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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/12154

Title: Data mining for materials design: A computational study of single molecule magnet
Authors: Dam, Hieu Chi
Pham, Tien Lam
Ho, Tu Bao
Nguyen, Anh Tuan
Nguyen, Viet Cuong
Keywords: Data Mining
Materials Design
Single Molecule Magnet
Issue Date: 2014-01-23
Publisher: American Institute of Physics
Magazine name: The Journal of Chemical Physics
Volume: 140
Number: 4
Start page: 044101
DOI: 10.1063/1.4862156
Abstract: 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.
Rights: This is the author's version of the work. Copyright 2014 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Hieu Chi Dam, Tien Lam Pham, Tu Bao Ho, Anh Tuan Nguyen and Viet Cuong Nguyen, The Journal of Chemical Physics, 140(4), 044101 (2014) and may be found at http://dx.doi.org/10.1063/1.4862156
URI: http://hdl.handle.net/10119/12154
Material Type: author
Appears in Collections:a10-1. 雑誌掲載論文 (Journal Articles)

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