Advanced Catalyst Discovery for Clean Energy Transformation Using Computational Material Design

Synopsis

The adoption of sustainable energy sources is crucial for reducing the escalating levels of CO 2 in the atmosphere. To address this issue, renewable energy technologies such as fuel cells and metal-air batteries are poised to play a significant role. In addition, electrolysis cells can help overcome the challenge of producing valuable compounds such as fuels, hydrogen, and ammonia from low-value chemicals like CO_2, H_2O, and N_2. Nevertheless, the lack of efficient catalyst materials poses a significant barrier to the widespread adoption and economic viability of these technologies.

Addressing this challenge requires innovative approaches, and one such avenue is computational catalyst material design and development. By leveraging tools such as density functional theory (DFT), we can develop the atomic scale understanding of surface reactivity, paving the way for the discovery of highly efficient catalyst materials. This approach holds immense potential for catalyzing global efforts towards clean energy.

In this seminar, I will present our recent research endeavors on understanding the atomic-scale properties of existing catalysts using quantum mechanical calculations. By examining their frontiers in various key reactions integral to clean energy processes, we aim to contribute to the advancement of sustainable energy technologies. With various examples, I will show how computational techniques can effectively capture catalytic reactivity across diverse chemical
space. This approach holds the promise of discovering novel catalyst materials crucial for propelling the shift towards a greener and more sustainable future.