Strategies for the Development of Conjugated Polymer Molecular Dynamics Force Fields Validated with Neutron and X-ray Scattering

Conjugated polymers (CPs) enable a wide range of lightweight, lower cost, and flexible organic electronic devices, but a thorough understanding of relationships between molecular structure and dynamics and electronic performance is critical for improved device efficiencies and for new technologies. Molecular dynamics (MD) simulations offer in silico insight into this relationship, but their accuracy relies on the approach used to develop the model's parameters or force field (FF). In this Perspective, we first review current FFs for CPs and find that most of the models implement an arduous reparameterization of inter-ring torsion potentials and partial charges of classical FFs. However, there are few FFs outside of simple CP molecules, e.g., polythiophenes, that have been developed over the last two decades. There is also limited reparameterization of other parameters, such as nonbonded Lennard-Jones interactions, which we find to be directly influenced by conjugation in these materials. We further provide a discussion on experimental validation of MD FFs, with emphasis on neutron and X-ray scattering. We define multiple ways in which various scattering methods can be directly compared to results of MD simulations, providing a powerful experimental validation metric of local structure and dynamics at relevant length and time scales to charge transport mechanisms in CPs. Finally, we offer a perspective on the use of neutron scattering with machine learning to enable high-throughput parametrization of accurate and experimentally validated CP FFs enabled not only by the ongoing advancements in computational chemistry, data science, and high-performance computing but also using oligomers as proxies for longer polymer chains during FF development.

Automated summary

Conjugated polymers (CPs) have enabled a variety of lightweight, low-cost, and flexible organic electronic devices, but a thorough understanding of the relationship between molecular structure, dynamics, and electronic performance is crucial. Molecular dynamics (MD) simulations provide theoretical insights into these relationships, but accurate parameterization of force fields (FFs) for CPs and experimental validation methods such as neutron and X-ray scattering are essential for improving device efficiencies and developing new technologies. The use of machine learning and oligomers as proxies for longer polymer chains show promise in high-throughput parametrization of accurate CP FFs.