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Record W2891808721 · doi:10.1088/1361-651x/aae2c8

Multiscale approach for determining hydrogen diffusivity in zirconium

2018· article· en· W2891808721 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueModelling and Simulation in Materials Science and Engineering · 2018
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsSimon Fraser UniversityCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceZirconiumThermal diffusivityHydrogenThermodynamicsMetallurgy

Abstract

fetched live from OpenAlex

Abstract The current research presents an approach which is used to determine the diffusivity of hydrogen in the hexagonal close packed (hcp) zirconium crystal, using a combination of first principles calculations and kinetic Monte Carlo (KMC) simulations. Rate constants found through the energy landscapes of hydrogen motion between different interstitial sites in the zirconium lattice were used in KMC to determine the values of bulk diffusivity. We simulated a stress-free environment to eliminate the effect of stress. It is hypothesized that stress could act as a driving forces for diffusion. We found that hydrogen diffusivity in hcp Zr is closely isotropic, with a slightly higher diffusivity in the axis direction. The individual diffusion jumps were closely investigated to identify the reasons for the isotropic nature of the diffusivity in the anisotropic hcp Zr lattice. We also use this study to validate the modeling approach followed to extend it to other diffusion studies of similar nature, which comprises of clearly understood diffusion steps.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.296
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

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

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 head0.031
GPT teacher head0.244
Teacher spread0.213 · 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