Our NNP is trained based on density functional theory (DFT) reference data at the revPBE-D3 level of theory. The training set includes both bulk aqueous NaCl structures as well as confined structures across a range of concentrations and slit heights. The NNP architecture used here only captures short-range interactions within the 12 Bohr cutoff of the atom-centered symmetry functions encoding the chemical environments within the system. In order to capture long-range electrostatic effects, we include a Coulomb baseline, in which each atom is assigned a fixed partial charge (ions are ±1, carbon atoms are zero, and water molecules have the charges of the SPC/E model). These charges give rise to the Coulombic energy of a system, E Coul . We can then decompose the total energy from DFT as E = E sr + E Coul , where E sr is a short-ranged contribution. The NNP is trained only on E sr and the corresponding short-ranged forces. When running molecular dynamics, we propagate the dynamics by summing together both the short-ranged contributions from the NNP and the Coulombic baseline.