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Record W2158377860 · doi:10.1139/v00-200

Hydrogenation of carbon dioxide catalyzed by ruthenium trimethylphosphine complexes Effect of gas pressure and additives on rate in the liquid phase

2001· article· en· W2158377860 on OpenAlexvenueno aff
Colin A. Thomas, R. Jason Bonilla, Yong Huang, Philip G. Jessop

Bibliographic record

VenueCanadian Journal of Chemistry · 2001
Typearticle
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsnot available
FundersPacific Northwest National LaboratoryOffice of ScienceU.S. Department of Energy
KeywordsChemistryFormic acidCatalysisMethanolSupercritical fluidCarbon dioxideRutheniumInorganic chemistryInert gasReaction rateSupercritical carbon dioxideCarbon monoxideOrganic chemistry

Abstract

fetched live from OpenAlex

Kinetic and mechanistic studies of CO2 hydrogenation were performed in liquid triethylamine and at subcritical CO2 pressures to avoid complications from phase behaviour that are observed under supercritical conditions. Kinetic measurements of the hydrogenation of CO2 to formic acid, catalyzed by RuCl(O2CMe)(PMe3)4, support a CO2 insertion mechanism. The reaction is first-order in both H2 and CO2 under most conditions. The rate is strongly dependent on the choice of additive, with methanol giving the greatest rates. Because only trace amounts of methanol are needed, the effect of the additive is believed to involve direct interactions with the catalyst rather than changes in the physical properties of the reaction medium. The optimized rates exceed 3500 h–1. Addition of an inert gas affects the rate of the reaction, probably via the phenomenon of gas expansion of the liquid phase.Key words: carbon dioxide, homogeneous catalysis, hydrogenation, formic acid, expanded liquids.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.006
GPT teacher head0.226
Teacher spread0.220 · 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

Citations50
Published2001
Admission routes1
Has abstractyes

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Same venueCanadian Journal of ChemistrySame topicCarbon dioxide utilization in catalysisFrench-language works237,207