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Record W3102599675 · doi:10.1063/5.0013183

Electron transport within bulk cubic boron nitride: A Monte Carlo simulation analysis

2020· article· en· W3102599675 on OpenAlexafffund
Poppy Siddiqua, Michael S. Shur, Stephen K. O’Leary

Bibliographic record

VenueJournal of Applied Physics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBoron nitrideMonte Carlo methodElectric fieldCondensed matter physicsElectronSteady state (chemistry)Materials scienceDrift velocitySemiconductorNitridePhysicsChemistryNanotechnologyQuantum mechanicsPhysical chemistryOptoelectronics

Abstract

fetched live from OpenAlex

Through the use of a semi-classical three-valley Monte Carlo electron transport simulation analysis, we analyze the nature of the steady-state and transient electron transport processes that occur within the zinc-blende phase of bulk boron nitride. For the purposes of our steady-state analysis, the dependence of the electron drift velocity on the applied electric field strength is examined. For our transient electron transport analysis, however, we study how an ensemble of electrons, initially in thermal equilibrium, i.e., zero-field, responds to the sudden application of a constant and uniform applied electric field. The results obtained, corresponding to the specific case of bulk zinc-blende boron nitride, are then contrasted with those corresponding to a number of other compound semiconductors of interest within the III–V nitride semiconductor genome.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.015
GPT teacher head0.248
Teacher spread0.233 · 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 designSimulation or modeling
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

Citations11
Published2020
Admission routes2
Has abstractyes

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