Computational Advances in Ionic Liquid Applications for Green Chemistry: A Critical Review of Lignin Processing and Machine Learning Approaches.

The valorization and dissolution of lignin using ionic liquids (ILs) is critical for developing sustainable biorefineries and a circular bioeconomy. This review aims to critically assess the current state of computational and machine learning methods for understanding and optimizing IL-based lignin dissolution and valorization processes reported since 2022. The paper examines various computational approaches, from quantum chemistry to machine learning, highlighting their strengths, limitations, and recent advances in predicting and optimizing lignin-IL interactions.

Molecular and Spectroscopic Insights into a Metal Salt-Based Deep Eutectic Solvent: A Combined Quantum Theory of Atoms in Molecules, Noncovalent Interaction, and Density Functional Theory Study.

Deep eutectic solvents (DESs) based on metal halide salts are highly catalytic, low toxic, reusable, cost-effective, and have higher thermal stability than their analogue ionic liquids (ILs). In this work, we have reported the formation mechanism of metal salt-based DESs at the molecular level along with their charge-transfer analysis and thermodynamics associated with their formation using density functional theory. The DES systems analyzed in the present work were choline chloride and tin(II)chloride (DES1) and choline chloride and zinc(II)chloride (DES2), both in a molar ratio of 1:2, respectively.