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Record W1721540193 · doi:10.3166/acsm.34.345-363

Reactivity of solids from the black hole of pre-electronic literature to success in heterogeneous catalysis: the remote control concept

2009· article· en· W1721540193 on OpenAlexvenueno aff
Elhassan Zantalla, Yоussef Ait Yassine, Abdellah Aguizir, N. Selhaoui, L. Bouirden

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2009
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsReactivity (psychology)CatalysisControl (management)Computer scienceChemistryMedicineArtificial intelligenceOrganic chemistry

Abstract

fetched live from OpenAlex

This focussed review is an update concerning highly active surface species moving between different solids (the 'spillover' phenomenon). Initially, this specifically concerned the reactivity of solids (e.g. nucleus formation in the reduction of oxides to metals). More surprising and more important have been consequences concerning heterogeneous catalysis. Spillover hydrogen, H-so, and spillover oxygen, O-so, create active sites during catalytic processes. This leads to modifications of activity and selectivity in the treatment of petroleum fractions and in the selective oxidation of hydrocarbons in petrochemistry (by H-so, or O-so, respectively). For example, in hydrodesulfurization, H-so from a physically separated catalyst bed increases the activity of MoS2. O-so leads to a reconstruction of the surface of MoO3 and higher selectivity in oxidation. This opens completely new perspectives for the fundamental understanding of catalysis.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.256
Teacher spread0.244 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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