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Record W2330524954 · doi:10.1021/ie303197a

Determination and Modeling of Vapor–Liquid Equilibria for the Sulfuric Acid + Water + Butyl Acetate + Ethanol System

2013· article· en· W2330524954 on OpenAlexaff
Geng Li, Zhibao Li, Edouard Asselin

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2013
Typearticle
Languageen
FieldChemical Engineering
TopicChemical and Physical Properties in Aqueous Solutions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSulfuric acidChemistryAzeotropeDistillationEthanolExtractive distillationAzeotropic distillationTernary numeral systemSolventBoilingInorganic chemistryChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

A novel azeotropic distillation for sulfuric acid recovery, which uses organic solvents as entrainers, is proposed. This new distillation process may provide significant energy savings. Vapor–liquid equilibria (VLE) data were determined by the quasi-static ebulliometric method for the following systems at (30, 60, and 90) kPa: (1) sulfuric acid + water + ethanol; (2) sulfuric acid + water + butyl acetate; and (3) sulfuric acid + water + butyl acetate + ethanol. Through the use of the OLI software, a chemical model was established via regressing the experimental data to obtain the mixed solvent electrolyte (MSE) model parameters. The average absolute deviations of boiling points for all systems are only 1.34 K. The new model with newly obtained parameters was successfully applied to predict the VLE for the sulfuric acid + water + butyl acetate ternary system at constant pressure, providing important VLE information for the recovery of spent sulfuric acid by this new azeotropic distillation technology.

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 score0.455
Threshold uncertainty score0.565

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 integrity0.0000.001
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 head0.100
GPT teacher head0.304
Teacher spread0.204 · 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

Citations18
Published2013
Admission routes1
Has abstractyes

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