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Record W4408602417 · doi:10.1117/12.3044478

Laser coupling in indirect bandgap Ge nanocrystals

2025· article· en· W4408602417 on OpenAlexaff
Amr S. Helmy, Manuchehr Ebrahimi, Nazir P. Kherani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceOptoelectronicsNanocrystalBand gapCoupling (piping)LaserWide-bandgap semiconductorNanotechnologyEngineering physicsOpticsComposite materialPhysics

Abstract

fetched live from OpenAlex

In this study, we present the first observation of laser cooling in an indirect bandgap semiconductor. Utilizing precise Raman measurements, we detected dominant anti-Stokes photoluminescence in germanium nanocrystals with average particle sizes ranging from 16 nm to 30 nm. These measurements were consistently reproducible in two distinct experimental setups: germanium nanocrystals in isopropyl alcohol (IPA) solution and dispersed germanium nanocrystal powder. From these observations, we inferred lattice temperatures as low as approximately 50K. This cooling effect can be attributed to several converging factors: ultra-high purity of the germanium nanocrystals, generation of a high-density electron-hole plasma, inherent degeneracy of longitudinal and transverse optical phonons in non-polar indirect bandgap semiconductors, and corresponding confinement effects. Our findings underscore the critical role of laser power density in solid-state cooling, identifying a threshold level that induces dominant anti-Stokes emission.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.010
GPT teacher head0.251
Teacher spread0.241 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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