Kinetic modelling of enzymatic biodiesel production from castor oil: Temperature dependence of the Ping Pong parameters
Bibliographic record
Abstract
Biodiesel is considered an alternative replacement for petroleum diesel, and enzymatic reaction is one method for biodiesel production. Understanding the kinetics of this reaction is important to achieve higher production rates. The kinetics of transesterification of castor oil using Novozym 435 was investigated in this study. The genetic algorithm was employed for estimation of kinetic parameters including Vmax, KmTG, and KmA in the Ping Pong kinetic model at different temperatures. In most enzymatic reactions that follow the Ping Pong mechanism, inhibition by alcohol has been taken into consideration. Here, we examined a competitive inhibition mechanism and found no inhibition effect at high alcohol‐to‐oil molar ratios of 12.6, 15.6, and 18.9 mol/mol. Arrhenius expressions were used to fit the kinetic parameters for reaction temperatures of 30–50 °C. An acceptable agreement with experimental data at 45 °C was observed when biodiesel yields were predicted using the temperature‐dependent parameters, thus validating the proposed model.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".