MétaCan
Menu
Back to cohort
Record W2291723412 · doi:10.1002/cjce.22435

Methanol carboxylation over zirconium dioxide: Effect of catalyst phase composition on its acid‐base spectrum and direction of catalytic transformations

2016· article· en· W2291723412 on OpenAlexvenueno aff
Yuri N. Kochkin, N. V. Vlasenko, V. L. Struzhko, Alexander M. Puziy, P. E. Strizhak

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsnot available
Fundersnot available
KeywordsCatalysisCalcinationZirconium dioxideCarboxylationMethanolChemistryBase (topology)Inorganic chemistryTetragonal crystal systemZirconiumSelectivityAcid–base reactionPhase (matter)BicarbonateChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

The effect of ZrO 2 calcination temperature on its structure and acid‐base characteristics was investigated to elucidate their relation to catalytic behaviour in methanol carboxylation. Varying the calcination temperature causes changes in ZrO 2 phase composition and acid‐base characteristics. The base properties of ZrO 2 play a prominent role in dimethyl carbonate synthesis. Strong base sites (E CO2 > 78 kJ/mol) are needed to activate СО 2 . Tetragonal modification of zirconium dioxide has a higher basicity than the monoclinic. Thus, the greater the contribution of t‐ZrO 2 in the catalyst, the greater its ability to activate СО 2 and therefore result in higher catalytic activity for methanol carboxylation. DMC selectivity was determined by the ratio of catalyst base site to acid site concentration.

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)0.000
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 score0.013
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.225
Teacher spread0.216 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicCarbon dioxide utilization in catalysisFrench-language works237,207