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Record W2104521531 · doi:10.1002/cjce.21805

From molecules to processes: Molecular simulations applied to the design of simulated moving bed for ethane/ethylene separation

2013· article· en· W2104521531 on OpenAlexvenueno aff
Miguel Angelo Granato, Vanessa F. D. Martins, João C. Santos, Miguel Jorge, Alı́rio E. Rodrigues

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsSimulated moving bedPropaneButaneAdsorptionEthyleneZeoliteWork (physics)Molecular dynamicsAir separationSeparation (statistics)Materials scienceChemistryChemical engineeringChromatographyThermodynamicsOrganic chemistryComputer scienceComputational chemistryCatalysisEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract This paper presents results of a modelling study on the separation of ethane/ethylene mixture by selective adsorption on zeolite 13X in a simulated moving bed (SMB) unit. Propane and n ‐butane are evaluated as desorbent candidates. The study encompasses molecular simulation calculations for determination of adsorption parameters, whose results will then be used in a mathematical model for evaluating the performance of an SMB unit. This work is entirely done in silico , by using available force field parameters for the molecular simulations part and reliable mathematical models for the SMB part. Experimental data are solely used for comparison with the molecular simulation results, which are subsequently expanded to calculate adsorption properties for separating the mixtures, without further experimental work. The separation regions of an SMB unit operating with zeolite 13X for ethane/ethylene separation, using propane and n ‐butane as desorbents, were obtained by simulation at 110 kPa and at four different temperatures: 298, 323, 348 and 373 K. For each desorbent, an operating point was selected, and the size of the required unit was presented for the complete separation of the two components of the mixture.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.220
Teacher spread0.208 · 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

Citations20
Published2013
Admission routes1
Has abstractyes

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