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Record W4400682915 · doi:10.1063/5.0211046

The transition between the collision-dominated and ballistic electron transport regimes as the device length is reduced: A continuum analysis

2024· article· en· W4400682915 on OpenAlexafffund
Alireza Azimi, Mohammadreza Azimi, M. S. Shur, Stephen K. O’Leary

Bibliographic record

VenueJournal of Applied Physics · 2024
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersRES’EAU-WaterNETMitacs
KeywordsCollisionElectronBallistic conductionPhysicsAtomic physicsMaterials scienceCondensed matter physicsNuclear physicsComputer science

Abstract

fetched live from OpenAlex

Noting that the conventional collision-dominated electron transport perspective is only relevant when the length scale over which the transit occurs is greater than the electron’s mean free path, one can conceptually partition the electron transport “space” into collision-dominated and ballistic electron transport regimes. As the boundaries between these regimes are quite porous, in this analysis, we devise a means of quantitatively examining the transition between electron transport regimes as the length scale is reduced on a continuum basis. Our approach introduces a collision-dominated fractional scattering parameter, this parameter quantifying the fraction of the total scattering rate that arises purely from bulk scattering processes, contact scattering also contributing to the total scattering rate. We pursue this analysis for two conventional semiconductors of interest, silicon and gallium arsenide. A determination of the dependence of the results on both the length scale and the crystal temperature is pursued. Finally, for the specific case of room temperature, a comparison with the results of experiment is performed.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.233
Teacher spread0.225 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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