Determination of adsorption and kinetic parameters for methyl oleate (biodiesel) esterification reaction catalyzed by Amberlyst 15 resin
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".