Work

Scientific exploration with expert knowledge (SEEK) in autonomous scanning probe microscopy with active learning

Year: 2024

Type: article

Abstract: 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.

Source: Digital Discovery

DOI: 10.1039/d4dd00277f

Authors: Utkarsh Pratiush, Hiroshi Funakubo, Rama Vasudevan, Sergei V. Kalinin, Yongtao Liu

Institutions: University of Tennessee at Knoxville, Tokyo Institute of Technology, Oak Ridge National Laboratory, Center for Nanophase Materials Sciences, Pacific Northwest National Laboratory

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: diamond

Funders: U.S. Department of Energy, Ministry of Education, Culture, Sports, Science and Technology, Office of Science, Basic Energy Sciences

Awards: G2451401391, G5005311294

OpenAlex ID: W4405002930

FWCI: 1.796

Cites: 65

Cited by: 19

Related to: 10