Accelerated Prediction\nof Phase Behavior for Block\nCopolymer Libraries Using a Molecularly Informed Field Theory

Solution\nformulations involving polymers are the basis\nfor a wide\nrange of products spanning consumer care, therapeutics, lubricants,\nadhesives, and coatings. These multicomponent systems typically show\nrich self-assembly and phase behavior that are sensitive to even small\nchanges in chemistry and composition. Longstanding computational efforts\nhave sought techniques for predictive modeling of formulation structure\nand thermodynamics without experimental guidance, but the challenges\nof addressing the long time scales and large length scales of self-assembly\nwhile maintaining chemical specificity have thwarted the emergence\nof general approaches. As a consequence, current formulation design\nremains largely Edisonian. Here, we present a multiscale modeling\napproach that accurately predicts, without any experimental input,\nthe complete temperature–concentration phase diagram of model\ndiblock polymers in solution, as established postprediction through\nsmall-angle X-ray scattering. The methodology employs a strategy whereby\natomistic molecular dynamics simulations is used to parametrize coarse-grained\nfield-theoretic models; simulations of the latter then easily surmount\nlong equilibration time scales and enable rigorous determination of\nsolution structures and phase behavior. This systematic and predictive\napproach, accelerated by access to well-defined block copolymers,\nhas the potential to expedite <i>in silico</i> screening\nof novel formulations to significantly reduce trial-and-error experimental\ndesign and to guide selection of components and compositions across\na vast range of applications.