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Record W1523373673 · doi:10.1063/1.4927509

Size-dependent deformation mechanisms in hollow silicon nanoparticles

2015· article· en· W1523373673 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

VenueAIP Advances · 2015
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceNanoparticleBrittlenessComposite materialSlip (aerodynamics)SiliconBucklingNucleationDeformation (meteorology)RADIUSNanotechnologyMetallurgyChemistry

Abstract

fetched live from OpenAlex

Even inherently brittle hollow silicon nanoparticles (NPs) can withstand larger strain to failure than solid NPs. However, the influence of wall thickness on the mechanical behavior of hollow Si NPs is not fully understood. Using molecular dynamics simulations, we investigate the compressive behavior of hollow Si NPs. Three distinct failure mechanisms of hollow NPs are uncovered, and their strength and deformability are analyzed quantitatively. For extra-thick-walled NPs, dislocations will nucleate below the contact area and cut through the particles till failure. For mid-thick-walled NPs, however, dislocations will emit from the inner surface and slip towards the outer surface. For thin-walled NPs, elastic buckling is the cause of failure. Compared to solid NPs, hollow NPs with wall thickness being around half of its outer radius can achieve significant improvement in both strength and deformability.

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 score0.014
Threshold uncertainty score0.397

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 communication0.0000.001
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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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