Periodic NVT simulations driven by mbGDML force fields were performed at 298.15 K for 10-30 ps in the atomic simulation environment (ASE). Note that NVT simulations could artificially bias intermolecular distances due to the volume constraint. NPT simulations would be a more rigorous metric, but these are not yet implemented in mbGDML, and this will be the focus of future work. The minimum-image convention was used with cubic boxes with lengths of 16 Å (137 molecules), 18 Å (67 molecules), and 16 Å (61 molecules) for water, acetonitrile, and methanol, respectively. Production trajectories were used to compute all possible RDFs. Some RDF curves are shown in Fig. . Wa- ter, acetonitrile, and methanol reference RDF curves are from neutron diffraction experiments. Results from classical MD simulations are also shown in Fig. . Note that classical references often include some fitting to empirical data, whereas mbGDML and others run calculations with no explicit empirical fitting. Individual figures of all RDF curves, along with labeled classical references, are shown in the ESI. Dispersion and polarization are not always accurately treated with MP2 theory, and likewise, the underlying model chemistry (MP2/def2-TZVP) to train mbGDML force fields may not accurately reproduce experimental liquid properties. For example, MP2 yields excellent results for liquid water simulations when appropriate density corrections or basis set error cancellation schemes are employed, but these were not used here. To our knowledge, a thorough investigation has not been performed for liquid acetonitrile and methanol with MP2, so the agreement with experiments is more uncertain. Note that molecular simulations using Kohn-Sham density functional theory (DFT) results in comparable differences in RDFs shown in Fig. , depending on the exchange-correlation functional and dispersion treatment used. The simulated RDFs with mbGDML fairly agree with the reference curves. In particular, the water g OO (r) in Fig. agrees remarkably well with experimental data. This is consistent with fragment-based ab initio MD (AIMD) simulations. However, these AIMD simulations include higher-order contributions through electrostatic embedding. Deviations in the g OH (r) and g HH (r) curves are partially due to the neglect of quantum nuclear effects. In all cases, acetonitrile peaks from mbGDML are less intense than the reference curves. This indicates that the predicted liquid structure with mbGDML is less ordered than the deuterated neutron diffraction data. Notably, g NN (r) is wide with two distinct peaks that deviate from the experimental reference. However, classical RDFs from the literature can vary substantially. Some classical potentials result in a similar g NN (r) shape while others better resemble the experimental reference.