Population balance approach for the modelling of enzymatic hydrolysis of cellulose. (17th December 2014)

• Record Type: Journal Article
• Authors: Lebaz, Noureddine; Cockx, Arnaud; Spérandio, Mathieu; Morchain, Jérôme
• Is Part Of: Canadian journal of chemical engineering. Volume 93:Number 2(2015)
• Page Start: 276
• Page End: 284
• Publication Date: 2014-12-17
• Subjects: Chemical engineering -- Periodicals; Technology -- Periodicals; 660.05
• DOI: 10.1002/cjce.22088
• Languages: English
• ISSNs: 0008-4034

Abstract

<abstract abstract-type="main" xml:lang="en"> <title>Abstract</title> <sec id="cjce22088-sec-0001" sec-type="section"> <p>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.</p> </sec> </abstract>