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Record W2072433653 · doi:10.1021/jp075294q

Computational Studies of the Adsorption and Diffusion of Hydrogen on Fe−Co Alloy Surfaces

2008· article· en· W2072433653 on OpenAlexaff
John M. H. Lo, Tom Ziegler

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2008
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAdsorptionDiffusion barrierDensity functional theoryActivation energyDiffusionBond cleavageHydrogenAlloyChemistryCleavage (geology)Surface diffusionMoleculeCrystallographyActivation barrierMaterials sciencePhysical chemistryChemical physicsComputational chemistryCatalysisThermodynamicsNanotechnologyMetallurgy

Abstract

fetched live from OpenAlex

Studies of the dissociative adsorption of H 2 and surface diffusion of H atoms on FeCo(110) using periodic density functional theory and a slab model are reported. It is found that the bcc Fe−Co alloy in B2 phase favors the exposure of (110) plane under cleavage. The H 2 molecule is adsorbed on FeCo(110) via the dissociative mechanism where H−H bond scission over an OT-Co site kinetically is the most feasible, possessing an energy barrier of merely 1.5 kcal/mol, much lower than that for the corresponding H 2 adsorption on Fe(100) and Fe(110). Upon adsorption, H atoms prefer the TF-Co and TF-Fe sites so that the highest degree of coordination with the surface atoms can be achieved. The calculations reveal that H atoms may diffuse easily over the FeCo(110) surface; the rate-determining step is the migration across a SB site which requires that an activation barrier of about 4.2 kcal/mol be overcome. It is noticed that the diffusive motion TF-Fe → TF-Fe is dominant at room temperature, while at higher temperatures the diffusion TF-Fe → TF-Co prevails.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
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 head0.026
GPT teacher head0.280
Teacher spread0.254 · 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 designSimulation or modeling
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

Citations10
Published2008
Admission routes1
Has abstractyes

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Same venueThe Journal of Physical Chemistry CSame topicHydrogen Storage and MaterialsFrench-language works237,207