Towards a Predictive Control for Ionic Liquid enabled Lignocellulosic Biomass Conversion:  Computational Perspective
Monday, April 28, 2014
Exhibit/Poster Hall, lower level (Hilton Clearwater Beach)
Ramakrishnan Parthasarathi1, Jian Shi2, Ning Sun3, Blake A. Simmons4 and Seema Singh1, (1)Deconstruction Division, Joint BioEnergy Institute, Emeryville, CA, (2)Deconstruction Division, Joint BioEnergy Institute/Sandia National Laboratories, Emeryville, CA, (3)Deconstruction Division, Joint BioEnergy Institute, Physical Biosciences Division, Lawrence Berkeley National Laboratory, Emeryville, CA, (4)Vice-President, Deconstruction Division, Joint BioEnergy Institute, Emeryville, CA
A deeper mechanistic understanding of lignocellulosic biomass dissolution in ionic liquids (ILs) is desired for the development of efficient pretreatment approaches to enhance the efficiency of biofuel production. As a part of a broader effort to improve IL process selectivity, biocompatibility, and economics, we are using computational approaches integrated with experiments to gain a fundamental understanding of the chemistry of biomass deconstruction at molecular level. We use multiscale computational approaches to analyze; (A) the interactions of ions and ion pairs (i.e. ILs) with model lignin compounds, (B) the interactions of ILs with crystalline cellulose, and (C) to develop predictive models of IL reactivity. In this investigation, quantum chemical calculations were carried out to quantify the interactions of biocompatible ILs derived from natural resources such as cholinium and lysinate and compared with combination of 1-ethyl-3-methylimidazolium and acetate ions. Furthermore, the dissolution mechanism of cellulose in different [C2mim][OAc]:water ratios was deduced from all atom molecular dynamics simulations, including explicit IL:water mixtures. Finally, we examined the relationship between the experimental and predicted Kamlet and Taft (K-T) solvatochromic parameters of a series of ILs and compared with their pretreatment efficiency. The models developed in these studies will guide the targeted design of ILs on solubilizing lignocellulosic biomass and will advance the development of IL pretreatment technologies.