Abstract
A kinetic model could provide a dynamical description of mechanism in that it is required for analysis, design, optimization and control. Temperature and pH could affect the cellulose activity. In this study, we have introduced the kinetic model, which includes temperature and pH effects, to describe dynamic behaviors of the enzymatic hydrolysis of cellulose to glucose. A commercial enzyme was applied to the hydrolysis process. Various batch time-series observations were collected and used to estimate the model parameters of the kinetic model. Hybrid differential evolution with a geometric mean mutation was applied to determine optimal estimates, and then such estimates were used as the initial starting for a gradient-based method to obtain the refined solution. The approach is capable of predicting the dynamic behaviors of the cellulose hydrolysis process as observed extra experimental validations. Furthermore, the time-average sensitivities were applied to evaluate accuracy and robustness of the mathematical model.
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