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Record W3185373354 · doi:10.1002/cjce.24261

Kinetic study on hydrolysis of isoamyl <scp>DL</scp> ‐lactate catalyzed by <scp>NKC</scp> ‐9

2021· article· en· W3185373354 on OpenAlexvenueno aff
Jumei Xu, Ying Wang, Shating Li, Zuoxiang Zeng, Weilan Xue, Shan Jiang

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryHydrolysisCatalysisUNIFACEnthalpyEthyl lactateActivation energyChromatographyOrganic chemistryThermodynamicsAqueous solutionActivity coefficient

Abstract

fetched live from OpenAlex

Abstract The kinetics for hydrolysis of isoamyl DL‐lactate over cation‐exchange resin NKC‐9 was investigated in this paper, which was the prerequisite for a proper design of reactive distillation processes. The effects of mass transfer resistance, temperature, catalyst dosage, and the molar ratio of water to isoamyl DL‐lactate on conversion of isoamyl DL‐lactate were evaluated. The pseudo‐homogeneous (PH), Eley‐Rideal (ER), and Langmuir‐Hinshelwood (LH) models were then utilized to correlate the data obtained from experiments. Activities were used in the kinetics instead of the mole fractions because the reactants and products were not ideal. The activity coefficients were estimated by UNIFAC. It was demonstrated that the PH model was the best one to describe the hydrolysis of isoamyl DL‐lactate. The standard enthalpy was 5.46 kJ · mol −1 and the activation energy was 59.71 kJ · mol −1 . Finally, the thermal stability and reusability of NKC‐9 were also tested.

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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.184
Teacher spread0.178 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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Same venueThe Canadian Journal of Chemical EngineeringSame topicProcess Optimization and IntegrationFrench-language works237,207