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IACS Seminar: Anatoly Frenkel

Inverting the Structure-Spectrum Relationship in Nanoparticles by Supervised Machine Learning Tracking the structure of nanocatalysts (and other functional nanomaterials) under operating conditions is a challenge due to the paucity of experimental techniques that can provide atomic-level information for active metal species. Here we report on the use of X-ray absorption spectroscopy (XAS) and supervised machine learning for determining the three-dimensional geometry of metal catalysts at the nanometer size scale. Artificial neural network is used to unravel the hidden relationship between the XAS features and catalyst geometry. In other words, we trained computer to learn how to ‘invert” the unknown spectrum and obtain the underlying structural descriptors. This method is demonstrated by reconstructing the average size, shape and morphology of nanoparticles with narrow size and composition distributions from the coordination numbers and interatomic distances obtained using the SML approach. First applications of this method to the determination of nanomaterial structure in operando conditions, such as studies of synthesis, nucleation, growth and reactivity of metal catalysts will be demonstrated. Bio: Anatoly Frenkel is a Professor in the Department of Materials Science and Chemical Engineering at the Stony Brook University and a Senior Chemist (Joint Appointment) at the Division of Chemistry, Brookhaven National Laboratory, has joined in the Fall of 2016. Prior to his appointment at SBU, he has held a number of different positions, including Associate and then appointed Full Professor and Chair, Physics Department at Yeshiva University, a Research Scientist and Principal Investigator in Materials Research Laboratory of the University of Illinois at Urbana-Champaign. He received M.Sc. degree from St. Petersburg University and Ph. D. degree from Tel Aviv University (with Prof. A. V. Voronel), all in Physics, followed by a postdoctoral appointment at the University of Washington (with Prof. E. A. Stern). His research interests focus on development and applications of in situ and operando ynchrotron methods to solve a wide range of materials problems, with most recent emphasis on catalysis, electromechanical materials, filtration materials, quantum dots, physico-chemical properties of nanoparticles, as well as machine learning methods for structural analysis and design of nanomaterials. He is a founding Principal Investigator and the Spokesperson for the Synchrotron Catalysis Consortium at Brookhaven National Laboratory. He is a Fellow of the American Physical Society and a Fellow of the Empire Innovation Program at the New York State. He is the author of over 300 peer-reviewed publications, which have been cited over 15,000 times, and has given over 250 invited lectures at conferences and university, government and corporate laboratories. This presentation was delivered on Feb. 9, 2019.