title: Information-theoretic approach for the discovery of design rules for crystal chemistry.
abstract: In this work, it is shown that for the first time that, using information-entropy-based methods, one can quantitatively explore the relative impact of a wide multidimensional array of electronic and chemical bonding parameters on the structural stability of intermetallic compounds. Using an inorganic AB2 compound database as a template data platform, the evolution of design rules for crystal chemistry based on an information-theoretic partitioning classifier for a high-dimensional manifold of crystal chemistry descriptors is monitored. An application of this data-mining approach to establish chemical and structural design rules for crystal chemistry is demonstrated by showing that, when coupled with first-principles calculations, statistical inference methods can serve as a tool for significantly accelerating the prediction of unknown crystal structures.
authors: Department of Materials Science and Engineering, Iowa State University, Ames, Iowa 50011, United States.
authors: Chang Sun
authors: CS
authors: Kong
authors: Wei
authors: W
authors: Luo
authors: Sergiu
authors: S
authors: Arapan
authors: Pierre
authors: P
authors: Villars
authors: Shuichi
authors: S
authors: Iwata
authors: Rajeev
authors: R
authors: Ahuja
authors: Krishna
authors: K
authors: Rajan
mesh_terms: D002621:Chemistry / Q000379:methods*; D018360:Crystallography, X-Ray; D057225:Data Mining; D062126:Databases, Chemical; D005544:Forecasting; D007287:Inorganic Chemicals; D015394:Molecular Structure
chemical_list: D007287:Inorganic Chemicals