From Event Detection to Physical Hypothesis Learning via Automated and Autonomous Microscopy
Source abstract
Abstract
Electron and scanning probe microscopies are by now the mainstay of areas ranging from fundamental condensed matter physics and materials science to chemistry and biology. In many cases, these imaging methods provide quantitative or semiquantitative information on materials structure and functionalities and allow for the exploration of broad range of responses to global (temperature, chemistry) and local (beam exposure, probe bias and pressure) stimuli. However, the connection between microscopy imaging, spectral data, and specific mechanisms of physical and chemical phenomena often requires extensive studies including multiple human-driven stages.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Machine Learning in Materials Science · Advanced Electron Microscopy Techniques and Applications · Cell Image Analysis Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
University of Tennessee Department of Materials Science and Engineering, , Knoxville, TN, United States
Oak Ridge National Laboratory , Oak Ridge, TN, United States
References (2)
Show source-provided references
1. Ovchinnikov · Microsc. Microanal · 2010 · 1610.1017/S1431927610062720 ↗
2. Kalinin · ACS Nano · 2021 · 15 · 1260410.1021/acsnano.1c02104 ↗