Details

Autor(en) / Beteiligte

• Xue, Dezhen
• Balachandran, Prasanna V.
• Yuan, Ruihao
• Hu, Tao
• Qian, Xiaoning
• Dougherty, Edward R.
• Lookman, Turab

Titel

Accelerated search for BaTiO₃-based piezoelectrics with vertical morphotropic phase boundary using Bayesian learning

Ist Teil von

• Proceedings of the National Academy of Sciences - PNAS, 2016-11, Vol.113 (47), p.13301-13306

Ort / Verlag

United States: National Academy of Sciences

Erscheinungsjahr

2016

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• 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.