Intelligent cross-linking in polymer simulations: SuSi’s approach to complex 3D networks

Cross-linked polymers play a vital role in the materials science due to their mechanical strength, chemical resistance, and thermal stability, making them invaluable in biomedical devices, coatings, and electronics. However, constructing realistic molecular models of these systems remains a challenge due to their complex cross-linked networks. This study introduces SuSi, a Python-based program designed to generate both linear and cross-linked polymer systems for molecular simulations. SuSi uses artificial intelligence tree search algorithms to optimize the cross-linking process, ensuring efficient and collision-free network formation. The program is compatible with the AMBER force field and supports a wide variety of polymer architectures, including homopolymers, block copolymers, and complex 3D-network structures. To demonstrate its capabilities, SuSi was employed to generate three distinct cross-linked systems: silane-cross-linked polyethylene (Si-XLPE), thermosensitive poly(NIPAAm-co-MBA), and the complex unsaturated polyesteramide hydrogel made of phenylalanine, butenediol, and fumarate, cross-linked with polyethylene glycol (UPEA-PEG). The generated structures were successfully parametrized for molecular dynamics simulations and validated through experimental observables, showing that SuSi is a versatile tool for accurately modeling complex polymeric systems and advancing polymer simulations.