(197ac) Reproducible Workflows for Parameterizing and Simulating Models of Complex Conjugated Copolymers for Organic Photovoltaics

Organic semiconductors that can self-assemble into morphologies with high charge mobility have the potential to transform green energy generation, but measuring or predicting the stable morphologies and their charge mobilities is difficult. Here we develop computational workflows for screening the morphologies of organic photovoltaic (OPV) macromolecules and copolymers. We employ the Espaloma¹ toolkit to parameterize all-atom forcefields, signac-flow² to manage simulation workspaces, MoSDeF tools³ to initialize simulation volumes, and HOOMD-Blue⁴ to perform molecular dynamics simulations. We compare predicted morphologies between all-atom and united atom representations with a variety of methods of handling partial charges for a set of complex donor-acceptor copolymers⁵ and justify the use of the coarser models to predict morphology in these systems. Finally, we summarize short-range structural motifs and long-range periodicities that emerge across conjugated polymers with varying backbone rigidity.

This material is based upon work supported by the National Science Foundation under Grant No. 1653954.

(1) Wang, Y.; Fass, J.; Kaminow, B.; Herr, J. E.; Rufa, D.; Zhang, I.; Pulido, I.; Henry, M.; Chodera, J. D. End-to-End Differentiable Molecular Mechanics Force Field Construction. Chem. Sci. 2022, 13 (41), 12016–12033. https://doi.org/10.1039/D2SC02739A.

(2) Adorf, C. S.; Dodd, P. M.; Ramasubramani, V.; Glotzer, S. C. Simple Data and Workflow Management with the Signac Framework. Comput. Mater. Sci. 2018, 146, 220–229. https://doi.org/10.1016/j.commatsci.2018.01.035.

(3) Cummings, P. T.; MCabe, C.; Iacovella, C. R.; Ledeczi, A.; Jankowski, E.; Jayaraman, A.; Palmer, J. C.; Maginn, E. J.; Glotzer, S. C.; Anderson, J. A.; Ilja Siepmann, J.; Potoff, J.; Matsumoto, R. A.; Gilmer, J. B.; DeFever, R. S.; Singh, R.; Crawford, B. Open‐source Molecular Modeling Software in Chemical Engineering Focusing on the Molecular Simulation Design Framework. AIChE J. 2021, 67 (3). https://doi.org/10.1002/aic.17206.

(4) Anderson, J. A.; Glaser, J.; Glotzer, S. C. HOOMD-Blue: A Python Package for High-Performance Molecular Dynamics and Hard Particle Monte Carlo Simulations. Comput. Mater. Sci. 2020, 173, 109363. https://doi.org/10.1016/j.commatsci.2019.109363.

(5) Danielsen, S. P. O.; Bridges, C. R.; Segalman, R. A. Chain Stiffness of Donor–Acceptor Conjugated Polymers in Solution. Macromolecules 2022, 55 (2), 437–449. https://doi.org/10.1021/acs.macromol.1c02229.