Researchers have developed a tool which could accelerate the discovery of top-performing materials for carbon capture, beating traditional trial-and-error methods.
One of the biggest challenges society faces is to bridging the gap between fundamental scientific research and its successfully to real world problems.
This gap – the so-called ‘the valley of death’ for new technologies - is common in the field of carbon capture.
Carbon capture researchers explore new materials which could be used to remove carbon dioxide from the flue gasses produced by industrial processes. Capturing this carbon dioxide can help to mitigate the effects of climate change.
The European Commission has identified carbon capture, utilisation and storage (CCUS) as one of eight strategic net-zero technologies that will be critical in helping the EU reach its climate goals. While momentum on CCUS has increased in recent years, the deployment of projects has remained relatively flat, according to a report from the International Energy Agency last year.
Chemists have proposed thousands of novel materials for carbon capture, but even when results look exciting in the lab it’s hard to know what that means for real-world performance. This makes it far less likely that any will ever cross the valley of death.
To compound the problem, while chemists design materials and engineers develop processes, economic and environmental impacts are factored in later, further delaying the implementation of carbon capture processes.
Now an international team of scientists has developed a tool which can identify the most effective options and predict the performance of new materials.
The Process-Informed design of tailor-made Sorbent Materials (PrISMa) tool uses simulations and machine learning to find the most cost-effective and sustainable combinations.
“Chemists have proposed thousands of novel porous materials, but we did not have the tools to quickly evaluate if any materials are promising for a carbon capture process. Evaluating such materials requires a lot of experimental data and detailed knowledge of the capture process,” said Professor Susana Garcia from Heriot-Watt University in Edinburgh, who led the study and is the project coordinator for PrISMa.
Garcia said that chemists can’t be expected to have all that knowledge, which is where the PrISMa tool can make a difference, by integrating different aspects of carbon capture, including materials, process design, economic analysis, and life cycle assessment.
“We use quantum chemistry, molecular simulation, and machine learning to predict, for new materials, all the data that is needed to design a process. Alternatively, we can use the experimental data from materials synthesised in a lab. The platform then evaluated their performance in over 60 different case studies from around the world,” she said.
The aim is to accelerate the discovery of top-performing materials for carbon capture, and outperform traditional trial-and-error methods. PrISMa has been used to accurately simulate the implementation of carbon capture technologies in cement plants. It found suitable materials for each location, cutting costs by half when compared with previous technologies.
Screening large numbers of materials requires large amounts of computational time and the team developed a machine learning model to “significantly” accelerate this process.
PrISMa has been led by Heriot-Watt University in partnership with scientists from the Swiss Federal Institute of Technology Lausanne and ETH Zurich, Lawrence Berkeley National Laboratory and the University of California Berkeley, and the Institut des Matériaux Poreux de Paris in France.
SCI is part of the Flue2Chem project, along with Unilever and 13 other partners, which has the aim of developing a new value chain to convert industrial waste gases into sustainable materials for consumer products.
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