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Record W2066959901 · doi:10.1021/ja204865t

Preparation of Monodisperse Silicon Nanocrystals Using Density Gradient Ultracentrifugation

2011· article· en· W2066959901 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

VenueJournal of the American Chemical Society · 2011
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDispersityChemistryTrichlorosilaneAlkylTransmission electron microscopyChemical engineeringSiliconNanocrystalAnalytical Chemistry (journal)NanotechnologyPolymer chemistryChromatographyOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

We report the preparation of monodisperse silicon nanocrystals (ncSi) by size-separation of polydisperse alkyl-capped ncSi using organic density gradient ultracentrifugation. The ncSi were synthesized by thermal processing of trichlorosilane-derived sol-gel glasses followed by HF etching and surface passivation with alkyl chains and were subsequently fractionated by size using a self-generating density gradient of 40 wt % 2,4,6-tribromotoluene in chlorobenzene. The isolated monodisperse fractions were characterized by photoluminescence spectroscopy and high-angle annular dark-field scanning transmission electron microscopy and determined to have polydispersity index values between 1.04 and 1.06. The ability to isolate monodisperse ncSi will allow for the quantification of the size-dependent structural, optical, electrical, and biological properties of silicon, which will undoubtedly prove useful for tailoring property-specific optoelectronic and biomedical devices.

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 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 score0.252

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)0.0000.000

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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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