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Record W2078233717 · doi:10.1021/ie034123e

Simulation Studies of Catalytic Distillation for Removal of Water from Ethanol Using a Rate-Based Kinetic Model

2003· article· en· W2078233717 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2003
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsReboilerChemistryDistillationCatalysisReactive distillationAlcoholIsobutyleneEthanolProcess engineeringChemical engineeringChromatographyOrganic chemistryPolymerEngineering

Abstract

fetched live from OpenAlex

A new approach based on catalytic distillation (CD) technology was proposed to remove water from ethanol, by reaction with isobutylene to form tert -butyl alcohol (TBA) and ethyl tert -butyl ether. Reaction within the CD column was calculated using a rate-based kinetic model with the simulation package Aspen Plus. A sensitivity analysis of the effect of the key design and operating factors on the column performance was performed. The most important factors affecting water conversion, TBA selectivity, and reboiler duty are the operating pressure and reaction temperature, distillate-to-feed ratio, amount of catalyst, and feed and reaction stage location. Optimization of operating variables found that the CD process offers potential advantages of reduced energy consumption and reduced capital cost over the traditional approaches for the removal of water from ethanol.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.213
GPT teacher head0.376
Teacher spread0.163 · 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