Data mining for materials design: A computational study of single molecule magnet

Hieu Chi Dam, Tien Lam Pham, Tu Bao Ho, Anh Tuan Nguyen, Viet Cuong Nguyen

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

We develop a method that combines data mining and first principles calculation to guide the designing of distorted cubane Mn4+ Mn 33+ 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 Mn4 + and Mn3 + 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 results.

Original languageEnglish
Article number044101
JournalJournal of Chemical Physics
Volume140
Issue number4
DOIs
Publication statusPublished - 2014 Jan 28

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