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Data mining for materials design: A computational study of single molecule magnet
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Description
We develop a method that combines data mining and first principles calculation to guide the designing of distorted cubane Mn^<4+>Mn^<3+>_3 single molecule magnets. The essential idea of the method is a process consisting of sparse regressions and cross-validation for analyzing calculated data of the materials. The method allows us to demonstrate that the exchange coupling between Mn^<4+> and Mn^<3+> ions can be predicted from the electronegativities of constituent ligands and the structural features of the molecule by a linear regression model with high accuracy. The relations between the structural features and magnetic properties of the materials are quantitatively and consistently evaluated and presented by a graph. We also discuss the properties of the materials and guide the material design basing on the obtained resutls.
identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/12154
Journal
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- The Journal of Chemical Physics
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The Journal of Chemical Physics 140 (4), 044101-, 2014-01-23
American Institute of Physics
