Maximizing Information: A Machine Learning Approach for Analysis of Complex Nanoscale Electromechanical Behavior in Defect‐Rich PZT Films
Maximizing Information: A Machine Learning Approach for Analysis of Complex Nanoscale Electromechanical Behavior in Defect‐Rich PZT Films
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DOI：
10.1002/smtd.202100552
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发表时间：
2021-10
期刊：
影响因子：
12.4
通讯作者：
Fengyuan Zhang;Kerisha N. Williams;David Edwards;A. Naden;Yulian Yao;S. Neumayer;Amit Kumar;B. Rodriguez;N. Bassiri‐Gharb
中科院分区：
文献类型：
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作者：
Fengyuan Zhang;Kerisha N. Williams;David Edwards;A. Naden;Yulian Yao;S. Neumayer;Amit Kumar;B. Rodriguez;N. Bassiri‐Gharb
基于扫描探针显微镜 (SPM) 的技术以纳米级分辨率探测微米级区域的材料特性，最终导致对介观尺度功能的研究。在 SPM 技术中，压电响应力显微镜 (PFM) 是探索铁电材料极化切换的高效工具。然而，它的信号对样本相关的静电和化学机电变化也很敏感。文献报告通常集中于与场外压电响应相比对场外压电响应的评估，因为后者对非铁电贡献的敏感性增加。使用结合场外和场外压电响应以及场外谐振频率的机器学习方法来最大化信息，研究了富含缺陷的 Pb(Zr,Ti)O3 薄膜中的切换压电响应。正如预期的那样，压电响应的主要贡献者主要是铁电体，以及现场测量期间的静电现象。第二个成分本质上是静电的，而第三个成分可能是由于多个非铁电过程的叠加造成的。所提出的方法将有助于更深入地理解弱铁电样品和具有大化学机电响应的材料中的开关现象。
Scanning Probe Microscopy (SPM) based techniques probe material properties over microscale regions with nanoscale resolution, ultimately resulting in investigation of mesoscale functionalities. Among SPM techniques, piezoresponse force microscopy (PFM) is a highly effective tool in exploring polarization switching in ferroelectric materials. However, its signal is also sensitive to sample‐dependent electrostatic and chemo‐electromechanical changes. Literature reports have often concentrated on the evaluation of the Off‐field piezoresponse, compared to On‐field piezoresponse, based on the latter's increased sensitivity to non‐ferroelectric contributions. Using machine learning approaches incorporating both Off‐ and On‐field piezoresponse response as well as Off‐field resonance frequency to maximize information, switching piezoresponse in a defect‐rich Pb(Zr,Ti)O3 thin film is investigated. As expected, one major contributor to the piezoresponse is mostly ferroelectric, coupled with electrostatic phenomena during On‐field measurements. A second component is electrostatic in nature, while a third component is likely due to a superposition of multiple non‐ferroelectric processes. The proposed approach will enable deeper understanding of switching phenomena in weakly ferroelectric samples and materials with large chemo‐electromechanical response.