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Record W1990026139 · doi:10.1007/s12274-011-0177-y

Surface dislocation nucleation mediated deformation and ultrahigh strength in sub-10-nm gold nanowires

2011· article· en· W1990026139 on OpenAlexaff
Yang Lü, Jun Song, Jun Lou

Bibliographic record

VenueNano Research · 2011
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsMcGill University
FundersSandia National LaboratoriesBasic Energy SciencesLos Alamos National LaboratoryNational Nuclear Security AdministrationBrown UniversityWelch Foundation
KeywordsNucleationMaterials scienceHigh-resolution transmission electron microscopyNanowireDislocationTransmission electron microscopyUltimate tensile strengthDeformation (meteorology)Nanoscopic scaleComposite materialCrystallographyNanotechnologyChemistry

Abstract

fetched live from OpenAlex

The plastic deformation and the ultrahigh strength of metals at the nanoscale have been predicted to be controlled by surface dislocation nucleation. In situ quantitative tensile tests on individual 〈111〉 single crystalline ultrathin gold nanowires have been performed and significant load drops observed in stress-strain curves suggest the occurrence of such dislocation nucleation. High-resolution transmission electron microscopy (HRTEM) imaging and molecular dynamics simulations demonstrated that plastic deformation was indeed initiated and dominated by surface dislocation nucleation, mediating ultrahigh yield and fracture strength in sub-10-nm gold nanowires.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.069
GPT teacher head0.299
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations93
Published2011
Admission routes1
Has abstractyes

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