MétaCan
Menu
Back to cohort
Record W3192215011 · doi:10.1149/2162-8777/ac1c59

Germanium Nanocrystal Properties from Photoluminescence

2021· article· en· W3192215011 on OpenAlexaff
N. L. Rowell, D. J. Lockwood

Bibliographic record

VenueECS Journal of Solid State Science and Technology · 2021
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsNanocrystalGermaniumMaterials sciencePhotoluminescenceMolecular beam epitaxyQuantum dotAlloyOptoelectronicsLattice (music)Tensile strainEpitaxyNanotechnologyUltimate tensile strengthSiliconComposite material

Abstract

fetched live from OpenAlex

Morphological information has been obtained using the strong near-infrared photoluminescence emitted by germanium (Ge) nanocrystals (NCs) coherently imbedded in SiGe alloy layers, grown by molecular beam epitaxy on Si substrates. The emission spectra are analyzed for the effects of strain, carrier confinement, and disorder over a wide range of Ge concentrations in the surrounding SiGe medium. This analysis provided significant insight into the properties of the Ge nanocrystals, including their size and shape. We also discuss the mechanisms leading to the high quantum efficiency observed for emission from the Ge nanocrystals at low temperatures. We indicate how direct gap behavior might be achieved for Ge NCs lattice matched within dilute Ge 1-y Sn y alloys, where tensile strain would be present in the NCs in all three directions.

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 score0.004

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 head0.009
GPT teacher head0.232
Teacher spread0.223 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueECS Journal of Solid State Science and TechnologySame topicSilicon Nanostructures and PhotoluminescenceFrench-language works237,207