Creating new technologies to reduce carbon emissions, slow climate change
CME professors Thomas Theis and Santanu Chaudhuri are contributing to an initiative to create new technologies that reduce carbon emissions and slow climate change.
The research is supported by the U.S. Department of Energy’s Energy Earthshots Initiative, a funding program geared toward driving breakthroughs in clean energy, next-generation batteries, and decarbonization. The researchers plan to develop new materials for carbon capture and hydrogen transportation and new processes for cleaner steel production.
“The principal objectives are to study the properties of novel molecular structures such as covalent organic frameworks (COFs) to, among other things, concentrate and store hydrogen, which is a ‘clean’ fuel and chemical feedstock, and carbon dioxide, which is a greenhouse gas and also a possible chemical feedstock,” Theis said.
Chaudhuri and his team have been creating the computational and artificial intelligence backbone for designing and deploying such materials.
“There are billions of possibilities to search for porous organic frameworks for making carbon capture from air possible. Electrochemical carbon capture in such systems can be highly efficient if we can find stable and scalable systems,” said Chaudhuri, who is the director of the Multiscale Materials and Manufacturing Lab. “Generative AI can predict improved carbon capture capabilities by morphing the molecular backbones. In collaboration with Argonne National Laboratory, my students recently developed a way to use supercomputers and physics-informed AI to make the search of efficient carbon capture in metal-organic frameworks faster than currently possible.”
The team is extending this approach to a new class of electrochemically active porous frameworks in the newly funded project. They will work closely with synthesis teams at UIC and the University of Nebraska to design novel pathways to address the complex challenge of making such electrochemically active materials from relatively abundant molecular precursors.
“It is like solving a multidimensional jigsaw puzzle where pieces can come together in many different ways,” Chaudhuri said. “Using the power of generative AI and quantum molecular dynamics simulations in sorting through the chemical reactions pathways to design the shortest, fastest, or cheapest routes will be a major breakthrough over a purely laboratory-based effort.”
A part of the research is thinking long term and avoiding the past mistakes of other researchers where the potential environmental impacts of projects were not addressed until much later when it was either too late or too expensive to correct.
“We propose embedding life cycle thinking into the research from initial conceptual and laboratory stages,” Theis said. “For example, we will rank the synthesis methods, energy use, precursor performance, and their operational life and end-of-life impacts on the environment to ensure that by the time the technology is ready for scaleup, the system will meet objectives while minimizing environmental impacts.”