Artificial intelligence is helping researchers upcycle waste carbon. A collaboration between University of Toronto Engineering and Carnegie Mellon University has produced a record-setting catalyst for CO2-to-ethylene conversion.
Researchers at University of Toronto Engineering and Carnegie Mellon University are using artificial intelligence (AI) to accelerate progress in transforming waste carbon into a commercially valuable product with record efficiency.
They leveraged AI to speed up the search for the key material in a new catalyst that converts carbon dioxide (CO2) into ethylene – a chemical precursor to a wide range of products, from plastics to dish detergent.
The resulting electrocatalyst is the most efficient in its class. If run using wind or solar power, the system also provides an efficient way to store electricity from these renewable but intermittent sources.
“Using clean electricity to convert CO2 into ethylene, which has a $60 billion global market, can improve the economics of both carbon capture and clean energy storage,” explained Professor Ted Sargent, one of the senior authors, in a statement.
Sargent and his team have already developed a number of world-leading catalysts to reduce the energy cost of the reaction that converts CO2 into ethylene and other carbon-based molecules. But even better ones may be out there. Using computer models and theoretical data, algorithms can toss out the worst options and point the way toward more promising candidates.
In the new paper, the co-authors describe their best-performing catalyst material, an alloy of copper and aluminum. After the two metals were bonded at a high temperature, some of the aluminum was then etched away, resulting in a nanoscale porous structure that Sargent describes as “fluffy.”
The new catalyst was then tested in a device called an electrolyzer, where the “faradaic efficiency” – the proportion of electrical current that goes into making the desired product – was measured at 80%, a new record for this reaction.
Lowering the energy cost
Sargent says the energy cost will need to be lowered still further if the system is to produce ethylene that is cost-competitive with that derived from fossil fuels. Future research will focus on reducing the overall voltage required for the reaction, as well as further reducing the proportion of side products, which are costly to separate.
The new catalyst is the first one for CO2-to-ethylene conversion to have been designed in part through the use of AI. Its strong performance validates the effectiveness of this strategy and bodes well for future collaborations of this nature.