Raghavan Aditya, Pant Rohit, Takeuchi Ichiro, Eliseev Eugene A, Checa Marti, Morozovska Anna N, Ziatdinov Maxim, Kalinin Sergei V, Liu Yongtao
Department of Materials Science and Engineering, University of Tennessee, Knoxville, Tennessee 37909, United States.
Deparment of Materials Science and Engineering, University of Maryland, College Park, Maryland 20742, United States.
ACS Nano. 2024 Sep 17;18(37):25591-25600. doi: 10.1021/acsnano.4c06380. Epub 2024 Sep 6.
Combinatorial spread libraries offer an approach to explore the evolution of material properties over broad concentration, temperature, and growth parameter spaces. However, the traditional limitation of this approach is the requirement for the read-out of functional properties across the library. Here we develop automated piezoresponse force microscopy (PFM) for the exploration of combinatorial spread libraries and demonstrate its application in the SmBiFeO system with the ferroelectric-antiferroelectric morphotropic phase boundary. This approach relies on the synergy of the quantitative nature of PFM and the implementation of automated experiments that allow PFM-based sampling of macroscopic samples. The concentration dependence of pertinent ferroelectric parameters was determined and used to develop the mathematical framework based on the Ginzburg-Landau theory describing the evolution of these properties across the concentration space. We pose that a combination of automated scanning probe microscope and combinatorial spread library approach will emerge as an efficient research paradigm to close the characterization gap in high-throughput materials discovery. We make the data sets open to the community, and we hope that this will stimulate other efforts to interpret and understand the physics of these systems.
组合扩散库提供了一种在宽广的浓度、温度和生长参数空间中探索材料性能演变的方法。然而，这种方法的传统局限性在于需要读出整个库的功能特性。在此，我们开发了用于探索组合扩散库的自动化压电响应力显微镜（PFM），并展示了其在具有铁电 - 反铁电同型相界的SmBiFeO系统中的应用。这种方法依赖于PFM的定量特性与自动化实验的结合，后者允许对宏观样品进行基于PFM的采样。确定了相关铁电参数的浓度依赖性，并用于基于金兹堡 - 朗道理论开发描述这些特性在浓度空间中演变的数学框架。我们认为，自动化扫描探针显微镜与组合扩散库方法的结合将成为一种有效的研究范式，以弥合高通量材料发现中的表征差距。我们将数据集向社区开放，希望这将激发其他解读和理解这些系统物理特性的努力。
