where D is the diffusion coefficient, ⟨r 2 ⟩ the mean-square displacement of β -Glc (the mean is carried over the number of β -Glc in the simulation) and t the time. Figure presents the results. In previous MD studies, non-physical β -Glc aggregation manifested within a few ns, characterized by a sharp peak in the radial distribution function at about 5.5 Å. In our simulations, we do not see this feature (Figure ). Rather, we see a much smaller and broader peak at 7 Å, whose integration (Figure ) scales with the concentration of β -Glc. This suggests that non-physical aggregation of the monosaccharides in water does not equate to the broad peak in our radial distribution function. Further, the diffusion coefficients computed from these simulations agree well with experimental data (Figure ), where AMOEBA only slightly underestimates the diffusion of β -Glc in water, outperforming other force fields. Running MD for the highest concentration (c=4 mol/kg) without mutual polarization results in a similar, although slightly broader, COM radial distribution function (light green curve in Figures and). This result emphasizes van der Waals interactions as governing the aggregation of monosaccharides in solution, not polarization. In summary, the polarizable AMOEBA force field with its robust multipole expansion, atomic induced dipoles and buffered 14-7 Halgren potential outperforms other force fields when modeling monosaccharides in solution. As AMOEBA has also been proven accurate for water properties and protein modeling, it provides the opportunity for a unified set of parameters that can described saccharides in diverse hydrated environments.