Speaker: Sergei V. Kalinin, Oak Ridge, TN

Speaker:  Sergei V. Kalinin, A Material Opportunity: How Microscopy and Autonomous Experimentation Can Accelerate Materials Design

Affiliation:  The Center for Nanophase Materials Sciences, Oak Ridge National Laboratories, Oak Ridge, TN

A Material Opportunity: How Microscopy and Autonomous Experimentation Can Accelerate Materials Design

Materials discovery, optimization, and design is one of the major challenges facing civilization in the XXI century. This problem is equivalent to search in the extremely high dimensional chemical space, the task for which the machine learning and artificial intelligence methods are uniquely suited. However, unlike typical ML problems, this space is essentially non-differentiable, the cost functions are not always accessible due to lack of forward theories, and practically we seek outliers more then average behaviors. Hence, the potential of the classical correlative machine learning tools is limited. It can be argued that the presence of parsimonious physical mechanisms can allow effective navigation and extrapolation in chemical space. In this talk, I will present the new opportunities enabled by physics-informed big data and machine learning technologies to extract physical information from static and dynamic STEM images. I will further illustrate how this data can be used to develop correlative models for solid structures on the atomic level, and further elucidate generative physics. These approaches allow to recover effective pairwise and many body interactions directly from imaging data. Synergy of deep learning image analytics and real-time feedback further allows harnessing beam-induced atomic and bond dynamics to enable direct atom-by-atom fabrication. Examples of direct atomic motion over mesoscopic distances, engineered doping at selected lattice site, and assembly of multiatomic structures will be demonstrated. Finally, I will share initial results on implementation of image-based feedback on SPM and STEM platforms, opening the pathway for automated experimentation with microscopy. These advances position STEM and SPM towards transition from purely imaging tool for atomic-scale laboratory of electronic, phonon, and quantum phenomena in mesoscale and atomically-engineered structures.

Biography

Sergei Kalinin is the director of the Institute for Functional Imaging of Materials (IFIM) and distinguished staff member at the Center for Nanophase Materials Sciences at Oak Ridge National Laboratory. He received his MS degree from Moscow State University in 1998 and Ph.D. from the University of Pennsylvania (with Dawn Bonnell) in 2002.

His research presently focuses on the applications of big data and artificial intelligence methods in atomically resolved imaging by scanning transmission electron microscopy and scanning probes, as well as mesoscopic studies of electromechanical and transport phenomena via scanning probe microscopy.

Sergei has co-authored >600 publications, with a total citation of >30,000 and an h-index of >85. He is a fellow of MRS, APS, IoP, IEEE, Foresight Institute, and AVS; a recipient of the RMS medal for Scanning Probe Microscopy (2015); Blavatnik Award for Physical Sciences (2018), Presidential Early Career Award for Scientists and Engineers (PECASE) (2009); Burton medal of Microscopy Society of America (2010); 4 R&D100 Awards (2008, 2010, 2016, and 2018); and a number of other distinctions.