From Quantum Mechanics to Coarse-Grained Models: Bridging the Gap toward Polymer Rational Design

In the rational design of novel polymers, the role of simulation methods based on classical physics is often hindered by the limited accuracy and transferability of the available models, at both the full-atomistic (FA) and coarse-grained (CG) level. Here, we introduce a first-principles-based, fully modular computational protocol for the generation of accurate and consistent FA and CG force fields, tailored on a specific material, and requiring as the sole input the chemical formula of one repeating monomeric unit of the target polymer. The proposed workflow is aimed to connect, across multiple scales, Quantum Mechanical (QM) calculations, FA and CG quantum-mechanically derived force fields (QMD-FFs), and Molecular Dynamics (MD), integrating them into a single, consistent, and reproducible framework. The protocol is tested on poly(ethylene terephthalate) (PET), a well-known polymeric material, widely used in the packaging industry. MD simulations carried out with our FA and CG QMD-FFs are found to significantly outperform standard general-purpose models in predicting key properties such as density, glass transition temperature, as well as the intra- and supra-molecular structure. Such improvement is traced back to the accuracy of the parent QM description by controlling the adherence of the lower level models to the reference set, monitoring this flow of information at each step of the applied procedure. The performances obtained for PET confirm the reliability of a general and tunable approach, which supports systematic refinement and hence stands as a promising tool for in silico design of novel polymers. Subjected to further automation, the procedure could also be integrated into computational machine-learning-based high-throughput schemes, paving the way toward an efficient data-driven polymer discovery.