Energy research is by far the fastest growing segment of Carnegie Mellon Chemical Engineering’s research portfolio. Researchers from across all other areas in the department are applying their unique expertise to the major energy problems facing our world today. From the optimization of existing energy sources like oil and natural gas, to the development and production of renewable energy systems like wind and solar, energy researchers in the department of chemical engineering are paving the way for the necessary changes that will bring us all to a more sustainable and energy efficient future.

Though the energy and biofuels research in the department covers a wide spectrum of topic areas, many of the current projects focus on three main areas:

Carbon capture and sequestration – The process of removing and containing carbon emissions from human-made sources remains a viable option for reducing the negative effects of these emissions on the environment. Researchers in the department are working to understand and optimize the process holistically—using mathematical models to study the interplay of pollutant emissions and atmospheric particles, and identifying cost-effective emission controls to reduce the subsequent damages. Additionally, researchers are interested in the many ways that this captured carbon can be used to make valuable products, though processes known as carbon utilization.

Fuel cells – The development of fuel cell technology focuses primarily on the discovery and development of new catalysts and materials to aid in hydrogen production. These materials are being discovered and optimized here every day through the use of novel machine learning methods, study of surface chemistry and physics, and more.

Energy transitions – Natural gas currently serves as a bridge fuel that helps ease the transition between traditional coal power generation and less reliable but more sustainable energy sources like wind and solar. Researchers in the department are not only working to develop new power storage technologies to aid future renewables implementation, but also developing complex optimization algorithms to plan the cost-effective, long term solutions for power generation source combinations for a given region.

Catalysis discovery through machine learning

The discovery of new catalysts allows researchers to create and perfect new materials, which can be used in future products, fuels, and just about everything else. Unfortunately, discovering and optimizing these new catalysts can be a long and difficult process, involving an unruly number of variables. But Carnegie Mellon is at the forefront of research into the role that machine learning can play in the discovery of new catalysts. Through the use of high-performance computing and molecular simulations, and the development and implementation of novel machine learning algorithms, the rate at which researchers can discover new, effective catalysts, as well as understand and design new materials, will increase exponentially.

Students from all over the world come to the department of Chemical Engineering to study this exciting, emerging field. Both the Department of Energy and the National Science Foundation have invested in the unique research that Zachary Ulissi, John Kitchin, and Andrew Gellman are pioneering, which looks at new ways that machine learning can facilitate faster catalysis discovery and optimization. Additionally, Gellman and Ulissi have received an ARPA-E grant to study deep reinforcement learning in catalysis. ChemE faculty, students, and partner organizations are poised to bring unprecedented change to the field of catalysis discovery.

Related news