MétaCan
Menu
Back to cohort
Record W4313573630 · doi:10.1002/cjce.24827

Feasibility of reactive chromatography for the production of 2‐phenyl ethyl acetate

2023· article· en· W4313573630 on OpenAlexvenueno aff
Kapil Jayant, Sanjay M. Mahajani

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein purification and stability
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryReactive distillationAdsorptionEthyl acetateCatalysisAcetic acidKineticsChromatographyWork (physics)Batch reactorParticle sizeLangmuirChemical engineeringOrganic chemistryThermodynamicsPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Reactive chromatography is a novel process intensification option when the progress of a reaction is hampered by reversibility (e.g., esterification and acetalization). In this work, we study its feasibility for the production of 2‐phenyl ethyl acetate (PEAct) by esterification of 2‐phenyl ethyl alcohol with acetic acid using Amberlyst‐15 as a catalyst/adsorbent. The reaction kinetics is investigated in a laboratory batch reactor by varying various parameters such as agitation speed, temperature, feed molar ratio, catalyst loading, and particle size, and a Langmuir Hinshelwood kinetic model is proposed. The reaction is then studied in a fixed‐bed chromatographic reactor (FBCR). Non‐reactive binary adsorption experiments are performed in the same setup to estimate the corresponding parameters of the Langmuir adsorption isotherm. The experimentally observed reactive breakthrough curves in FBCR reveal that RC is a promising process option for the production of PEAct. Furthermore, it is shown that the FBCR model, which uses kinetics and isotherms developed in this work, explains the reactive breakthrough curves and the regeneration performance reasonably well. The work reported here forms a base for the design of a simulated moving‐bed reactor that may be used for large‐scale production.

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)0.001
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 score0.003
Threshold uncertainty score0.140

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.019
GPT teacher head0.244
Teacher spread0.225 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicProtein purification and stabilityFrench-language works237,207