Reaction and Kinetics in Immobilized Glucose Isomerase of Packed-Bed Reactors Using Akbari-Ganji’s Method
Bibliographic record
Abstract
Nonlinear differential equations often arise in many real-world problems.The complexity of solving nonlinear systems arises from the strong interdependence between the variables of the system and the boundary conditions.An immobilized glucose isomerase-based mathematical model for the enzymatic isomerization process that converts glucose to fructose is presented.The model's kinetic mechanism is stated using the nonlinear reaction-diffusion equation for MichalisMenten kinetics.The general approximate analytical formulas for the glucose molar concentration and flux inside packed-bed reactors are determined by solving the nonlinear equation using Akbari-Ganji's method.The effects of the kinetic parameters and pore-level Thiele modulus on concentration and flux were discussed.Estimating the kinetic parameters from current density is suggested.It has been shown that this method reduces processing time without affecting the quality of the solution.This method works well for many different types of nonlinear systems, making it useful in engineering and other fields of science.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".