A team of researchers from the US and Canada have employed artificial intelligence (AI) to accelerate the process of transforming waste carbon into a commercially viable product.
The teams from Carnegie Mellon University in the US and the University of Toronto in Canada used AI to search for a key material in a new catalyst that will convert carbon dioxide (CO2) into ethylene, a key component in many products, such as detergent and plastics, according to Bio Market Insights.
“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,” said Professor Ted Sargent (ECE), one of the senior authors on a new paper published in Nature.
Professor Sargent and his team have been working on several catalysts to reduce energy costs in converting CO2 into ethylene and other products, but it is the sheer amount of viable and better catalysts and the millions of potential material combinations that make testing them all impossible.
Introducing AI and matching learning to the problem significantly speeds up the search. The AI uses computer models and theoretical data to generate the options, and discard the failed one, and help point the way towards more promising candidates.
The idea of using AI to search for clean energy materials was first put forward by Sargent and the Canadian Institute for Advanced Research (CIFAR) in 2017.
The new electrocatalyst for CO2-to-ethylene conversion is the first to have been designed with the help of AI and the first experimental demonstration of active machine learning.
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