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Record W100154478 · doi:10.1520/stp17973s

Internal Friction and Young's Modulus Measurements in Zr-2.5Nb Alloy Doped with Hydrogen

2009· book-chapter· en· W100154478 on OpenAlexaff
I.G. Ritchie, Z-L. Pan

Bibliographic record

VenueASTM International eBooks · 2009
Typebook-chapter
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsAlloyMaterials scienceDopingModulusInternal frictionHydrogenComposite materialMetallurgyChemistryOptoelectronicsOrganic chemistry

Abstract

fetched live from OpenAlex

The presence of hydrides is an important factor in assessing the potential for delayed hydride cracking in Zr-2.5Nb alloys, and consequently, the terminal solid solubility (TSS) of hydrogen in the material is an importantparameter. In pure zirconium doped with hydrogen, the TSS is marked by a dissolution peak of internal friction on heating and a truncated precipitation peak associated with hydride nucleation on cooling. These phenomena occur only at low frequencies and are accompanied in torsion pendulum studies by autotwisting of the sample (or zero-point drift) that stops abruptly at the TSS. Neither the dissolution/ precipitation peaks nor the autotwisting phenomena are observed in Zr-2.5Nb. However, the TSS is also marked by an abrupt change in the slope of Young's modulus as a function of temperature. This phenomenon is observed regardless of the frequency (in the range 1 Hz to 120 kHz) and in both pure zirconium and Zr-2.5Nb alloys. The reasons for the absence of the dissolution/precipitation peak in Zr- 2.5Nb alloys are discussed and the use of Young's modulus changes to investigate the TSS of hydrogen and the hysteresis between heat-up and cool-down TSS curves is demonstrated.

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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.220
Teacher spread0.193 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

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Same venueASTM International eBooksSame topicNuclear Materials and PropertiesFrench-language works237,207