Accelerated Discovery of Large Electrostrains in BaTiO $_{\textrm{3}}$ ‐Based Piezoelectrics Using Active Learning. Yuan, R., Liu, Z., Balachandran, P. V., Xue, D., Zhou, Y., Ding, X., Sun, J., Xue, D., & Lookman, T. 30(7):1702884.
Accelerated Discovery of Large Electrostrains in BaTiO $_{\textrm{3}}$ ‐Based Piezoelectrics Using Active Learning [link]Paper  doi  abstract   bibtex   
Abstract A key challenge in guiding experiments toward materials with desired properties is to effectively navigate the vast search space comprising the chemistry and structure of allowed compounds. Here, it is shown how the use of machine learning coupled to optimization methods can accelerate the discovery of new Pb‐free BaTiO 3 (BTO‐) based piezoelectrics with large electrostrains. By experimentally comparing several design strategies, it is shown that the approach balancing the trade‐off between exploration (using uncertainties) and exploitation (using only model predictions) gives the optimal criterion leading to the synthesis of the piezoelectric (Ba 0.84 Ca 0.16 )(Ti 0.90 Zr 0.07 Sn 0.03 )O 3 with the largest electrostrain of 0.23% in the BTO family. Using Landau theory and insights from density functional theory, it is uncovered that the observed large electrostrain is due to the presence of Sn, which allows for the ease of switching of tetragonal domains under an electric field.
@article{yuan_accelerated_2018,
	title = {Accelerated Discovery of Large Electrostrains in {BaTiO} $_{\textrm{3}}$ ‐Based Piezoelectrics Using Active Learning},
	volume = {30},
	issn = {0935-9648, 1521-4095},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/adma.201702884},
	doi = {10.1002/adma.201702884},
	abstract = {Abstract
            
              A key challenge in guiding experiments toward materials with desired properties is to effectively navigate the vast search space comprising the chemistry and structure of allowed compounds. Here, it is shown how the use of machine learning coupled to optimization methods can accelerate the discovery of new Pb‐free {BaTiO}
              3
              ({BTO}‐) based piezoelectrics with large electrostrains. By experimentally comparing several design strategies, it is shown that the approach balancing the trade‐off between exploration (using uncertainties) and exploitation (using only model predictions) gives the optimal criterion leading to the synthesis of the piezoelectric (Ba
              0.84
              Ca
              0.16
              )(Ti
              0.90
              Zr
              0.07
              Sn
              0.03
              )O
              3
              with the largest electrostrain of 0.23\% in the {BTO} family. Using Landau theory and insights from density functional theory, it is uncovered that the observed large electrostrain is due to the presence of Sn, which allows for the ease of switching of tetragonal domains under an electric field.},
	pages = {1702884},
	number = {7},
	journaltitle = {Advanced Materials},
	shortjournal = {Advanced Materials},
	author = {Yuan, Ruihao and Liu, Zhen and Balachandran, Prasanna V. and Xue, Deqing and Zhou, Yumei and Ding, Xiangdong and Sun, Jun and Xue, Dezhen and Lookman, Turab},
	urldate = {2024-01-10},
	date = {2018-02},
	langid = {english},
}
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