Foundation of Sri LankaNational Science Foundation
KeywordsNanocrystalNitrideMolecular beam epitaxyMaterials scienceOptoelectronicsNanotechnologyQuantum dotEpitaxy

Abstract

fetched live from OpenAlex

Recently, significant progress has been made in III‐nitride nanocrystals. They exhibit unique structural, electronic, optical, and photocatalytic properties, and have emerged as a functional platform to realize high‐performance optoelectronic, electronic, quantum, and solar energy devices. Compared with conventional III‐nitride epilayers and quantum wells, dislocation‐free III‐nitride nanocrystals can, in principle, be achieved on lattice mismatched foreign substrates due to the efficient surface strain relaxation. In this Feature Article, the authors discuss the epitaxy, characteristics, and some emerging device applications of III‐nitride nanocrystals grown by plasma‐assisted molecular beam epitaxy.

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 score0.068
Threshold uncertainty score0.693

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)0.0010.000

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 head0.020
GPT teacher head0.281
Teacher spread0.261 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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