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Record W2422565755 · doi:10.1002/cnma.201600151

Silicon Nanocrystals: It's Simply a Matter of Size

2016· article· en· W2422565755 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemNanoMat · 2016
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNanocrystalNanotechnologySiliconMaterials scienceOptoelectronics

Abstract

fetched live from OpenAlex

Abstract Composed of one of the most earth abundant, low cost and least toxic elements, silicon nanocrystals exhibit quantum and spatial confinement effects when their size is diminished to that of the exciton, around 5 nm. With the recent discovery of various means for synthesizing and separating silicon nanocrystals into narrow size distribution mono‐dispersions, it became possible for the first time to implement more deeply analytical studies of their size‐dependent chemical, physical and biological properties than was possible with poly‐dispersions. In this article we take a look at some recent studies of mono‐dispersions of silicon nanocrystals where it is apparent that size really matters. With this newfound knowledge we imagine the new directions that the field may take in the future. The topics covered include how silicon nanocrystal size is manifest on their (i) surface structure and reactivity, (ii) optical and electronic properties, (iii) chemical and photochemical stability, and (iv) biochemical and cytotoxicity behavior. The article concludes with a vision of what the future might hold for this important class of nanocrystals.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.009
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

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)0.0100.001

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 head0.009
GPT teacher head0.232
Teacher spread0.222 · 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