Special Physical Chemistry Seminar: Searching for a method in the madness of disordered materials
Prof. Yelena Simine, Department of Chemistry, McGill University, Canada
Abstract:
In this talk I will present a new generative machine learning protocol for bridging the nano- and meso-scale simulations of amorphous materials called the Morphological Autoregressive Protocol (MAP). I will make the case for the physicality of the generated structures, present its application in a case study of electronic properties of amorphous graphene in 2D, and discuss the extension to multi-elemental 3D simulations. To conclude the talk I will switch to a different category of ‘disordered materials’ and discuss our approach to computational design of single stranded DNA electrochemical sensors by means of machine learning and traditional simulations using a computational pipeline E2EDNA.
Seminar Organizer: Dr. Barak Hirshberg
