(4y) Freedom: First-Principles Aided Reverse Engineered Design of Materials

Using the concept of reverse engineering with state-of-the-art computational methods, my research vision is to enable the in-silico discovery and design of materials that would help usher the sustainable energy future. Specifically, I’m interested in the discovery and design of catalysts, with a particular emphasis on heterogeneous catalysis, as well as materials for energy conversion and storage. This paradigm, dubbed “FREEDOM” for First-principles aided REverse Engineered Design Of Materials is built on integrating my unique expertise in first-principles methods, electronic structure analysis, solid-state physics and statistical mechanics, with machine learning and data science approaches, to enable the iterative improvement in the choice of material for a given application, through the process of deducing the key features responsible for making the current state-of-the-art work as well as it does. The three major components to achieve this, will involve: a) a reactivity (suitability) screening of idealized representations of the materials under consideration b) evaluating their performance under working conditions to provide a realistic in-silico representation and c) the prescription of a tailored synthesis protocol to achieve the desired performance.

My prior work involving the development of physics-based chemisorption models to predict reactivity, the use of ab-initio molecular dynamics and enhanced sampling methods to deduce the dissolution and dynamic evolution of electrocatalysts, and ab-initio thermodynamics-based design rules for synthesis methods, will form the bedrock of the research program. The overarching goal of the three tasks that make up the paradigm is to go beyond the conventional computational approach to materials design which largely involves simplified systems, and towards bridging the gap to realistic systems that would mutually benefit both the experimentalists, as well as the computational models, by leveraging the data generated from the experiments. My research program will therefore be at the cross-roads between fundamental and applied materials science, where identifying the best material for a given application will be the central theme, with fundamental physical insights gained through the revere engineering approach. This will enable close collaborations with experimentalists, particularly involving in-situ/operando characterization of electrocatalysts, electronic-structure measurements, and tailored synthesis methods. Further, students and postdoctoral researchers will gain multi-faceted expertise in the areas of first-principles methods, electronic structure analysis, statistical mechanics and machine learning, enabling the further progression of computational materials discovery and design.

Teaching Interests

My training and background render me with the ability to teach all undergraduate and introductory courses in Chemical engineering. At the more advanced level, I’m well suited to teach courses relevant to my area of research, such as thermodynamics and statistical mechanics, kinetics, physical chemistry, and computational methods in materials modeling. With the ever-increasing popularity of computational and data science approaches, I would also like to introduce a course that can be useful across several engineering disciplines, titled "Multi-scale Methods". The purpose of this course is to provide a one-stop shot at gaining beginner level proficiency across different methods spanning from first-principles to coarse-grained approaches, as well as hands-on-training with using relevant open-source software and computational methods for analyzing large data. My research expertise and proficiency in multi-scale modeling will be leveraged in designing this course, with the potential implementation of an ongoing research problem as a course project to also provide the students with a taste of computational research approaches. Further, one area of major deficiency in engineering doctoral programs is the absence of a "journal-club". I would like to develop a course specifically designed for doctoral candidates that encourages them to explore topics beyond their areas of research, through a weekly seminar involving the discussion of journal articles across different disciplines. The aim is that this would provide a well-rounded interdisciplinary understanding of science and engineering, that will be beneficial even beyond the doctoral program.