The understanding of solvation is an essential prerequisite for the quantitative description and analysis of many sophisticated chemical, biological and biomolecular processes.. Implicit solvent models, particularly those based on the Poisson-Boltzmann (PB) equation for electrostatic analysis, are established approaches for solvation analysis. However, ad hoc solvent-solute interfaces and complex solutions of nonlinear equations post some severe limitations on their applications. We have introduced differential geometry (DG) based multiscale solvation models, which allow the solvent-solute interface, electrostatic potential, and even electron densities to be determined by the variation of a total free energy functional. In addition, our models is able to significantly reduce the number of free parameters and to avoid complicated interface problems raised by sharp solvent-solute interface. Finally, our DG based models have shown promising power in blind prediction of solvation as well as other applications. This is primarily joint work with Prof. Guowei Wei and Prof. Nathan Baker.