Enzyme-Catalyzed Synthesis and Kinetics of Ultrasonic-Assisted Methanolysis of Waste Choice White Grease for Fatty Acid Methyl Ester Production
Bibliographic record
Abstract
In this study, the effects of ultrasonic parameters (amplitude, cycle, and pulse) and major reaction factors (molar ratio and enzyme concentration) on the reaction kinetics of fatty acid methyl ester (FAME) generation from waste choice white grease (CWG) biocatalyzed by immobilized lipase [ Candida antarctica lipase B (CALB)] were investigated. A yield of 98.2% was attained in 20 min at an ultrasonic amplitude (40%) at 5 kHz, fat/methanol molar ratio (1:4), and catalyst level of 6% (wt/wt of fat). The effect of ultrasonic mixing on the reaction kinetic of enzymatic transesterification was investigated using a Ping Pong Bi Bi kinetic model approach. Kinetic constants of the transesterification reaction were determined at different ultrasonic amplitudes (30, 35, 40, 45, and 50%) and enzyme concentrations (4, 6, and 8 wt % of fat) at a constant molar ratio (fat/methanol) of 1:6 and ultrasonic cycle of 5 kHz. The fitted curves of the kinetic mechanism showed a sigmoidal curve as a result of mass-transfer limitations, which controlled the process at the beginning of the reaction. The kinetic model results also revealed interesting features of ultrasound-assisted enzyme-catalyzed transesterification. The kinetic model approach described the whole methanolysis process accurately. At the ultrasonic amplitude of 40%, the reaction activities within the system seemed to have steadied after 20 min, which means that the reaction could proceed with or without ultrasonic mixing.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".