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Ultimate Strength of Nanotwinned Face-Centered Cubic Metals

2020· article· en· W3113865732 on OpenAlexaff
Jianwei Xiao, Chuang Deng

Bibliographic record

VenuePhysical Review Letters · 2020
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsNanocrystalline materialMaterials scienceGrain boundaryCubic crystal systemCondensed matter physicsWork (physics)Strengthening mechanisms of materialsGrain sizeMetallurgyNanotechnologyThermodynamicsPhysicsMicrostructure

Abstract

fetched live from OpenAlex

In this work, we present a theoretical model to predict the ultimate strength of nanotwinned face-centered cubic (fcc) metals based on the activation energy for phase transformation (i.e., between the matrix and the twinned counterpart) mediated by the migration of {112}-type step on Σ3(111) twin boundaries. By integrating the Hall-Petch strengthening and grain boundary sliding into this model, we can accurately predict the strength of four representative nanotwinned (nt) fcc metals (nt-Cu, nt-Ag, nt-Ni, and nt-Al) within a broad range of grain sizes including the so-called nanocrystalline-nanotwinned regime. This framework is built on material parameters which directly connect the theoretical calculations with experimental measurements and reveals new insights into the design of ultrastrong metals and alloys.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.282
Teacher spread0.245 · 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

Citations17
Published2020
Admission routes1
Has abstractyes

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