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Publication Date

2019-04-30

Availability

UM campus only

Embargo Period

2021-04-29

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PHD)

Department

Chemistry (Arts and Sciences)

Date of Defense

2019-03-29

First Committee Member

Orlando Acevedo

Second Committee Member

Rajeev Prabhakar

Third Committee Member

Roger Leblanc

Fourth Committee Member

Odelia Schwartz

Abstract

Due to the negative environmental impact of damaging organic solvents and the high-cost of chemical waste disposal, the search for alternative, renewable solvents is a top priority in the chemical industry. Part of a worldwide emphasis on improving sustainability, the push has led to increasing interest in a set of environmentally-friendly solvents: ionic liquids (ILs) and deep eutectic solvents (DES). These solvents, primarily composed of ions, provide numerous advantages from both chemical and environmental perspectives. Despite the excitement surrounding these solvents, a fundamental understanding of how they operate is still lacking. The goal of this thesis is to develop and apply computer models to both elucidate how these solvents function and to design the next generation of cost-effective “green” solvents. Studies performed within include (1) development of new computer models, i.e., force fields, that accurately predict experimental IL and DES data, (2) insight into an important Diels-Alder chemical reaction enhanced by ILs, and (3) development of new artificial intelligence tools (i.e., machine learning) that could potentially shift the paradigm by reducing the cost of the simulations with increased accuracy.

Keywords

Force Field; Molecular Dynamics; Machine Learning; Ionic Liquids; Deep Eutectic Solvents

Available for download on Thursday, April 29, 2021

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