The demonstrated ability of NNIP to accurately predict intermediate-range structures and their populations despite being trained on small DFT simulation cells can be attributed to 1) training on a diverse range of configurations beyond a single AIMD trajectory and 2) sufficient charge-screening of long- range interactions in FLiBe. First, training the NNIP on configurations sampled at both 510 °C and 700 °C enables accurate interpolation of atomic forces and energies over the wide range NNMD-predicted configurations. Second, it is believed that the electrostatic potential beyond the 8 Å NNIP cutoff are sufficiently screened by polarizable solvent ions. This is consistent with our previous studies of other molten salts containing multivalent cations, in which NNMD-predicted structures were supported by Raman spectroscopy. However, we note from our previous investigation that it is possible for compounding approximations of semi-empirical DFT-VdW functionals and the NNIP truncation beyond 8 Å to induce larger errors for those systems and properties that are more strongly influenced by long-range interactions. In such cases, other considerations may be required for the explicit treatment of these effects. Here, the NNIP agrees with the scattering structure factor, providing confidence in the structural analysis.