Molecular aspects of solvation investigated using statistical mechanics

Norio Yoshida, Katsura Nishiyama

Research output: Chapter in Book/Report/Conference proceedingChapter


The majority of organic and inorganic chemical reactions relevant for synthesis or industrial applications take place in the solution phase. Similarly, almost all biological reactions proceed in an aqueous environment. Theoretical descriptions of chemical reactions in solution differ in the way they treat the surrounding solvent molecules. Their large number excludes an explicit treatment. Nevertheless, the elucidation of the solvated structure plays a key role in obtaining an accurate description of chemical reactions as well as the activity of biomolecules. In this chapter, we review recent theoretical developments for the description of solvated molecules during chemical reactions, employing statistical physics to treat the solvent. The reference interaction-site model (RISM) theory, and some of its extensions, coupled with recent quantum mechanical theories, are described, and applications to various systems in solution, from conventional chemical reactions to the activities of biomolecules in biological systems, are presented. The solvent distribution around the solute and solute-solvent interactions is critical for the reactions and structures of such systems. The theories described here offer the possibility to obtain detailed information on the molecular origin of solvation and may contribute to discover and elucidate novel phenomena in chemistry, physics, and bioscience.

Original languageEnglish
Title of host publicationHandbook of Computational Chemistry
PublisherSpringer International Publishing
Number of pages17
ISBN (Electronic)9783319272825
ISBN (Print)9783319272818
Publication statusPublished - Jan 1 2017

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Computer Science
  • General Engineering
  • General Mathematics
  • General Agricultural and Biological Sciences
  • General Biochemistry,Genetics and Molecular Biology
  • General Medicine


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