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Record W2043373963 · doi:10.1021/ic700806b

Highly Efficient Colloidal Cobalt- and Rhodium-Catalyzed Hydrolysis of H<sub>3</sub>N·BH<sub>3</sub> in Air

2007· article· en· W2043373963 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.

Bibliographic record

VenueInorganic Chemistry · 2007
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChemistryCatalysisRhodiumHydrolysisAqueous solutionCobaltColloidCyclooctadieneMetalInorganic chemistryHydrogenIonic bondingOrganic chemistryIon

Abstract

fetched live from OpenAlex

The compound H3N.BH3 (1) is currently attracting considerable attention as a potential hydrogen storage material. Group 9 catalysts which rapidly and conveniently hydrolyze aqueous 1 in air are described. When treated with 1 mol % [{Rh(mu-Cl)(1,5-cod)}2] (cod=cyclooctadiene) in air, aqueous 1 undergoes rapid hydrolysis to afford the ionic species [NH4][BO2] in approximately 40 s. Higher catalyst loadings (3 mol %) result in a reduction in reaction time to 10 s. Quantification of the hydrogen evolved revealed that, on average, 2.8 of a maximum possible 3.0 equivalents (93%) were generated during the course of the reaction. Rh(0) species (e.g., Rh black, Rh stabilized on alumina, aqueous Rh colloids) were also found to be active hydrolysis catalysts, and evidence for a heterogeneous mechanism is provided. Significantly, although Ir(0) colloids are less active, aqueous Co(0) colloids are also effective catalysts for this process. This result is particularly important as Co, a first-row metal, is considerably more economical than the precious metal catalysts typically employed.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.207
Teacher spread0.202 · 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