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)


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
Issue number4
Publication statusPublished - 2014 Jan 28
Externally publishedYes

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry


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