MétaCan
Menu
Back to cohort
Record W4250955882 · doi:10.1002/9781119506003.ch3

Optical Properties of Disordered Condensed Matter

2019· other· en· W4250955882 on OpenAlexaff
K. Shimakawa, Jai Singh, Stephen K. O’Leary

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMaterials Science
TopicPhase-change materials and chalcogenides
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsChalcogenideAmorphous semiconductorsAmorphous solidCondensed matter physicsSemiconductorBand gapPhoton energyMaterials scienceDipoleAbsorption (acoustics)Attenuation coefficientPhotonPhysicsOpticsChemistryQuantum mechanicsOptoelectronics

Abstract

fetched live from OpenAlex

This chapter reviews the understanding of the fundamental optical properties in some disordered semiconductors. It presents two approaches that are used for calculating the absorption coefficient in amorphous semiconductors. In the first approach, one assumes that the transition matrix element is independent of the photon energy. In the second approach, contrary to the first one, using the constant dipole approximation, the transition matrix element is found to be photon-energy dependent. Applying the first approach, one obtains the well-known Tauc's relation for the absorption coefficient of amorphous semiconductors. It is shown that, through the first approach, both the fractal and effective medium theories are useful in explaining the optical properties of disordered forms of condensed matter. The chapter also discusses the effect of the compositional variation on the optical gap of amorphous chalcogenide alloys. The bandgap varies with the composition and often exhibits extrema at certain stoichiometric compositions.

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: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.028
GPT teacher head0.231
Teacher spread0.203 · 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
GenreOther

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

Citations3
Published2019
Admission routes1
Has abstractyes

Explore more

Same topicPhase-change materials and chalcogenidesFrench-language works237,207