Published:
At Heriot-Watt University, we are pioneering ground-breaking artificial intelligence techniques that could revolutionise carbon capture and storage (CCS) technologies and collectively propel us toward a net-zero future.
Our new multimillion-pound ECO-AI research project, led by our net-zero focused global research institute iNetZ+, has achieved a remarkable feat - slashing the time required for modelling CCS methods from 100 days down to just 24 hours using advanced AI simulators.
This unprecedented acceleration opens up new possibilities for making CCS a viable economic option, enabling traditional industries like steel, cement, and chemicals to decarbonise efficiently.
The ECO-AI approach
Funded by £2.5 million from UK Research and Innovation (UKRI), the ECO-AI project, in partnership with colleagues from Imperial College London, brings together an interdisciplinary team of experts from chemical engineering, physics, geology, mathematics, computer science, and economics.
Their mission? To develop energy-efficient solvents for CO2 capture and facilitate the permanent storage of captured CO2 in deep geological formations through cutting-edge AI techniques.
By harnessing the power of AI, our researchers can replace standard techniques for modelling complex processes. Tasks that would typically require more than three months of intense supercomputer simulations can now be achieved in just a day.
This game-changing capability not only accelerates research progress but also drastically reduces the associated time and costs, making CCS more accessible and scalable.
Collaborative Innovation
To strengthen our research efforts, we recently hosted a two-day workshop and three-day hackathon event, bringing together leading experts in AI, computational science, and CCS.
The workshop highlighted the vital role of interdisciplinary collaboration and explored the use of digital twins for decision-making around net-zero emissions, as well as the incorporation of simplified models into large-scale optimisation replicas for complex systems.
The hackathon provided a hands-on opportunity for teams to develop AI-based solutions for challenges related to CO2 capture, storage, and policy/economics. With access to tools, data, and expert support, participants tackled tasks like discovering new materials, modelling subsurface fluid flow, and analysing patterns in CCS patents.
The enthusiasm and ingenuity displayed during these events were truly inspiring, as students and postdocs coded and worked on developing AI models that could reshape how we approach CCS technologies.
A profound impact
As Professor Ahmed H. Elsheikh, leader of the data and artificial intelligence research theme at iNetZ+, said: "Our efforts for the ECO-AI research are primarily focused on refining algorithms that can potentially be applied to CCS in the future in typically hard-to-decarbonise industries.
“Our research has the ability to really advance existing scientific research streams to source suitable options for safe storage of CO2 without consuming too much energy and without the need to deploy expensive and often time-consuming exploratory investigations."
Professor Clare McCabe, co-leader of the project's carbon capture component, echoes this sentiment, saying: "The optimism and energy in the hackathon, where students and postdocs coded for several days working on various AI models related to the ECO-AI project, was truly impressive."
Professor Gill Murray, Deputy Principal for Enterprise and Business at Heriot-Watt University, emphasised: "Using our new global research institute iNetZ+ as a vehicle to impact global solutions towards decarbonisation, we're pioneering ground-breaking methods in all major sectors that can propel us toward a net-zero future."
She highlighted the importance of integrating research-informed teaching to "shape the next generation of leaders and engineers," fostering "a dynamic environment where we can cultivate a culture of innovation and excellence."
The ECO-AI project exemplifies the university’s commitment to innovate for the future and beyond, harnessing the power of artificial intelligence to address the global climate crisis and accelerate the transition to a sustainable, carbon-neutral world.
For more information about the ECO-AI project, please visit https://ai4netzero.github.io/eco-ai/
More information on iNetz+ can be found https://www.hw.ac.uk/uk/research/inetzplus.htm