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Record W2786010589 · doi:10.1021/acs.jpclett.7b03288

Scalable Super-Resolution Synthesis of Core-Vest Composites Assisted by Surface Plasmons

2018· article· en· W2786010589 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2018
Typearticle
Languageen
FieldEngineering
TopicNonlinear Optical Materials Studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaW. Garfield Weston FoundationUniversity of TorontoOntario Research Foundation
KeywordsCore (optical fiber)VESTMaterials scienceComposite materialResolution (logic)ScalabilitySurface plasmonPlasmonOptoelectronicsComputer science

Abstract

fetched live from OpenAlex

The behavior of composite nanostructures depends on both size and elemental composition. Accordingly, concurrent control of size, shape, and composition of nanoparticles is key to tuning their functionality. In typical core-shell nanoparticles, the high degree of symmetry during shell formation results in fully encapsulated cores with severed access to the surroundings. We commingle light parameters (wavelength, intensity, and pulse duration) with the physical properties of nanoparticles (size, shape, and composition) to form hitherto unrealized core-vest composite nanostructures (CVNs). Unlike typical core-shells, the plasmonic core of the resulting CVNs selectively maintains physical access to its surrounding. Tunable variations in local temperature profiles ≳50 °C are plasmonically induced over starburst-shaped nanoparticles as small as 50-100 nm. These temperature variations result in CVNs where the shell coverage mirrors the temperature variations. The precision thus offered individually tailors access pathways of the core and the shell.

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 score0.006
Threshold uncertainty score0.404

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 head0.010
GPT teacher head0.215
Teacher spread0.206 · 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