In:
Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 47 ( 2016-11-22), p. 13301-13306
Abstract:
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 BaTiO 3 -based piezoelectrics with the desired target of a vertical morphotropic phase boundary. We predict, synthesize, and characterize a solid solution, (Ba 0.5 Ca 0.5 )TiO 3 -Ba(Ti 0.7 Zr 0.3 )O 3 , with piezoelectric properties that show better temperature reliability than other BaTiO 3 -based piezoelectrics in our initial training data.
Type of Medium:
Online Resource
ISSN:
0027-8424
,
1091-6490
DOI:
10.1073/pnas.1607412113
Language:
English
Publisher:
Proceedings of the National Academy of Sciences
Publication Date:
2016
detail.hit.zdb_id:
209104-5
detail.hit.zdb_id:
1461794-8
SSG:
11
SSG:
12
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