(357ag) Computational Inverse Design of Multifunctional Surfaces to Control Water and Solute Behavior | AIChE

(357ag) Computational Inverse Design of Multifunctional Surfaces to Control Water and Solute Behavior


Jiao, S. - Presenter, University of California, Santa Barbara
DeStefano, A., University of Wyoming
Rivera Mirabal, D., University of Puerto Rico at Mayagüez
Segalman, R., UC Santa Barbara
Han, S., University of California, Santa Barbara
Shell, M. S., UC Santa Barbara
Next-generation membranes for water treatment that move beyond simple desalination require materials with precisely tuned functionality. In particular, the purification and reuse of highly contaminated waters, such as oilfield-produced water, face key challenges in removing a wide array of solutes, including small neutral solutes that are difficult to separate. Multifunctional membrane surfaces potentially provide a vast, underexplored design space to improve membrane transport properties, but are difficult to optimize through trial-and-error. Here, we demonstrate an inverse design computational approach to efficiently identifying promising materials. We develop a combined optimization, machine learning, and molecular simulation workflow to engineer the transport of water relative to that of boric acid in a model nanopore by spatially patterning the pore wall with nonpolar methyl and polar hydroxyl groups. The genetic algorithm optimization identifies non-intuitive functionalization strategies that hinder the transport of boric acid through the pore, simply by altering the functional group patterning. Examining patterns inspired by the genetic algorithm results, we demonstrate that precise spatial functionalization of the methyl and hydroxyl groups differentially impacts the transport of water and boric acid in the pore, enabling design solutions that simultaneously improve both permeability and selectivity, a longstanding trade-off in membrane technology. Moving towards a more synthetically accessible platform, we establish an integrated experimental-computational approach to elucidate the structural behavior of disordered polypeptoids, which can be used to precisely control chemical functionality at a surface. We then leverage this workflow to demonstrate that changes in the sequence of polar and nonpolar polypeptoid residues can tune hydration water structure and dynamics in non-intuitive and non-additive ways, suggesting that polypeptoid-decorated surfaces can be designed to control hydration and surface-solute interactions. Taken together, these projects provide new insight into the fundamental mechanism by which multifunctional surfaces perturb water and solute behavior and suggest novel, optimization-based approaches to mapping the design space and resolving longstanding challenges in membrane design.

Research Interests

bio(mimetic)molecules, hydrophobicity, inverse design, machine learning