2023 AIChE Annual Meeting

(508g) Efficient Simulation of Complex Fluid Phase Diagrams within Self-Consistent Field Theory Using Bayesian Optimization

Authors

Steven G. Arturo - Presenter, The Dow Chemical Company
Kaoru Aou, Dow Chemical
Huikuan Chao, University of Pennsylvania
Daniel Dermody, The Dow Chemical Company
William Edsall, The Dow Chemical Company
Jillian Emerson, Dow Chemical Company
Kathryn Grzesiak, The Dow Chemical Company
Paul M. Mwasame, University of Delaware
Clyde Fare, IBM Research UK
Jed W. Pitera, IBM Almaden Research Center
Edward Pyzer-Knapp, IBM Research UK
The phase diagrams of complex fluids are essential for understanding solubility and miscibility, properties of central importance in polymer formulation. At a typical industrial resolution of 10 wt%, exhaustive exploration of a ternary phase diagram requires simulation or experimentation at 63 composition points, a number which grows exponentially with the number of components. Using a new objective function derived from Self-Consistent Field Theory (SCFT) computations coupled with a constrained Bayesian optimization algorithm, we demonstrate efficient search of phase boundaries in a sample two-phase ternary modeled by polymer SCFT with 50% fewer simulations than an exhaustive search. Our approach is general, gradient-free, and can be applied to either simulation or experimental campaigns.