MétaCan
Menu
Back to cohort
Record W3092132890 · doi:10.1139/cjc-2020-0348

Synthesis of amino-phenolate manganese complexes and their catalytic activity in carbon dioxide activation and oxidation reactions

2020· article· en· W3092132890 on OpenAlexaffvenue
Ali I. Elkurtehi, Francesca M. Kerton

Bibliographic record

VenueCanadian Journal of Chemistry · 2020
Typearticle
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsChemistryCatalysisCyclohexene oxideReactivity (psychology)Propylene carbonateStyrene oxidePropylene oxideManganeseBenzaldehydeInorganic chemistryYield (engineering)CyclohexeneAldehydeLigand (biochemistry)Carbon dioxideSolventStyreneOrganic chemistryElectrolyteCopolymerEthylene oxide

Abstract

fetched live from OpenAlex

Two manganese(III) compounds were studied as catalysts for the reaction of carbon dioxide with propylene oxide, styrene oxide, and cyclohexene oxide, and formed cyclic carbonate products selectively under solvent free conditions in the presence of an ionic co-catalyst such as TBAB or PPNCl. Variable temperature kinetic studies allowed the activation energy for propylene carbonate formation to be determined (64 kJ mol −1 ). The catalysts showed good stability in these reactions and overall turnover numbers (TON) of up to 6000 were observed. The complexes showed low activity for the aerobic oxidation of 4-methyoxybenzylalcohol to the corresponding aldehyde, achieving up to 40% conversion in 72 h. However, near quantitative conversion of 1,2-diphenyl-2-methoxyethanol to provide up to 90% yield of benzaldehyde could be achieved over the course of 5 days. Both complexes showed similar reactivity in the two catalytic processes, and this is likely due to the weakly coordinating nature of the pendant donor within the tetradentate ligand.

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 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 score0.006
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.202
Teacher spread0.188 · 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 teacher head, 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

Citations2
Published2020
Admission routes2
Has abstractyes

Explore more

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