Towards Sustainable Energy: Enhancing Thermochemical Energy Storage with Deep Learning and Multiscale Modeling

About This Grant

Energy storage technologies are critical for advancing renewable energy integration and ensuring a stable energy supply for large-scale applications such as industrial processes and solar power generation. Among these technologies, thermochemical energy storage systems, which store and release heat through reversible chemical reactions, offer significant potential due to their high energy density and long-term storage capabilities. This project focuses on improving the efficiency and reliability of calcium-based thermochemical systems, which are pivotal for sustainable energy practices. By enhancing the understanding of particle behavior and system dynamics, this project aims to overcome current limitations, such as low thermal conductivity and particle agglomeration. The results of the research will benefit the energy sector and the broader economy. The broader impacts include advancing energy sustainability, reducing carbon emissions, and fostering education and outreach initiatives. This research seeks to develop a comprehensive multiscale understanding of thermochemical energy storage systems through small-scale computational simulations and large-scale experimental validation. Using advanced molecular dynamics and machine learning techniques, the project will explore particle configurations and reaction dynamics at the micro-level. These simulations will be complemented by macroscopic experiments designed to ensure homogeneity and practical relevance. By integrating these methodologies, the project will validate and refine a physics-informed neural operator model, bridging the gap between atomistic and macroscopic scales. The outcomes will provide critical insights into system optimization, inform scalable design strategies, and establish a framework for addressing challenges in related energy technologies. This effort is expected to have a lasting impact on energy storage innovation, environmental sustainability, and STEM education. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.