PhD Proposal: Samiha Sharlin

Water pollution impacts ecology and human health, motivating the need for engineered technologies for remediation. Adsorption (the partitioning of molecules between fluid and solid phases) is fundamental in environmental chemistry. In aqueous systems, adsorption plays a role in the distribution of water and solutes between surface water and soil, adsorption onto microplastics, partitioning in groundwater, and removal of heavy metals. Zeolites, in particular, are important adsorbent materials in water and wastewater remediation and have been used for purification from ammonia, heavy metals, radioactive, toxic, and organic substances, as well as for water softening and seawater desalination. Understanding the fundamental thermodynamics, kinetics, and structure of mixtures adsorption is challenging. Experimentally, even for binary adsorption from liquid solutions, quantifying both solute and solvent co-adsorption is difficult because the mass and volume balances are underdetermined, requiring assumptions about the nature of co-adsorption. Quantifying adsorption of all species in multicomponent mixtures is even more challenging (unless one doesn’t quantify adsorption of the solvent), but such mixtures are ubiquitous in the environment.

Molecular simulations complement and provide invaluable access to thermodynamic phenomena occurring at the pore sites and thus have significantly contributed to the synthesis and applications of zeolite. Additionally, adsorption systems with competition between complex adsorbates onto complex adsorbents can be better understood and more clearly evaluated through computer simulations. For example, molecular dynamics has been used to study 1,4-dioxane transport and adsorption into Ti-silicalite in the presence of organic contaminants while Monte Carlo has been used to investigate the structure-function relationship of metal-organic frameworks (MOFs) for adsorption of perfluorooctanoic acid (PFOA) from water. Modeling adsorption in aqueous environment systems is challenging due to the presence of numerous unknown substances that are present in trace amounts and often interact with each other. From a numerical perspective, these substances have concentrations that are too low (ppb or ppt) for standard molecular simulations to represent. Additionally, there is also a need for transferrable force fields and efficient simulation techniques to model the chemisorption interactions. This project aims to address the challenges associated with low-concentration and chemisorption sampling techniques in Monte Carlo simulations. The project also explores automated equation discovery tools for force field development that can incorporate scientific context as natural language input. Generating accessible, amenable, and interpretable molecular modeling software can facilitate cheaper, more accurate simulations that match experiments.

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