期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2016
卷号：113
期号：47
页码：13301-13306
DOI：10.1073/pnas.1607412113
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：SignificanceLearning from data to accelerate the discovery of new materials is an outstanding challenge in materials science. However, in addition to data, a distinguishing aspect of materials science is that there exists a substantial body of knowledge in the form of phenomenological models and physical theories. We combine informatics and materials knowledge using results from Landau-Devonshire theory to guide experiments in the design of lead-free piezoelectrics with desired properties. An outstanding challenge in the nascent field of materials informatics is to incorporate materials knowledge in a robust Bayesian approach to guide the discovery of new materials. Utilizing inputs from known phase diagrams, features or material descriptors that are known to affect the ferroelectric response, and Landau-Devonshire theory, we demonstrate our approach for BaTiO3-based piezoelectrics with the desired target of a vertical morphotropic phase boundary. We predict, synthesize, and characterize a solid solution, (Ba0.5Ca0.5)TiO3-Ba(Ti0.7Zr0.3)O3, with piezoelectric properties that show better temperature reliability than other BaTiO3-based piezoelectrics in our initial training data.
