Descriptor-Driven Operando Spectroscopy as A Predictive Framework for Heterogeneous Catalysis

Abstract:

This talk explores how density functional theory combined with operando spectroscopy can describe the nature of active sites and reaction intermediates in heterogeneous catalytic systems. Drawing on examples from chemical feedstock manufacturing, air pollution remediation, and energy conversion, I will demonstrate how ambient pressure X-ray photoelectron spectroscopy and diffuse reflectance infrared spectroscopy can track surface species and reaction products under realistic conditions, while microkinetic models can resolve precise adsorption configurations. Together, these tools provide a predictive framework for designing highly selective catalysts.

The integration of machine-learning models has accelerated this process, albeit with a potential loss of physical interpretability. I will discuss emerging strategies for embedding physics-based insights with machine learning workflows for human-guided AI-driven catalyst discovery without sacrificing mechanistic insight.

Speaker bio:

Dr. Karthik Akkiraju is an Assistant Professor in the Department of Materials Engineering at the University of British Columbia. His research bridges materials engineering, computational social science, and public policy, utilizing both experimental and computational methods to understand how materials shape human well-being. An overarching theme is to develop a material design framework that delineates material requirements for a good life within equitable environmental and societal bounds. Karthik holds a Ph.D. in Materials Science and Engineering from the Massachusetts Institute of Technology.