Feasibility of reactive chromatography for the production of 2‐phenyl ethyl acetate
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".