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Record W2088281183 · doi:10.1063/1.4907866

Strength and texture of Pt compressed to 63 GPa

2015· article· en· W2088281183 on OpenAlexaff
Susannah M. Dorfman, S. R. Shieh, T. S. Duffy

Bibliographic record

VenueJournal of Applied Physics · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsWestern University
FundersBasic Energy SciencesU.S. Department of EnergyBrookhaven National LaboratoryOffice of ScienceNational Science Foundation
KeywordsMaterials scienceTexture (cosmology)CrystalliteCompressive strengthCubic crystal systemDiamondYield (engineering)Grain sizeComposite materialCompression (physics)DiffractionParticle sizeClose-packing of equal spheresCrystallographyMetallurgyOpticsChemistry

Abstract

fetched live from OpenAlex

Angle- and energy-dispersive X-ray diffraction experiments in a radial geometry were performed in the diamond anvil cell on polycrystalline platinum samples at pressures up to 63 GPa. Observed yield strength and texture depend on grain size. For samples with 70–300-nm particle size, the yield strength is 5–6 GPa at ∼60 GPa. Coarse-grained (∼2-μm particles) Pt has a much lower yield strength of 1–1.5 GPa at ∼60 GPa. Face-centered cubic metals Pt and Au have lower strength to shear modulus ratio than body-centered cubic or hexagonal close-packed metals. While a 300-nm particle sample exhibits the 〈110〉 texture expected of face-centered-cubic metals under compression, smaller and larger particles show a weak mixed 〈110〉 and 〈100〉 texture under compression. Differences in texture development may also occur due to deviations from uniaxial stress under compression in the diamond anvil cell.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.215
Teacher spread0.199 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

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