Kinetics and Gibbs Function Studies on Lipase-Catalyzed Production of Non-Phthalate Plasticizer
Bibliographic record
Abstract
Petroleum based phthalate plasticizers encounter enormous claims to prohibit their production due to their harmful health impacts when they are mixed with plastics. That is why efforts are being done to find safer natural alternatives. We have investigated the reaction kinetics of the esterification epoxidation of oleic acid and 2-ethylhexanol in the presence of hydrogen peroxide catalyzed using Candida antarctica lipase (Novozym 435, Novozymes, Kobenhavn, Denmark). The product of this reaction is epoxidized 2-ethylhexyl oleate, a non-phthalate green plasticizer. The kinetic model for this reaction follows a multi-substrate PingPong Bi-Bi mechanism with competitive inhibition by the alcohol. The reaction’s kinetic parameters were found to be 0.76 M, 0.37 M, 0.08 M, and 37.20 mM/min for Michalis-Menten constant for oleic acid (Kmo), Michalis-Menten constant for alcohol (Kma), alcohol inhibition constant (Kia), and maximum reaction velocity (Vmax), respectively. Then the Gibbs function analysis of the transition state based on the Arrhenius and Eyring equations was carried out. The internal diffusional limitations were found to be negligible as the effectiveness factor took the value of almost unity. While the external mass transfer resistance had no effect on the reaction due to operating at relatively high agitation speed and high temperature. This investigation confirms that this reaction was only kinetically controlled.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".