Characterizing and Exploiting Topological and Point Defects in Ferroelectric Thin Films—Optimizing Electromechanical Response and Investigating Energy Landscapes with Automated Experiments

The static and dynamic properties of ferroelectric thin films are heavily impacted by the presence and distribution of both point- and topological defects. Harnessing and controlling these factors has been critical to improving the dielectric and electromechanical properties of ferroelectric thin films [1,2]. However, many of the mechanisms that associate functional properties with changes to material properties are still difficult to pinpoint, and their effects at the nanoscale are still poorly understood in many cases [3].<br/> <br/>In this talk, we will discuss our work on studying and characterizing both point- and topological defects in ferroelectric thin films. First, we explore the ability to dynamically modify the electromechanical response of defective BaTiO₃ thin films [4], via injection of vacancies in ultra-high vacuum environments by the scanning probe tip. Multiple lines of evidence from detailed piezoresponse force spectroscopy and atomic resolution imaging via scanning transmission electron microscopy are used to measure the local structure and functionality of these films. A strong environmental dependence on the local dynamics is found on the piezoresponse as a function of field cycling. These measurements are corroborated by thermodynamic, first-principles and reactive force field calculations, which point towards a mechanism of increased electromechanical response engendered by dynamic injection of vacancies in the scanning probe volume.<br/> <br/>At the same time, topological defects such as domain walls and vortices can also be critical to understanding and modifying the dielectric and piezoelectric properties of thin films [5]. We discuss a newly developed automated experiment framework that explores the interplay between grain boundaries, domain switching, and domain wall de-pinning, to attempt to quantitatively measure the impact of local domain structure and longer-range elastic fields on the dynamics of topological defects in a model PbTiO₃ thin film grain boundary. Preliminary reinforcement learning methodologies to optimize the domain wall geometries will be discussed. This work was supported by the Center for Nanophase Materials Sciences (CNMS), which is a US Department of Energy, office of Science User Facility at Oak Ridge National Laboratory.<br/> <b>References</b><br/>[1] N. Setter, et al. <i>Journal of applied physics</i> 100.5 (2006): 051606.<br/>[2] A. J. Bell, P. M. Shepley and Y. Li. <i>Acta Materialia</i> 195 (2020): 292-303.<br/>[3] R. K. Vasudevan et al.<i> Advanced Functional Materials</i> 23.1 (2013): 81-90.<br/>[4] K. P. Kelley et al. <i>Advanced Materials</i> 34.2 (2022): 2106426.<br/>[5] G. F. Nataf et al <i>Nature Reviews Physics</i> 2.11 (2020): 634-648.