Yongtao Liu, a researcher at the U.S. Department of Energy’s Oak Ridge National Laboratory, has been honored by the Royal Microscopical Society (RMS) and the Materials Research Society (MRS) for contributions to AI-enabled autonomous microscopy and materials research. Liu is an R&D staff member at the Center for Nanophase Materials Sciences (CNMS), a DOE Office of Science national user facility at ORNL.
Atomic force microscopy (AFM) allows researchers to study materials at extremely small scales, but traditional experiments often require researchers to interpret complex data and manually decide where and how to measure next. Liu’s work uses artificial intelligence to recognize subtle patterns in microscopy data and guide measurements automatically, allowing experimental systems to adapt to incoming data and accelerate nanoscale discovery.
Royal Microscopical Society recognition
The RMS Atomic Force Microscopy & Scanning Probe Microscopy Award is presented annually to one researcher for outstanding contributions to AFM and scanning probe microscopy.
In addition to honoring Liu for his role advancing AI approaches in AFM, the RMS recognized him for introducing new experimental paradigms to support dynamic measurement parameters in AFM experiments, and for his leadership within the international research community.
Liu’s publications are widely cited and have become reference points for other researchers developing advanced AFM techniques. Furthermore, he has given many invited presentations, including keynote talks at major international conferences and institutions.
Materials Research Society recognition
At the 2026 MRS Spring Meeting, Liu was recognized as an Early Career Distinguished Presenter for his contributions to self-driving laboratories and AI for materials science.
He also served as a lead organizer of the five-day MRS symposium on AI and human expertise for data-efficient autonomous materials research. The symposium drew broad participation and overflow attendance.
For Liu, the strong turnout showed that the symposium organizers had identified a timely research priority with growing importance well in advance. Since MRS symposium topics are selected well ahead of the meeting, the strong engagement highlighted how quickly interest in the field has expanded. The topic grew out of CNMS research in data-efficient AI, autonomous experiments and human-AI collaboration.
Looking ahead, Liu expects autonomous microscopy to become part of interconnected research networks, where instruments, facilities and theory work together to tackle increasingly complex materials challenges.
UT-Battelle manages ORNL for the Department of Energy’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. The Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science. – Galen Fader
