Maximizing Information: A Machine Learning Approach for Analysis of Complex Nanoscale Electromechanical Behavior in Defect‐Rich PZT Films.

MLA

Zhang, Fengyuan, et al. “Maximizing Information: A Machine Learning Approach for Analysis of Complex Nanoscale Electromechanical Behavior in Defect‐Rich PZT Films.” Small Methods, vol. 5, no. 12, Dec. 2021, pp. 1–11. EBSCOhost, https://doi.org/10.1002/smtd.202100552.

APA

Zhang, F., Williams, K. N., Edwards, D., Naden, A. B., Yao, Y., Neumayer, S. M., Kumar, A., Rodriguez, B. J., & Bassiri, G. N. (2021). Maximizing Information: A Machine Learning Approach for Analysis of Complex Nanoscale Electromechanical Behavior in Defect‐Rich PZT Films. Small Methods, 5(12), 1–11. https://doi.org/10.1002/smtd.202100552

Chicago

Zhang, Fengyuan, Kerisha N. Williams, David Edwards, Aaron B. Naden, Yulian Yao, Sabine M. Neumayer, Amit Kumar, Brian J. Rodriguez, and Gharb, Nazanin Bassiri. 2021. “Maximizing Information: A Machine Learning Approach for Analysis of Complex Nanoscale Electromechanical Behavior in Defect‐Rich PZT Films.” Small Methods 5 (12): 1–11. doi:10.1002/smtd.202100552.