Mechanistic insights into the lignin dissolution behavior in amino acid based deep eutectic solvents

Abstract

Deep eutectic solvents (DESs) composed by amino acids (L-arginine, L-proline, L-alanine) as the hydrogen bond acceptors (HBAs) and carboxylic acids (formic acid, acetic acid, lactic acid, levulinic acid) as hydrogen bond donors (HBDs) were prepared and used for the dissolution of dealkaline lignin (DAL). The mechanism of lignin dissolution in DESs was explored at molecular level by combining the analysis of Kamlet-Taft (K-T) solvatochromic parameters, FTIR spectrum and density functional theory (DFT) calculations of DESs. Firstly, it was found that the formation of new hydrogen bonds between lignin and DESs mainly drove the dissolution of lignin, which were accompanied by the erosion of hydrogen bond networks in both lignin and DESs. The nature of hydrogen bond network within DESs was fundamentally determined by the type and number of functional groups in both HBA and HBD, which affected its ability to form hydrogen bond with lignin. One hydroxyl group and carboxyl group in HBDs provided active protons, which facilitated proton-catalyzed cleavage of β-O-4, thus enhancing the dissolution of DESs. The superfluous functional group resulted in more extensive and stronger hydrogen bond network in the DESs, thus decreasing the lignin dissolving ability. Moreover, it was found that lignin solubility had a closed positive correlation with the subtraction value of α and β (net hydrogen donating ability) of DESs. Among all the investigated DESs, L-alanine/formic acid (1:3) with the strong hydrogen-bond donating ability (acidity), weak hydrogen-bond accepting ability (basicity) and small steric-hindrance effect showed the best lignin dissolving ability (23.99 wt%, 60 °C). On top of that, the value of α and β of L-proline/carboxylic acids DESs showed some positive correlation with the global electrostatic potential (ESP) maxima and minima of the corresponding DESs respectively, indicating the analysis of ESP quantitative distributions of DESs could be an effective tool for DESs screening and design for lignin dissolution as well as other applications.