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Record W4221138391 · doi:10.48550/arxiv.2203.15528

Absorption spectrum of doped highly mismatched alloys

2022· preprint· en· W4221138391 on OpenAlexaff
Hassan Allami, Jacob J. Krich

Bibliographic record

VenuearXiv (Cornell University) · 2022
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicSurface and Thin Film Phenomena
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsElectronegativityAbsorption edgeSemiconductorAbsorption (acoustics)DopingAbsorption spectroscopyMaterials scienceEnhanced Data Rates for GSM EvolutionCondensed matter physicsSpectral lineAlloyConduction bandChemistryBand gapPhysicsOptoelectronicsOpticsElectronQuantum mechanicsTelecommunications

Abstract

fetched live from OpenAlex

Highly mismatched alloys (HMA's) are a class of semiconductor alloys with large electronegativity differences between the alloying elements. We predict the absorption spectrum due to transitions between the split bands of a doped highly mismatched alloy with a conduction band anticrossing. We analyze the joint densities of states for both direct and indirect transitions between the split bands. The resulting spectrum has features that reveal the unusual state distribution that is characteristic of HMAs, hence providing valuable insight into their electronic structure. In particular, we predict a peak near the absorption edge, which arises due to the suppression of direct transitions at large momenta. We present analytic forms for the near-absorption-edge and large-energy spectra, showing that they are qualitatively different from those in standard parabolic semiconductors. In particular, as a result of suppressed direct transitions, indirect transitions dominate the spectrum away from the edge of absorption.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 head0.042
GPT teacher head0.182
Teacher spread0.140 · 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 designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

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