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Record W2075594035 · doi:10.1016/j.egypro.2012.09.074

Fundamental Aspects of Mechanical Dehydrogenation of Li- Based Complex Hydride Nanocomposites and Their Self-Discharge at Low Temperatures

2012· article· en· W2075594035 on OpenAlexaff
Robert A. Varin, Roozbeh Parviz, L. Zbroniec, Zbigniew S. Wronski

Bibliographic record

VenueEnergy Procedia · 2012
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsNatural Resources CanadaUniversity of Waterloo
Fundersnot available
KeywordsDehydrogenationHydrideBall millComposite numberHydrogenMaterials scienceHydrogen storageNanocompositeChemical engineeringDecompositionMagnesium hydrideCatalysisChemistryMetallurgyComposite materialAlloyOrganic chemistry

Abstract

fetched live from OpenAlex

Large quantities of hydrogen (H2) are released at ambient temperatures as a result of mechanical dehydrogenation during ball milling of complex hydride composites such as (LiAlH4+5 wt.% nanometric Fe), (nLiAlH4+LiNH2; n=1, 3, 11.5, 30), (nLiAlH4+MnCl2; n=1, 3, 8, 13, 30, 63) and (LiNH2+nMgH2; n=0.5-2.0). For both the (nLiAlH4+LiNH2) and (LiAlH4+5 wt.% nanometric Fe) composites the second constituent strongly destabilizes LiAlH4 during milling by different mechanisms. For (nLiAlH4+MnCl2) two concurrent mechanisms are observed: (i) a reaction between both constituents during ball milling leading to the formation of LiCl, amorphous Mn and H2, and (ii) a catalytic-like induced decomposition of LiAlH4 into Li3AlH6, Al and H2. For the (LiNH2+nMgH2; n=0.5-2.0) composite system, the pathway of hydride reactions depends on the molar ratio n and total milling energy consumed during ball milling. Some composite systems slowly self-discharge H2 at room temperature (RT), 40 and 80 °C, after ball milling with an additive. Technical parameters such as specific energy-usable are estimated for LiAlH4-based complex hydride composite systems and are compared with both US DOE hydrogen powered car targets and Li-ion batteries benchmarks.

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 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 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 score0.005
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.220
Teacher spread0.209 · 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 teacher head, 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

Citations5
Published2012
Admission routes1
Has abstractyes

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