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Record W4399382600 · doi:10.1080/01614940.2024.2354699

Unimolecular and bimolecular reactions of organic intermediates on metal oxide catalysts: an update

2024· article· en· W4399382600 on OpenAlexaff
Victor Fung, Michael J. Janik, Steven Crossley, Ya-Huei Cathy Chin, Aditya Savara

Bibliographic record

VenueCatalysis Reviews · 2024
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsUniversity of Toronto
FundersBasic Energy SciencesDirectorate for GeosciencesU.S. Department of EnergyOffice of ScienceNational Science Foundation
KeywordsCatalysisChemistryMetalOxidePhotochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The surface chemistry of metal oxides and their catalytic roles in activating and transforming oxygenate and hydrocarbon feedstocks is rich. This review provides an update on mechanisms of such reactions, as well as modern promising concepts for selective catalytic conversions on metal oxide catalysts, including those occurring in molecularly confining reaction environments. Case examples built upon electronic structure modeling of transition states are emphasized, as well as on contemporary ideas to enable low free energies of activation. The chemistry covered is broad, and includes examples of Lewis acid–base chemistry, Brønsted acid–base chemistry, and oxygen vacancy-based redox chemistry. The reactions covered include C-H activation of alkanes, C–C coupling of aldehydes, C–C coupling of carboxylic acids (ketonization), dehydration of alcohols over confined sites, C–C bond formation between aldehydes over confined sites, and C–C bond formation between carboxylic acids over confined sites. For each reaction type, molecular-level knowledge of elementary reaction steps is critically reviewed.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.004
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.004

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 head0.014
GPT teacher head0.268
Teacher spread0.254 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2024
Admission routes1
Has abstractyes

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