MétaCan
Menu
Back to cohort
Record W2327829436 · doi:10.1021/jp406619p

Hydrogen Storage Properties of the Destabilized 4NaBH<sub>4</sub>/5Mg<sub>2</sub>NiH<sub>4</sub> Composite System

2013· article· en· W2327829436 on OpenAlexafffund
Greg Afonso, Arman Bonakdarpour, David P. Wilkinson

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2013
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsHydrogen storageDesorptionHydrogenBall millComposite numberMaterials scienceEnthalpyTernary operationAnalytical Chemistry (journal)Chemical engineeringThermodynamicsPhysical chemistryChemistryMetallurgyComposite materialAdsorptionOrganic chemistry

Abstract

fetched live from OpenAlex

A composite mixture of NaBH 4 and Mg 2 NiH 4 (4:5, M/M) was prepared by high-energy ball milling and was investigated for solid-state storage of hydrogen. Addition of Mg 2 NiH 4 to NaBH 4 leads to formation of the stable ternary boride phase MgNi 2.5 B 2 and lowers the enthalpy of hydrogen desorption for NaBH 4 from 110 to 76 ± 5 kJ mol –1 H 2 . As a consequence of this addition, the onset temperature of hydrogen desorption decreases from about 500 °C in NaBH 4 to 360 °C in the NaBH 4 /Mg 2 NiH 4 composite mixture. Furthermore, the system shows reversibility and is able to store 2.5 wt % hydrogen for a number of cycles. The impact of the ball milling time, the hydrogen desorption back-pressure, and cycling on the hydrogen desorption/absorption properties and crystallographic phases is discussed in detail.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.197
Teacher spread0.188 · 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

Citations30
Published2013
Admission routes2
Has abstractyes

Explore more

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