Perspective: Codesign for materials science: An optimal learning approach

by Turab Lookman, Francis J. Alexander, Alan R. Bishop
Published 2016-05-01

Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning

by Prasanna V. Balachandran, Benjamin Kowalski, Alp Sehirlioglu, Turab Lookman
Published 2018-04-01

Learning from data to design functional materials without inversion symmetry

by Prasanna V. Balachandran, Joshua Young, Turab Lookman, James M. Rondinelli
Published 2017-02-01

Accelerated search for materials with targeted properties by adaptive design

by Dezhen Xue, Prasanna V. Balachandran, John Hogden, James Theiler, Deqing Xue, Turab Lookman
Published 2016-04-01

Accelerated Search for BaTiO3‐Based Ceramics with Large Energy Storage at Low Fields Using Machine Learning and Experimental Design

by Ruihao Yuan, Yuan Tian, Dezhen Xue, Deqing Xue, Yumei Zhou, Xiangdong Ding, Jun Sun, Turab Lookman
Published 2019-11-01

Alkali-deficiency driven charged out-of-phase boundaries for giant electromechanical response

by Haijun Wu, Shoucong Ning, Moaz Waqar, Huajun Liu, Yang Zhang, Hong-Hui Wu, Ning Li, Yuan Wu, Kui Yao, Turab Lookman, Xiangdong Ding, Jun Sun, John Wang, Stephen J. Pennycook
Published 2021-05-01

Competing Interface and Bulk Effect–Driven Magnetoelectric Coupling in Vertically Aligned Nanocomposites

by Aiping Chen, Yaomin Dai, Ahmad Eshghinejad, Zhen Liu, Zhongchang Wang, John Bowlan, Erik Knall, Leonardo Civale, Judith L. MacManus‐Driscoll, Antoinette J. Taylor, Rohit P. Prasankumar, Turab Lookman, Jiangyu Li, Dmitry Yarotski, Quanxi Jia
Published 2019-10-01