arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2108.03290cond-mat.mtrl-scicond-mat.dis-nncond-mat.mes-hallphysics.data-an
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通过扫描透射电子显微镜中的自主实验在纳米等离子体系统中发现物理

Physics discovery in nanoplasmonic systems via autonomous experiments in Scanning Transmission Electron Microscopy

Kevin M. Roccapriore, Sergei V. Kalinin, Maxim Ziatdinov

摘要:

自主实验中的物理驱动发现已经成为机器学习在物理科学中的梦想应用。在这里,我们开发并实验性地实现了一种深度内核学习工作流程,该工作流程结合了目标功能响应的相关预测及其结构的不确定性,以及基于物理的采集功能选择,该功能可以自主引导图像空间的导航。与经典的贝叶斯优化方法相比,该方法可以捕获现实材料图像中存在的复杂空间特征,并动态学习结构-性能关系。结合灵活的定标器功能,允许将物理兴趣程度归因于预测光谱,这使得在自动化实验中的物理发现成为可能。在这里,这种方法被说明为纳米粒子的纳米等离子体激元研究和实验实施在一个真正自主的方式在MnPS 3,一个鲜为人知的光束敏感的层状2D材料的体和边缘等离子体激元的发现。这种方法是通用的,可以直接用于任何标本,预计将适用于任何基于探针的显微技术,包括其他STEM模式,扫描探针显微镜,化学和光学成像。

英文摘要:

Physics-driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here we develop and experimentally implement a deep kernel learning workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics-based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure-property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk- and edge plasmon discovery in MnPS3, a lesser-known beam-sensitive layered 2D material. This approach is universal, can be directly used as-is with any specimen, and is expected to be applicable to any probe-based microscopic techniques including other STEM modalities, Scanning Probe Microscopies, chemical, and optical imaging.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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