Population balance approach for the modelling of enzymatic hydrolysis of cellulose
Bibliographic record
Abstract
Abstract In this numerical work, a population balance‐based model is proposed in order to describe the cellulose particles size evolution during the enzymatic hydrolysis. Two kinds of actions are considered: endoglucanase activity that cleaves randomly β‐1,4‐glycosidic linkages of cellulose, and exoglucanase activity which reduces the particles size with chain‐end‐cleaving producing cellobiose (a dimer of two glucoses linked by a β‐1,4‐glycosidic bond). A discretization method with a fixed pivot technique is used for the endoglucanase action and a moving pivot technique for exoglucanase attack. The numerical resolution is then validated by analytical solutions available in literature. Afterwards, the combination of the two actions is investigated for different enzyme ratios in order to reproduce the endo‐exo synergism numerically. Since the biodegradation of cellulose releases D‐glucose as a final product due to β‐glucosidase which hydrolyzes cellobiose into two molecules of glucose, numerical kinetic model predicting the fractional conversion of cellulose is derived from the population balance developed model. The enzymes activity is strongly affected by the accumulation of the end‐products (cellobiose and glucose) during the hydrolysis, the inhibition effect is thereby incorporated in the model. The numerical model prediction is compared to experimental data in the case of combined activity and shows a promising approach for the modelling of cellulose‐cellulase systems.
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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 | 0.000 |
| 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".