(6cw) Computational Modeling of Chemical Interactions at Interfaces for Environmental Applications

Chemical reactions at interfaces are important in both natural environments and environmental applications. For example, crystal growth and dissolution reactions at mineral/water interfaces have been applied in environmental remediation, material synthesis, and carbon sequestration. Another good example is use of nanoparticles to remove contaminants, where nanoparticle surface chemistry can be modified to target chemicals. Experimental methods are limited by temporal and spatial resolution, resulting in ambiguous data interpretation and a lack of fundamental understanding of mechanisms underlying these reactions. These knowledge gaps can be addressed with computational chemistry tools. Atomistic simulations can provide molecular scale insights into the reactions at interfaces and guide theoretical models for predicting reaction thermodynamics and kinetics. In my research, I propose to use state-of-the-art simulations to gain molecular insights into chemical interactions at solid-liquid interfaces. Building on my previous experience, I intend to pursue three research thrusts that investigate crystal growth via different pathways at the mineral-water interface and the computational design of micellar-enhanced ultrafiltration (MEUF) techniques.

The topic of thrust 1 is atomistic understanding of the growth mechanism of metal oxides. A molecular-level understanding of metal oxide growth mechanisms can help solve diverse environmental problems including aquifer chemistry, removal of heavy metals, treatment of acid mine drainage, and treatment of nuclear waste. Aluminum hydroxides, the major components of the aluminum ore bauxite, will be chosen as a model system for this study. By using rare-event sampling techniques and reactive force fields, I will map the free energy landscapes for monomer and oligomer attachment and predict rates for aluminum hydroxides growth. For validation of our theoretical predictions, I will seek opportunities for collaborations with experimentalists in atomic force microscopy (AFM) measurements of growth velocities and transmission electron microscopy (TEM) observations. The mechanistic insights gained in this study will also shed light on the growth mechanism for layer-structured silicates.

The topic of thrust 2 isquantification and control of solvent effects in oriented attachment. Nanoparticle-nanoparticle aggregation, or oriented attachment (OA), has been shown to occur during the growth of multiple natural materials. Recent work revealed the critical role of solvent in the form of a hydration force that prevents particle coalescence at close separations while enabling the co-alignment of particles. A comprehensive knowledge of the underlying mechanisms behind the hydration force is fundamental to understanding nanoparticle-based aggregation. I will utilize multi-scale computational efforts (MD, QM, and MC methods) to reveal the effects of surface and solution chemistry on the magnitude and sign of hydration force. I also plan to seek collaborations with experimentalists who can perform force measurement using AFM. This thrust has a potential transformative impact by tweaking the identified factors to accurately control the inter-particle forces and thus optimizing the conditions for particle-particle aggregation.

The topic of thrust 3 is computational design of micellar-enhanced ultrafiltration (MEUF) techniques. MEUF is a versatile wastewater treatment technique that removes dissolved ions and molecules by ultrafiltration membranes using surfactants. Although a large number of surfactants are available in the design space, only a limited number of them have been adopted in MEUF. Therefore, it is helpful to develop an efficient computational method for predicting optimal surfactant types to avoid extensive and cost-prohibitive experimental efforts. I will use a combined method of a continuum model (COSMO-RS) and MD simulations to select optimal surfactants for removing organic contaminants from wastewater. This work will provide potential surfactants and experimental variables that can be tested and verified in the experiments. Therefore, I seek to collaborate with experimentalists in measuring partition coefficients of contaminants between micelles and water and adsorption isotherms. Given the extensive amount of data produced from simulations, I also seek to collaborate with machine learning experts to facilitate faster predictions.

Teaching Interests:

I am interested in teaching a graduate-level course on atomistic simulations as well as an undergraduate-level course on interfacial chemistry and am able to more broadly teach subjects related to environmental chemistry and thermodynamics.