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      Metal Ion Modeling Using Classical Mechanics

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      Chemical Reviews

      American Chemical Society

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          Abstract

          Metal ions play significant roles in numerous fields including chemistry, geochemistry, biochemistry, and materials science. With computational tools increasingly becoming important in chemical research, methods have emerged to effectively face the challenge of modeling metal ions in the gas, aqueous, and solid phases. Herein, we review both quantum and classical modeling strategies for metal ion-containing systems that have been developed over the past few decades. This Review focuses on classical metal ion modeling based on unpolarized models (including the nonbonded, bonded, cationic dummy atom, and combined models), polarizable models (e.g., the fluctuating charge, Drude oscillator, and the induced dipole models), the angular overlap model, and valence bond-based models. Quantum mechanical studies of metal ion-containing systems at the semiempirical, ab initio, and density functional levels of theory are reviewed as well with a particular focus on how these methods inform classical modeling efforts. Finally, conclusions and future prospects and directions are offered that will further enhance the classical modeling of metal ion-containing systems.

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          Self-Consistent Equations Including Exchange and Correlation Effects

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            Inhomogeneous Electron Gas

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              Density-functional thermochemistry. III. The role of exact exchange

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                Author and article information

                Journal
                Chem Rev
                Chem. Rev
                cr
                chreay
                Chemical Reviews
                American Chemical Society
                0009-2665
                1520-6890
                03 January 2017
                08 February 2017
                : 117
                : 3
                : 1564-1686
                Affiliations
                Department of Chemistry, Department of Biochemistry and Molecular Biology, and Institute of Cyber-Enabled Research, Michigan State University , East  Lansing, Michigan 48824, United States
                Author notes
                Article
                10.1021/acs.chemrev.6b00440
                5312828
                28045509
                Copyright © 2017 American Chemical Society

                This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes.

                Categories
                Review
                Custom metadata
                cr6b00440
                cr-2016-00440p

                Chemistry

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