In the past three decades, there have been numerous reviews dedicated to the theoretical and computational aspects of the study of liquid systems. As an important phenomenon of fundamental interest, solvation has a profound effect on the behavior of molecules and reaction pathways. Theoretical approaches to understanding solvation range in complexity from explicit models simulating multiple solvent molecules to implicit models that describe an approximate mean field of the bulk solvent. Explicit simulation of the solvent environment provides a highly detailed description of solvation, however, this type of calculation is very expensive and often requires extensive sampling to determine equilibrium properties. For example, if 100 molecules of a solvent are treated explicitly, 900 degrees of freedom for water, 7200 degrees of freedom for 1-heptanol, and 17100 degrees of freedom for 1-Octadecanol will be added respectively. Analyzing observable properties of a solute requires averaging over these degrees of freedom, often through Monte Carlo or molecular dynamics techniques, which are limited by computer resources and computing performance.