Preprint: (Post et al 2026) - Ab initio parametrization of distributed polarizable force fields

We propose a first-principles based parameterization procedure for atomic polarizability tensors and scalars, validated on a set of small set of organic molecules with conjugated building blocks. To overcome the computational cost of ab initio calculations, we train a message-passing graph neural network to predict polarizability parameters, enabling efficient and scalable parameterization.

The data sets that support the simulations reported here will be made freely accessible upon publication.