Department of Materials Science and Engineering, Iowa State University, Ames, Iowa 50011, United States.
J Chem Inf Model. 2012 Jul 23;52(7):1812-20. doi: 10.1021/ci200628z. Epub 2012 Jul 12.
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.
在这项工作中，首次表明，使用基于信息熵的方法，可以定量探索广泛的多维电子和化学成键参数对金属间化合物结构稳定性的相对影响。使用无机 AB2 化合物数据库作为模板数据平台，监测基于信息理论划分分类器的多维晶体化学描述符高维流形的晶体化学设计规则的演变。通过展示当与第一性原理计算相结合时，统计推断方法可以作为加速未知晶体结构预测的工具，证明了这种数据挖掘方法在建立晶体化学的化学和结构设计规则方面的应用。
