Scientific exploration with expert knowledge (SEEK) in autonomous scanning probe microscopy with active learning
This work introduces a knowledge-informed framework that integrates human expertise and prior interest into active learning-driven autonomous experimentation, which enhances the exploration efficiency through more targeted experimentation.
Authors
- Rama Krishnan Vasudevan (ORCID: https://orcid.org/0000-0003-4692-8579)
- Hiroshi Funakubo (ORCID: https://orcid.org/0000-0002-1106-200X)
- Sergei V. Kalinin (ORCID: https://orcid.org/0000-0001-5354-6152)
- Yongtao Liu (ORCID: https://orcid.org/0000-0003-0152-1783)
- Utkarsh Pratiush (ORCID: https://orcid.org/0009-0003-7249-103X)
Institutions
- Tokyo Institute of Technology (JP)
- Oak Ridge National Laboratory (US)
- Pacific Northwest National Laboratory (US)
- Knoxville College (US)
- University of Tennessee at Knoxville (US)
Publication Details
- Journal
- Digital Discovery
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1039/d4dd00277f
- Citations
- 10
- Primary Topic
- Force Microscopy Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 3.38
Funders
- U.S. Department of Energy
- Ministry of Education, Culture, Sports, Science and Technology
- Office of Science
- Basic Energy Sciences