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Record W2009040977 · doi:10.1021/ja0639766

Hydrogen Storage in Chemically Reducible Mesoporous and Microporous Ti Oxides

2006· article· en· W2009040977 on OpenAlexaff
Xin Hu, Boris O. Skadtchenko, Michel L. Trudeau, David M. Antonelli

Bibliographic record

VenueJournal of the American Chemical Society · 2006
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsUniversity of WindsorHydro-Québec
Fundersnot available
KeywordsChemistryHydrogen storageMesoporous materialMicroporous materialAdsorptionChemical engineeringSpecific surface areaOxidation stateReagentBET theoryHydrogenInorganic chemistryToluenePhysical chemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Chemically reducible micro- and mesoporous Ti oxides with controlled pore sizes from 12 to 26 A were synthesized. The hydrogen storage and adsorption capacity at 77 K was tested as a function of surface area, pore size, and reducing agent. Surprisingly, the oxidation state of the surface Ti species had an even greater effect on the storage densities than surface area or pore size. For example, the 12 A material reduced with bis(toluene) Ti possesses a surface area of less than 300 m2/g, but absorbs up to 4.94 wt % and 40.46 kg/m3 of H2 reversibly at 77 K and 100 atm. This volumetric storage capacity is higher than that of AX-21, which has a much higher surface area. The H2 binding enthalpies increased from 4.21 kJ/mol to 8.08 kJ/mol as the surface oxidation state of the Ti decreased. These results suggest that a Kubas-type sigma H2 complex may be involved and that further tuning of the H2 binding enthalpies through use of appropriate organometallic reagents may achieve even higher storage levels at more moderate 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 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 score0.001
Threshold uncertainty score0.002

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)0.0000.000

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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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

Citations113
Published2006
Admission routes1
Has abstractyes

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Same venueJournal of the American Chemical SocietySame topicHydrogen Storage and MaterialsFrench-language works237,207