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Record W2135532730 · doi:10.1039/c3cp52154k

New perspectives on potential hydrogen storage materials using high pressure

2013· article· en· W2135532730 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

VenuePhysical Chemistry Chemical Physics · 2013
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsWestern University
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of Canada
KeywordsHydrogen storageHydrideHydrogenHydrogen fuelEnergy storageCompressed hydrogenHydrogen economyRenewable energyProcess engineeringNanotechnologyMaterials scienceChemistryEngineeringThermodynamicsPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

In addressing the global demand for clean and renewable energy, hydrogen stands out as the most suitable candidate for many fuel applications that require practical and efficient storage of hydrogen. Supplementary to the traditional hydrogen storage methods and materials, the high-pressure technique has emerged as a novel and unique approach to developing new potential hydrogen storage materials. Static compression of materials may result in significant changes in the structures, properties and performance that are important for hydrogen storage applications, and often lead to the formation of unprecedented phases or complexes that have profound implications for hydrogen storage. In this perspective article, 22 types of representative potential hydrogen storage materials that belong to four major classes--simple hydride, complex hydride, chemical hydride and hydrogen containing materials--were reviewed. In particular, their structures, stabilities, and pressure-induced transformations, which were reported in recent experimental works together with supporting theoretical studies, were provided. The important contextual aspects pertinent to hydrogen storage associated with novel structures and transitions were discussed. Finally, the summary of the recent advances reviewed and the insight into the future research in this direction were given.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.233
Teacher spread0.224 · 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