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Record W2061455692 · doi:10.1121/1.3372629

Rhenium diboride’s monocrystal elastic constants, 308 to 5 K

2010· article· en· W2061455692 on OpenAlexaff
Yoko Suzuki, Jonathan B. Levine, A. Migliori, Jim D. Garrett, Richard B. Kaner, Victor Fanelli, Jonathan Betts

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2010
Typearticle
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsMcMaster UniversityBrockhouse Institute for Materials Research
FundersU.S. Department of EnergyNational Nuclear Security AdministrationNational Science Foundation
KeywordsMaterials scienceResonant ultrasound spectroscopyDiamondIsotropyDiffractionCondensed matter physicsTexture (cosmology)Hexagonal crystal systemSymmetry (geometry)Elastic modulusCrystallographyRheniumComposite materialOpticsGeometryPhysicsChemistryMetallurgyMathematics

Abstract

fetched live from OpenAlex

The five independent moduli required to construct the complete monocrystal elastic modulus tensor of the hexagonal-symmetry superhard compound ReB(2) were measured from 308 to 5 K using resonant ultrasound spectroscopy on a special-texture polycrystal. This is possible because, confirmed by X-ray diffraction, the specimen measured was composed of grains with hexagonal axes parallel so that its polycrystal elastic response is identical to a monocrystal and because hexagonal-symmetry solids are elastically isotropic in the plane perpendicular to the hexagonal axis. Along the hexagonal (c) axis, C(33) (0) = 1021 GPa, nearly equal to C(11) of diamond, and consistent with the superhard properties. However, in the (softer) isotropic plane, C(11) (0) = 671 GPa, much lower than diamond. The changes of C(ij) with temperature are very small and smooth. The Debye temperature was computed to be 738 K, and using a high-temperature approximation, the Grüneisen parameter is γ = 1.7.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.010
GPT teacher head0.266
Teacher spread0.255 · 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 teacher head, not a consensus.

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

Citations15
Published2010
Admission routes1
Has abstractyes

Explore more

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