Role of Computational Science in Materials and Systems Design for Sustainable Energy Applications: An Industry Perspective

Computational sciences have been utilized by scientist and engineers from various disciplines to provide solutions to real world problems, in fulfilling the energy demands as well as in designing chemicals, materials, and pharmaceutical drugs for daily use. Currently, greenhouse gas emission is one of the critical problems contributing to the health and environmental effects on our society, where computational sciences through material discovery and iefficient system design have been helping in early adoption of sustainable technologies. In this article, we present some of these works specific to hydrogen and carbon technologies, where atomistic and multi-scale continuum approaches, along with physics-informed machine-learning methods, have enabled new materials discovery and novel systems design that could lead to commercially viable sustainable technologies with reduced or zero emissions. Examples include but not limited to the use of reduced-order multiscale modeling in developing novel reactor configuration for chemicals manufacturing with renewable power, design and scale up of carbon-capture systems, use of computational fluid dynamics in designing cheaper and more efficient battery coolants for energy storage in electric vehicles; use of atomistic modeling in developing electrocatalysts for water splitting and enabling better design of electrolyzers and CO_2 sequestration systems. Specifically, we describe the importance of computational sciences in better understanding and optimal design for sustainable energy systems towards achieving zero-emission goals.