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Record W2615143027 · doi:10.1002/cjce.22896

Synthesis of diethyl carbonate from ethanol through different routes: A thermodynamic and comparative analysis

2017· article· en· W2615143027 on OpenAlexvenueno aff
Kartikeya Shukla, Vimal Chandra Srivastava

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsnot available
Fundersnot available
KeywordsUNIFACGibbs free energyEquilibrium constantThermodynamicsChemistryEnthalpyDiethyl carbonateChemical equilibriumCarbonateStandard enthalpy of formationHeat capacityThermodynamic equilibriumStandard molar entropyPhysical chemistryActivity coefficientEthylene carbonateOrganic chemistryElectrolyte

Abstract

fetched live from OpenAlex

In this study, thermodynamic analysis of various possible synthesis routes of diethyl carbonates (DEC), a benign organic carbonate, was carried out and a comparative analysis was performed. Chemical equilibrium constants at standard conditions were calculated using Gibbs free energy of the system. The Benson group contribution method was used to estimate standard heat of formation and standard entropy change of some raw materials/components like dimethyl carbonate. Variation of heat capacity (C p ) with temperature was estimated for different components from the Rozicka‐Domalski model. Variation of chemical equilibrium constants with temperature and pressure was studied for various routes. Synthesis of DEC from ethylene carbonate (EC) was also found to be better considering equilibrium constants at room temperature. The CO 2 route was found to be the most unfavourable route for DEC synthesis due to stability of CO 2 molecules. Moreover, DEC synthesis through the urea route was found to be best at high temperatures since the equilibrium constants were found to increase exponentially. Experiments were conducted for DEC synthesis using the EC route at two temperatures. Activity coefficients were calculated using the UNIFAC model. Experimentally and theoretically determined chemical equilibrium constant values were found to be similar. PRO/II was also used to minimize Gibbs free energy of the system and estimate the equilibrium constants and the results were comparable with those obtained by the equilibrium constant method and the trend was found to be the same for both the methods.

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)0.000
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 score0.314
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.236
Teacher spread0.215 · 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

Citations13
Published2017
Admission routes1
Has abstractyes

Explore more

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