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Record W2324586646 · doi:10.1021/ja404585p

A Highly Active Phosphine–Borane Organocatalyst for the Reduction of CO<sub>2</sub> to Methanol Using Hydroboranes

2013· article· en· W2324586646 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

VenueJournal of the American Chemical Society · 2013
Typearticle
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsChemistryBoranePhosphineMethanolReagentHydrolysisTurnover numberCatalysisOrganic chemistryCatecholOrganocatalysisNonaneMedicinal chemistryEnantioselective synthesis

Abstract

fetched live from OpenAlex

In this work, we report that organocatalyst 1-Bcat-2-PPh2-C6H4 ((1); cat = catechol) acts as an ambiphilic metal-free system for the reduction of carbon dioxide in presence of hydroboranes (HBR2 = HBcat (catecholborane), HBpin (pinacolborane), 9-BBN (9-borabicyclo[3.3.1]nonane), BH3·SMe2 and BH3·THF) to generate CH3OBR2 or (CH3OBO)3, products that can be readily hydrolyzed to methanol. The yields can be as high as 99% with exclusive formation of CH3OBR2 or (CH3OBO)3 with TON (turnover numbers) and TOF (turnover frequencies) reaching >2950 and 853 h(-1), respectively. Furthermore, the catalyst exhibits "living" behavior: once the first loading is consumed, it resumes its activity on adding another loading of reagents.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.009
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
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