  Understanding nucleation from aqueous solutions is of fundamental importance
in a multitude of fields, ranging from materials science to biophysics. The
complex solvent-mediated interactions in aqueous solutions hamper the
development of a simple physical picture elucidating the roles of different
interactions in nucleation processes. In this work we make use of three
complementary techniques to disentangle the role played by short and long-range
interactions in solvent mediated nucleation. Specifically, the first approach
we utilize is the local molecular field (LMF) theory to renormalize long-range
Coulomb electrostatics. Secondly, we use well-tempered metadynamics to speed up
rare events governed by short-range interactions. Thirdly, deep learning-based
State Predictive Information Bottleneck approach is employed in analyzing the
reaction coordinate of the nucleation processes obtained from LMF treatment
coupled with well-tempered metadynamics. We find that the two-step nucleation
mechanism can largely be captured by the short-range interactions, while the
long-range interactions further contribute to the stability of the primary
crystal state at ambient conditions. Furthermore, by analyzing the reaction
coordinate obtained from combined LMF-metadynamics treatment, we discern the
fluctuations on different time scales, highlighting the need for long-range
interactions when accounting for metastability.
