Closed: NRC-University of Toronto Collaboration Centre for Green Energy Materials

To help fight climate change, new technologies are needed to reduce carbon dioxide (CO₂) emissions. One promising method is capturing CO₂ from the air or industrial sources using an electrochemical process that works at room temperature and normal pressure. This method depends on special redox molecules that help absorb and release CO₂. Designing stable and efficient redox molecules is key to making this process practical and affordable. Research teams at the University of Toronto and the National Research Council of Canada, led by co-Principal Investigators Dr. Dwight Seferos and Dr. Sharon Chen, have developed a new set of redox molecules that improve energy efficiency of CO₂ capture processes under everyday conditions. This work supports Canada's climate goals and brings us closer to cleaner, low-carbon industrial solutions.

Developing new materials essential for clean energy technologies can be slow, costly and risky. To speed this up, research teams at the University of Toronto and the National Research Council of Canada, led by co-Principal Investigators Dr. Jason Hattrick-Simpers and Dr. Alex Whittingham, developed material accelerated platforms (MAPs). These combined automation, high-throughput materials synthesis and testing, and artificial intelligence (AI) to quickly find optimal materials. The team focused on high entropy oxides, known for their strong performance in harsh conditions, making them ideal candidates for catalysts for the oxygen evolution reaction—key to hydrogen production. The team built a high-throughput screening system to hasten their search for the most promising catalyst compositions among the tens of thousands of possibilities. Using AI tools like auto electrochemical impedance spectroscopy (AutoEIS), the platform analyzes how materials behave and guides smarter compositional design. This user-friendly platform supports faster clean energy innovation and helps advance Canada's hydrogen and materials research.

Research teams at the University of Toronto and the National Research Council of Canada, led by co-Principal Investigators Dr. Chris Lawson and Dr. Boris Tartakovsky, developed an innovative, cost-effective way to turn carbon dioxide (CO₂) into valuable chemicals using a process called microbial electrosynthesis. By combining electricity, specialized microbes, and a 3D-printed material, the team has created a system that efficiently converts CO₂ into medium-chain carboxylic acids—chemicals used in products like plastics and fuels. They have developed a robust community of useful microbes, boosting CO₂ conversion rates by 3 times and achieving over 95% CO₂ conversion efficiency. They have then designed a new kind of biorefinery that transforms carbon emissions into useful, sustainable materials—supporting Canada's efforts to reduce pollution and grow a greener economy.

Hydrogen is a promising clean energy source, and making its production more efficient is important. One way to produce hydrogen is through water electrolysis, which relies on a key part called the catalyst layer. This layer is made of mixed materials that can wear down over time, reducing performance. Research teams at the University of Toronto and the National Research Council of Canada, led by co-Principal Investigators Dr. Aimy Bazylak and Dr. Khalid Fatih, used advanced imaging tools to study how this layer changes during use. By closely examining its tiny structures, they could see how the materials behave and break down. This knowledge will help improve the design of more durable systems, making hydrogen production more reliable and affordable for clean energy.

As Canada works toward a net-zero future, capturing carbon pollution will remain essential for decades—even as we shift to cleaner energy. One promising solution is metal organic frameworks (MOFs), sponge-like materials that can trap carbon dioxide (CO₂) from the air. However, MOFs often accidentally absorb other gases like nitrogen or water, which can get in the way of what they are actually supposed to do. To solve this, research teams at the University of Toronto and the National Research Council of Canada, led by co-Principal Investigators Dr. Chandra Singh and Dr. Ali Asgarian, have developed an advanced AI-powered simulation to predict which MOFs work best at selectively capturing CO₂. Their system quickly screens thousands of materials and has already identified several strong candidates now being tested in labs. This innovative research speeds up the discovery of materials for next-generation carbon capture technologies—helping Canada fight climate change and meet its 2050 emissions goals.