Mathematical Modelling of Alkaline and Ionic Liquid Pretreated Coconut Husk Enzymatic Hydrolysis - Akbarningrum Fatmawati; Ari Anggoro; Kamila Adila Muslim; Arief Widjaja; Tantular Nurtono; Hanny Frans Sangian (Masyarakat Katalis Indonesia - Indonesian Catalyst Society (MKICS), 2021)
The problem of crude oil reserve shortage and air quality decline currently have led researches on renewable fuel such as bioethanol and biohydrogen. The attempt to provide such biofuel involves the utilization of enormously available wasted materials, lignocellulose. Coconut husk is one of such materials available in Indonesia. The previous work had reported the quantity of total reducing sugar produced after the enzymatic hydrolysis of pretreated coconut husk. The pretreatment methods used were dilute sodium hydroxide solution (1 and 4% w/v), 1,3-methylmethylimidazolium dimethyl phosphate ionic liquid and the combination of both methods. This work focused on constructing the mathematical model which describes the kinetic of those enzymatic hydrolysis reactions. Mathematical model expressions help describing as well as predicting the process behavior, which is commonly needed in the process design and control. The development of mathematical model in this work was done based on the total reducing sugar concentration resulted in batch hydrolysis reaction. The kinetic parameters including initial available substrate (S0), maximum reaction rate (rmax), and half-maximum rate constant (KM). According to the values of half-maximum rate constant (KM), the enzymatic hydrolysis performance of coconut husk treated using ionic liquid is better than that treated using dilute alkaline solution as the former had shown lower KM value and hence higher enzyme affinity to the substrate. The best hydrolysis result was performed using combination of 1% dilute sodium hydroxide solution and ionic liquid with kinetic model parameter of 0.5524 g/L.h of rmax, 0.0409 g/L of KM, and 4.1919 g/L of S0. Copyright © 2021 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).