Solvent model
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In computational chemistry, a solvent model is a computational method that accounts for the behavior of solvated condensed phases.[1][2][3] Solvent models enable simulations and thermodynamic calculations applicable to reactions and processes which take place in solution. These include biological, chemical and environmental processes.[1] Such calculations can lead to new predictions about the physical processes occurring by improved understanding.
Solvent models have been extensively tested and reviewed in the scientific literature. The various models can generally be divided into two classes, explicit and implicit models, all of which have their own advantages and disadvantages. Implicit models are generally computationally efficient and can provide a reasonable description of the solvent behavior, but fail to account for the local fluctuations in solvent density around a solute molecule. The density fluctuation behavior is due to solvent ordering around a solute and is particularly prevalent when one is considering water as the solvent. Explicit models are often less computationally economical, but can provide a physical spatially resolved description of the solvent. However, many of these explicit models are computationally demanding and can fail to reproduce some experimental results, often due to certain fitting methods and parametrization. Hybrid methodologies are another option. These methods incorporate aspects of implicit and explicit aiming to minimize computational cost while retaining at least some spatial resolution of the solvent. These methods can require more experience to use them correctly and often contain post-calculation correction terms.[4]