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扫描探针显微镜如何得到人工智能和量子计算的支持?

Agnieszka Pregowska¹, Agata Roszkiewicz¹, Magdalena Osial¹

¹Department of Information and Computational Science, Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland.

Microscopy research and technique

|June 12, 2024

概括

人工智能 (AI) 和量子计算 (QC) 可以通过自动化实验和提高准确性来增强扫描探针显微镜 (SPM). 这项研究探讨了AI-QC驱动的SPM,确定了研究差距和未来方向.

科学领域:

材料科学材料科学材料科学
计算科学计算科学
纳米技术纳米技术

背景情况:

扫描探头显微镜 (SPM) 对于材料表征至关重要,但面临着长时间扫描和样品损坏等挑战.
人工智能 (AI) 和量子计算 (QC) 为这些局限性提供了潜在的解决方案.

研究的目的:

探索AI和QC的整合,以支持和增强SPM测量.
确定研究缺口,并概述AI-QC驱动的SPM的未来方向.

主要方法:

专注于基于AI的算法,特别是机器学习,以及它们对SPM的应用.
研究将人工智能与量子计算 (QC) 结合起来,以提高SPM的协同潜力.
讨论SPM的AI-QC方法的局限性.

主要成果:

人工智能可以自动化SPM实验,优化样本区域选择,阐明结构-属性关系,提高效率和准确性.
人工智能和质量控制的结合显示了推动SPM实际应用的巨大潜力.
确定了AI-QC-SPM方法的局限性.

结论:

人工智能和QC集成为改善SPM能力提供了一个有前途的研究途径.
需要进一步的研究才能充分实现AI-QC驱动的SPM的潜力.
这项工作突出了通过计算方法推进SPM的研究缺口.

关键词:

人工智能的人工智能是人工智能.自动化实验,自动化实验.机器学习是机器学习.量子计算是一种量子计算.扫描探针显微镜扫描探针显微镜

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