Kelley Kyle P, Ren Yao, Morozovska Anna N, Eliseev Eugene A, Ehara Yoshitaka, Funakubo Hiroshi, Giamarchi Thierry, Balke Nina, Vasudevan Rama K, Cao Ye, Jesse Stephen, Kalinin Sergei V
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States.
Department of Materials Science and Engineering, University of Texas at Arlington, Arlington, Texas 76019, United States.
ACS Nano. 2020 Aug 25;14(8):10569-10577. doi: 10.1021/acsnano.0c04601. Epub 2020 Aug 6.
Domain walls and topological defects in ferroelectric materials have emerged as a powerful tool for functional electronic devices including memory and logic. Similarly, wall interactions and dynamics underpin a broad range of mesoscale phenomena ranging from giant electromechanical responses to memory effects. Exploring the functionalities of individual domain walls, their interactions, and controlled modifications of the domain structures is crucial for applications and fundamental physical studies. However, the dynamic nature of these features severely limits studies of their local physics since application of local biases or pressures in piezoresponse force microscopy induce wall displacement as a primary response. Here, we introduce an approach for the control and modification of domain structures based on automated experimentation, whereby real-space image-based feedback is used to control the tip bias during ferroelectric switching, allowing for modification routes conditioned on domain states under the tip. This automated experiment approach is demonstrated for the exploration of domain wall dynamics and creation of metastable phases with large electromechanical response.
铁电材料中的畴壁和拓扑缺陷已成为包括存储器和逻辑器件在内的功能性电子设备的有力工具。同样，壁相互作用和动力学是从巨大的机电响应到记忆效应等广泛的介观现象的基础。探索单个畴壁的功能、它们的相互作用以及对畴结构的可控修饰对于应用和基础物理研究至关重要。然而，这些特征的动态性质严重限制了对其局部物理的研究，因为在压电力显微镜中施加局部偏置或压力会导致壁位移作为主要响应。在此，我们介绍一种基于自动实验的畴结构控制和修饰方法，即利用基于实空间图像的反馈在铁电开关过程中控制尖端偏置，从而实现基于尖端下方畴状态的修饰路径。这种自动实验方法被用于探索畴壁动力学和创建具有大机电响应的亚稳相。
