A polarizable high‐rank quantum topological electrostatic potential developed using neural networks: Molecular dynamics simulations on the hydrogen fluoride dimer

The HF molecule is a simple polar system that serves as a prototype for developing new potentials. Here we build on earlier work [Liem and Popelier, J Chem Phys 2003, 119, 4560] in which a high‐rank multipolar potential was used to simulate liquid HF. That work was the first example of high‐rank multipole moments (up to hexadecapole) being employed in conjunction with multipolar Ewald summation in a molecular dynamics simulation. This potential is now extended with polarization, which is delivered by artificial neural networks. The neural nets predict how atomic multipole moments change as the position of neighboring molecules vary. This novel approach is successfully tested on the HF dimer in vacuum.