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Record W2155884024 · doi:10.1115/1.2125988

An Energy Balance Criterion for Nanoindentation-Induced Single and Multiple Dislocation Events

2005· article· en· W2155884024 on OpenAlexaff
W. W. Gerberich, William Mook, M.D. Chambers, Megan J. Cordill, Christopher R. Perrey, C. Barry Carter, Ronald E. Miller, W.A. Curtin, Rajesh Mukherjee, Steven L. Girshick

Bibliographic record

VenueJournal of Applied Mechanics · 2005
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsCarleton University
FundersNational Science Foundation
KeywordsNanoindenterNanoindentationMaterials scienceDislocationNucleationDrop (telecommunication)InstabilityCondensed matter physicsComposite materialDisplacement (psychology)MechanicsSurface energyCrystallographyPhysicsThermodynamicsChemistry

Abstract

fetched live from OpenAlex

Small volume deformation can produce two types of plastic instability events. The first involves dislocation nucleation as a dislocation by dislocation event and occurs in nanoparticles or bulk single crystals deformed by atomic force microscopy or small nanoindenter forces. For the second instability event, this involves larger scale nanocontacts into single crystals or their films wherein multiple dislocations cooperate to form a large displacement excursion or load drop. With dislocation work, surface work, and stored elastic energy, one can account for the energy expended in both single and multiple dislocation events. This leads to an energy balance criterion which can model both the displacement excursion and load drop in either constant load or fixed displacement experiments. Nanoindentation of Fe-3% Si (100) crystals with various oxide film thicknesses supports the proposed approach.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.222
Teacher spread0.209 · 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 designSimulation or modeling
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

Citations32
Published2005
Admission routes1
Has abstractyes

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