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Record W4288077309 · doi:10.1002/cjce.24576

Catalytic oxidation of glycerol in alkaline medium – Influence of mass transport limitations

2022· article· en· W4288077309 on OpenAlexvenueno aff
Ashutosh Namdeo, Jainesh H. Jhaveri, Sanjay M. Mahajani, Akkihebbal K. Suresh

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsnot available
Fundersnot available
KeywordsCatalysisChemistryGlycerolMass transferSelectivityRedoxReaction rateReaction mechanismMetalReaction intermediateMass transportKinetic controlInorganic chemistryChemical engineeringOrganic chemistryChromatographyBiochemical engineering

Abstract

fetched live from OpenAlex

Abstract Glycerol upgradation via oxidation is characterized by a complex reaction network, further complicated by the heterogeneous (gas/liquid/solid) nature of the reaction. Thus, rates and selectivities could be significantly modified by transport limitations, especially in industrial reactors. In this work, we have studied the reaction on supported Pd and Au catalysts under alkaline conditions, both in the absence and presence of transport resistances, both external and internal. Reaction pathways proposed on the basis of data under kinetic control have been used to rationalize the findings. Interestingly and counterintuitively, the selectivity to C 3 compounds is better under the influence of mass transfer. This behaviour is because of the nature of the reaction, which involves solution‐mediated reactions in addition to the metal‐catalyzed reactions on the catalyst surface. These findings have important implications for the scale up of this reaction and process design methodology.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.319

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 head0.007
GPT teacher head0.169
Teacher spread0.162 · 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
Published2022
Admission routes1
Has abstractyes

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