MétaCan
Menu
Back to cohort
Record W2431204623 · doi:10.1002/cjce.22436

Determination of adsorption and kinetic parameters for methyl oleate (biodiesel) esterification reaction catalyzed by Amberlyst 15 resin

2016· article· en· W2431204623 on OpenAlexaffvenue
Nillohit Mitra Ray, Ajay K. Ray

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsAdsorptionChemistryElutionCatalysisMethanolMass transferKinetic energyDispersion (optics)ChromatographyBiodieselIon-exchange resinOleic acidThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

In this work, adsorption equilibrium constants, dispersion coefficients, and kinetic parameters were determined for the reversible esterification reaction of oleic acid with methanol, producing methyl oleate (biodiesel) and water. The reaction was carried out at room temperature in the presence of Amberlyst 15 resin, which acts both as an adsorbent and catalyst in an HPLC column, which served as a packed bed reactor. A quasi‐homogenous kinetic model coupled with a linear adsorption isotherm was explored. The elution profiles of the reactant and products were experimentally monitored and then compared with a mathematical model. The adsorption and kinetic parameters were determined by minimizing the error between the experimentally obtained elution curves and the model‐predicted values using the genetic algorithm optimization technique. Further experiments were conducted under varying conditions to establish the validity of the obtained model parameters. It was also found that the system is not affected by internal and external mass transfer resistances. The mathematical model predicted the experimental outcome quite accurately.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.257

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 head0.014
GPT teacher head0.201
Teacher spread0.188 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicBiodiesel Production and ApplicationsFrench-language works237,207