(227c) Predicting Kamlet–Taft Parameters Using Quantum Chemical Descriptors | AIChE

(227c) Predicting Kamlet–Taft Parameters Using Quantum Chemical Descriptors


Ramakrishnan, P. - Presenter, joint Bioenergy Institute

Predicting Kamlet–Taft Parameters using Quantum Chemical Descriptors


Ionic liquids (ILs) have attracted increasing interests as promising solvents for effective biomass fractionation. Both the cations and anions of ILs play an important role in the dissolution of lignocellulosic biomass. By selecting different cation and anion combinations, ILs can be fine-tuned to accommodate a wide variety of solvent properties and applicaitons: thermoelectric cells, fuel cells, solar cells, CO2 solubility, lubricants, and pharmaceutical products. Kamlet and Taft (K-T) devised three general polarity parameters (dipolarity/polarizability (π*), hydrogen bond donor acidity (α), and hydrogen bond basicity (β)) and the K-T parameters had been successfully applied to characterize the ILs’ solvents properties and efficiency for dissolving biomass. However, limited knowledge is available for computationally predicting the solvent property of ILs and correlating with cellulose solvation and lignin depolymerization during IL pretreatment of lignocellulosic biomass. In this work, Density functional theory (DFT) based quantum chemical reactivity descriptors were used to develop structure-property-(re)activity of α, β, and π* solvent polarity parameters of ILs. We examined the relationship between the predicted K-T values and experimentally tested KT parameters on a series of imidazolium based and amino acid based ILs . Furthermore, we established correlations between K-T parameter and cellulose digestibility and lignin removal of pretreated biomass during IL pretreatment. For the first time, we demonstrated that DFT based descriptor is a very useful tool for predicting not only the chemical structure-reactivity of the selected ILs and but also the nature of interactions between IL and lignin or cellulose. We also conducted fully-atomistic molecular dynamics (MD) simulations on cellulose solvation and lignin depolymerization in selected ILs. The model developed in this study can guide the targeted design of ILs on solubilizing lignin/cellulose and advance the development of IL pretreatment technologies.