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Record W2057331852 · doi:10.1021/cm402853k

Observation of TiH<sub>5</sub> and TiH<sub>7</sub> in Bulk-Phase TiH<sub>3</sub> Gels for Kubas-Type Hydrogen Storage

2013· article· en· W2057331852 on OpenAlexaff
Tuan K.A. Hoang, Leah Morris, Daniel Reed, David Book, Michel L. Trudeau, David M. Antonelli

Bibliographic record

VenueChemistry of Materials · 2013
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsHydro-QuébecUniversity of Windsor
FundersEngineering and Physical Sciences Research Council
KeywordsHydrogen storageHydrideHomolepticHydrogenMaterials scienceBinding energyMicroporous materialChemisorptionRaman spectroscopyCrystallographyMetalChemical engineeringPhysical chemistryChemical physicsInorganic chemistryChemistryAdsorptionOrganic chemistryMetallurgyAtomic physics

Abstract

fetched live from OpenAlex

The lack of an efficient hydrogen storage material has so far hindered the implementation of hydrogen as an energy vector, that is, a substance that allows the transfer through space and time of a certain quantity of energy from its original source. This work presents porous Ti(III) hydride gels as a promising new hydrogen storage material, exploiting the first example of a solid-state homoleptic metal hydride that binds further H 2 ligands using the Kubas interaction. These materials use bridging hydride ligands as an ultralightweight structural feature to support a microporous network of Ti binding sites for molecular H 2 chemisorption. High-pressure Raman spectroscopy confirmed the first evidence of TiH 5 and TiH 7 species, in some ways analogous to hypervalent MH 5 and MH 7 (M = Si, Ge, Sn) species. The material with the highest capacity has an excess reversible storage of 3.49 wt % at 140 bar and 298 K without saturation, corresponding to a volumetric density of 44.3 kg/m 3, comparable to the DOE 2017 volumetric system goal of 40 kgH 2 /m 3 . However, extrapolations show that the phase-pure material is capable of binding at least 6 wt % hydrogen reversibly at room temperature.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.249
Teacher spread0.229 · 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.

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

Citations18
Published2013
Admission routes1
Has abstractyes

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