AI used to cut time and cost of carbon capture and storage design

Dubbed ECO-AI, the research team has begun the development of specialist AI techniques for scientific computing, material discovery and financial forecasting, to enable efficient CO2 capture and storage in deep geological formations and to reduce the cost of deploying these techniques.

The Heriot-Watt team, with colleagues from Imperial College London, aims to show how bespoke technologies can enable CCS to be a viable economic option for traditional industries wanting to decarbonise. Targets include hard to decarbonise industries such as steel, cement and chemicals.

Funded by £2.5m from UK Research and Innovation, the ECO-AI project will specifically develop energy-efficient solvents for CO2 capture followed by permanent storage of captured CO2 into geological storage sites, through various AI techniques.

The research is one of the projects being delivered by Heriot-Watt University’s global research institute which is focused on achieving net zero and beyond. Called iNetZ+, the team brings together a range of scientific expertise including chemical engineering, physics, geology, mathematics, computer science and economics.