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Record W2042123334 · doi:10.1103/physrevb.61.9895

Diffusion of hydrogen in crystalline silicon

2000· article· en· W2042123334 on OpenAlexaff
Sabrina Bédard, Laurent J. Lewis

Bibliographic record

VenuePhysical review. B, Condensed matter · 2000
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsDiffusionSiliconArrhenius equationEffective diffusion coefficientHydrogenCrystalline siliconMaterials scienceThermodynamicsChemical physicsMolecular dynamicsArrhenius plotChemistryActivation energyPhysical chemistryComputational chemistryPhysics

Abstract

fetched live from OpenAlex

The coefficient of diffusion of hydrogen in crystalline silicon is calculated using tight-binding molecular dynamics. Our results are in good quantitative agreement with an earlier study by Panzarini and Colombo [Phys. Rev. Lett. 73, 1636 (1994)]. However, while our calculations indicate that long jumps dominate over single hops at high temperatures, no abrupt change in the diffusion coefficient can be observed with decreasing temperature. The (classical) Arrhenius diffusion parameters, as a consequence, should extrapolate to low temperatures.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.250
Teacher spread0.242 · 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 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

Citations18
Published2000
Admission routes1
Has abstractyes

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