Cement pretty much holds the modern world together. The amount of cement required to create our infrastructure is almost incomprehensible. By weight, humanity consumes more cement than food, about 3 pounds per person per day. The cement industry produces around eight percent of global CO2 emissions, which is more than the aviation industry. So, if the amount of emissions produced making concrete could be reduced by even a few percent, it would make a significant impact.
Cement plants utilize rotary kilns heated to 2,500 degrees Fahrenheit to burn ground limestone down to a substance called clinker. That energy-intensive combustion process emits large amounts of carbon dioxide. However, the combustion process accounts for much less than half of the emissions associated with making concrete. The majority comes from the raw materials needed to produce clinker.
One strategy to reduce concrete emissions is to modify the cement recipe itself, replacing some of the clinker with alternative materials. Some producers already make use of materials like slag from iron production and fly ash from coal-fired power plants.
A team of researchers at the Paul Scherrer Institute in Switzerland is making use of machine learning to simulate and optimize cement formulations that would emit significantly less CO2 while maintaining the same high level of mechanical performance. This AI-based approach eliminates time-consuming experiments and conventional complex simulations.
The Scherrer Institute seeks to discover new materials and the effort has already yielded some promising candidates. The next steps will be testing some of these recipes in the laboratory.
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AI paves the way towards green cement
Photo, posted July 3, 2007, courtesy of Tim Shortt via Flickr.
Earth Wise is a production of WAMC Northeast Public Radio
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