April 11, 2024
Staff Accomplishment

Kalinin Receives Microanalysis Society Award

Sergei Kalinin earned the Peter Duncumb Award for excellence in microanalysis

Sergei Kalinin

Sergei Kalinin, who is the Weston Fulton Professor at the University of Tennessee-Knoxville and joint appointee at Pacific Northwest National Laboratory, recently received the Peter Duncumb Award from the Microanalysis Society.

(Image courtesy of Sergei Kalinin | Pacific Northwest National Laboratory)

The Microanalysis Society (MAS) announced Pacific Northwest National Laboratory (PNNL) joint appointee Sergei Kalinin as the 2024 recipient of the Peter Duncumb Award for excellence in microanalysis. Kalinin, who is the Weston Fulton Professor at the University of Tennessee-Knoxville, was recognized for his technical accomplishment, leadership, and educational and professional activities in the field of microanalysis.

“Sergei is a world-leading expert in machine learning-driven experimentation,” said Elke Arenholz, director of the Physical Sciences Division at PNNL. “Sergei's research focuses on applications of machine learning and artificial intelligence in nanotechnology and materials discovery using electron and scanning probe microscopy. I am glad Sergei joined PNNL as a joint appointee and collaborates with scientists across the lab.”

Kalinin and Arenholz worked together prior to joining PNNL as well. They both worked at Oak Ridge National Laboratory, where Kalinin built physics-based programs to extract information from large volumes of microscopy data and automated scanning transmission electron microscopy and scanning probe microscopy. As computing techniques advanced, Kalinin began incorporating physics-informed machine learning methods into his research. Now, Kalinin aims to make autonomous microscope systems with machine learning as a key component of the materials and physics discovery process, rather than “just imaging” techniques.

“Machine learning in the experimental context is difficult,” said Kalinin. “There are so many parameters to consider—the information one researcher wants to get out of an experiment may be completely different from another researcher using the exact same equipment.”

Kalinin came to PNNL to overcome this challenge. He is now a chief scientist in artificial intelligence/machine learning for physical sciences at PNNL.

“PNNL allows researchers to follow experiments that can change the fundamental way we view, and most importantly make, things,” said Kalinin. “We are pursuing projects that have the potential to transform how scientists investigate problems in materials science and chemistry.”

At PNNL, Kalinin works closely with Arenholz to identify research opportunities that combine physical sciences with machine learning.

Kalinin received his MS from Moscow State University and a PhD in materials science and engineering from the University of Pennsylvania. Following his PhD, Kalinin worked at Oak Ridge National Laboratory, where he was the director of the Institute for Functional Imaging of Materials from 2014 to 2019 and a group leader at the Center for Nanophase Materials Sciences from 2020 to 2022. He spent a year at Amazon in the Moonshot division as a principal scientist before joining the University of Tennessee-Knoxville as the Weston Fulton Professor.

Kalinin has received multiple awards for his work, including the Medard Welch Award in 2023, Feynman Prize of the Foresight Institute in 2022, the Blavatnik Award for Physical Sciences in 2018, a Royal Microscopy Society medal for Scanning Probe Microscopy in 2015, and a Presidential Early Career Award for Scientists and Engineers in 2009. Kalinin has also been elected as a fellow in many prestigious scientific societies, including the Materials Research Society, the American Physical Society, the Microscopy Society of America, the Institute of Physics, the Institute of Electrical and Electronics Engineers, the Foresight Institute, and the American Vacuum Society.