A variety of studies have begun exploring the use of NNIP-based workflows to predict classical interatomic potential parameters such as Espaloma, BespokeFit, the graph neural network for intermolecular forces proposed by Thürlemann et al, ByteFF, and ForceBalance. However, these studies focus on small molecule systems for biochemical applications, and no workflow has been applied to determining kinetic properties such as diffusivity, conductivity, and lithium-ion transference number of condensed polymer systems.