In-silico design of deep eutectic solvents for gas separation and energy related operations

Abstract

In this doctoral thesis, an exhaustive examination of sustainable solvents and advanced materials is conducted using state-of-the-art computational methods. The primary objective is to address environmental concerns related to carbon dioxide by designing materials in-silico. The study employs innovative multiscale computational models to gain fundamental insights into the relationships between structure, composition, property, and performance of the materials. The investigation delves into emerging deep eutectic solvents, composed of natural organic compounds, for designing task-specific solvents. The thesis also explores the potential of these solvents in addressing challenges associated with carbon dioxide emissions, resulting in promising carbon absorption performance. A holistic perspective on the carbon cycle was achieved including experimental investigations on carbon-to-hydrocarbon recombination, contributing valuable insights to green chemistry and sustainable technological advancements. Overall, the findings pave the way for integrating deep eutectic solvents into mainstream industrial processes for a more sustainable future in chemical production.