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Record W4389444150 · doi:10.1039/d3nr04478e

Not all silicon quantum dots are equal: photostability of silicon quantum dots with and without a thick amorphous shell

2023· article· en· W4389444150 on OpenAlexafffund
I Teng Cheong, LiYifan Yang Szepesvari, Chuyi Ni, Cole Butler, Kevin O’Connor, Riley W. Hooper, A. Meldrum, Jonathan G. C. Veinot

Bibliographic record

VenueNanoscale · 2023
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundAlberta Innovates
KeywordsSiliconMaterials scienceQuantum dotAmorphous solidPhotoluminescenceIrradiationShell (structure)Amorphous siliconInertNanoparticleInert gasNanotechnologyOptoelectronicsChemical engineeringPhotochemistryChemistryCrystalline siliconComposite materialCrystallographyOrganic chemistry

Abstract

fetched live from OpenAlex

Luminescent colloidal silicon quantum dots (SiQDs) are sustainable alternatives to metal-based QDs for various optical applications. While the materials are reliant on their photoluminescence efficiency, the relationship between the structure and photostability of SiQDs is yet to be well studied. An amorphous silicon (a-Si) shell was recently discovered in SiQDs prepared by thermally-processed silicon oxides. As a-Si is known as a source of defects upon UV irradiation, the disordered shell could potentially have an adverse effect on the optical properties of nanoparticles. Herein, the photostability of ∼5 nm diameter SiQDs with an amorphous shell was compared with that of over-etched SiQDs of equivalent dimensions that bore an a-Si shell of negligible thickness. An UV-induced degradation study was conducted by subjecting toluene solutions of SiQDs to 365 nm light-emitting diodes (LEDs) under an inert atmosphere for predetermined times up to 72 hours. The structure, composition, and optical responses of the exposed SiQDs were evaluated.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.267
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 teacher head, not a consensus.

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

Citations12
Published2023
Admission routes2
Has abstractyes

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