How scanning probe microscopy can be supported by artificial intelligence and quantum computing?

Author:

Pregowska Agnieszka1ORCID,Roszkiewicz Agata1,Osial Magdalena1,Giersig Michael1

Affiliation:

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

Abstract

AbstractThe impact of Artificial Intelligence (AI) is rapidly expanding, revolutionizing both science and society. It is applied to practically all areas of life, science, and technology, including materials science, which continuously requires novel tools for effective materials characterization. One of the widely used techniques is scanning probe microscopy (SPM). SPM has fundamentally changed materials engineering, biology, and chemistry by providing tools for atomic‐precision surface mapping. Despite its many advantages, it also has some drawbacks, such as long scanning times or the possibility of damaging soft‐surface materials. In this paper, we focus on the potential for supporting SPM‐based measurements, with an emphasis on the application of AI‐based algorithms, especially Machine Learning‐based algorithms, as well as quantum computing (QC). It has been found that AI can be helpful in automating experimental processes in routine operations, algorithmically searching for optimal sample regions, and elucidating structure–property relationships. Thus, it contributes to increasing the efficiency and accuracy of optical nanoscopy scanning probes. Moreover, the combination of AI‐based algorithms and QC may have enormous potential to enhance the practical application of SPM. The limitations of the AI‐QC‐based approach were also discussed. Finally, we outline a research path for improving AI‐QC‐powered SPM.Research Highlights Artificial intelligence and quantum computing as support for scanning probe microscopy. The analysis indicates a research gap in the field of scanning probe microscopy. The research aims to shed light into ai‐qc‐powered scanning probe microscopy.

Publisher

Wiley

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3