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Point defects in models of amorphous silicon and their role in structural relaxation

2001· preprint· en· W1562127043 on OpenAlexaff
Cristiano L. Dias, Laurent J. Lewis, S. Roorda

Bibliographic record

VenuearXiv (Cornell University) · 2001
Typepreprint
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAmorphous solidCrystallographic defectMaterials scienceAnnealing (glass)Relaxation (psychology)SiliconAmorphous siliconValence (chemistry)Molecular dynamicsCondensed matter physicsChemical physicsMolecular physicsCrystallographyCrystalline siliconChemistryPhysicsComputational chemistry

Abstract

fetched live from OpenAlex

We have used tight-binding molecular-dynamics simulations to investigate the role of point defects (vacancies and interstitials) on structural relaxation in amorphous silicon. Our calculations give unambiguous evidence that point defects can be defined in the amorphous solid, showing up as anomalies in the valence-charge/Voronoi-volume relation. The changes in the radial distribution functions that take place during annealing are shown to be in close agreement with recent, highly-accurate x-ray diffraction measurements. Our calculations provide strong evidence that structural relaxation in a-Si proceeds by the mutual annihilation of vacancies and interstitials, i.e., local structural changes rather than an overall relaxation of the network.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.149
Teacher spread0.123 · 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.

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
Published2001
Admission routes1
Has abstractyes

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