报告题目：Learning from data: 3D Imaging of vortices in ferroelectrics and role of data science
报告人：Turab Lookman（Los Alamos National Laboratory ）
There has been much interest in topological defects of spontaneous polarization as templates for unique physical phenomena and in the design of electronic devices. Experimental investigations of the complex topologies of polarization in ferrous have been limited to surface phenomena, which has restricted the probing of the dynamic volumetric domain morphology in operando. Utilizing Bragg coherent diffractive imaging of a single BaTiO3 nanoparticle of size ~100 nm in a composite polymer/ferroelectric capacitor, I will discuss the behavior of a three-dimensional vortex formed due to competing interactions involving ferroelectric domains. The structural phase transitions under the influence of an external electric field shows a mobile vortex core exhibiting a reversible hysteretic transformation path. We also study the toroidal moment of the vortex under the action of the field and perform simulations to predict how the toroidal moment is accompanied by a structural transformation under the influence of the field. Our results open avenues for the study of the structure and evolution of polar vortices and other topological structures in operando in functional materials under cross field configurations. To make contact with data science, I will show how a classifier may be built that can be used at beam lines to rapidly distill diffraction images most likely to contain vortices and topological objects.
Dr Turab Lookman is a LANL Laboratory Fellow (2018), Fellow of the American Physical Society (2012), and recipient of the Japan Society for the Promotion of Science (JSPS) award in 2010 and the LANL Fellows prize for Outstanding Research in Science or Engineering in 2009. He has been the focus lead for Theory, Modeling and Computation for the proposed MaRIE (Matter Radiation in Extremes) XFEL signature facility concept at LANL. He has led an LDRD-DR effort at LANL on Materials Informatics and was Computational Materials lead for ExMatEx, the LANL-LLNL codesign effort for materials under extreme conditions. His interests span the study of hard and soft functional materials and aspects of applied mathematics and computation.