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Record W2970627901 · doi:10.3390/ma12172778

Mechanochemistry of Metal Hydrides: Recent Advances

2019· review· en· W2970627901 on OpenAlexaff
Jacques Huot, Fermín Cuevas, Stefano Deledda, Kaveh Edalati, Yaroslav Filinchuk, Thierry Grosdidier, Bjørn C. Hauback, Michael Heere, Torben R. Jensen, M. Latroche, Sabrina Sartori

Bibliographic record

VenueMaterials · 2019
Typereview
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNordForskAgence Nationale de la Recherche
KeywordsMechanochemistryBall millMaterials scienceMetallurgyHydrogenMetalSevere plastic deformationGrindingStructural materialMechanical engineeringNanotechnologyEngineeringChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

This paper is a collection of selected contributions of the 1st International Workshop on Mechanochemistry of Metal Hydrides that was held in Oslo in May 2018. In this paper, the recent developments in the use of mechanochemistry to synthesize and modify metal hydrides are reviewed. A special emphasis is made on new techniques beside the traditional way of ball milling. High energy milling, ball milling under hydrogen reactive gas, cryomilling and severe plastic deformation techniques such as High-Pressure Torsion (HPT), Surface Mechanical Attrition Treatment (SMAT) and cold rolling are discussed. The new characterization method of in-situ X-ray diffraction during milling is described.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.057
GPT teacher head0.339
Teacher spread0.282 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations110
Published2019
Admission routes1
Has abstractyes

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