Predicting CCUS technology

IBM Research shows five ways in which CCUS technology developments are likely to shape up in the next five years. Sonia van Ballaert, IBM Distinguished Industry Leader, explains.

The landmark IEA Report Net zero by 2050* lays out daunting milestones for carbon capture, use and storage (CCUS) (see also pp14). Carbon dioxide (CO2 ) captured from fossil fuels and processes will need to multiply more than 30-fold over the next 10 years. Equally, CO2 captured from bioenergy and direct air capture (DAC) needs to account for 345mn tonnes of CO2 by 2030, starting from a base of one – a multiple of more than 300. These are huge numbers, both in terms of the availability of scalable technologies and of capital investments to achieve industry-wide deployment. From 2030 onwards, the IEA’s net zero pathway scenario suggests that each month the world should equip 10 heavy industry plants with CCUS.

However, one of the key uncertainties in the IEA report is the extent to which fossil fuel-based CCUS applications, which are needed to de-risk other CCUS applications, will actually be developed over the coming decade. ‘Without fossil fuel-based CCUS, the number of users and the volumes of the CO2 transport and storage infrastructure deployed around industrial clusters would be reduced. Fewer actors and more limited pools of capital would be available to incur the high upfront costs of infrastructure, as well as other risks associated with the initial roll-out of CCUS infrastructure clusters,’ says the report. ‘In addition, there would be less spill-over learning and cost-reduction benefits from developing fossil fuel-based CCUS, making the successful demonstration and scaleup of nascent CCUS technologies much less likely.’

While geological storage and re-use of CO2 in industrial processes will be needed at scale, increased technology innovation will also be required to unlock additional pockets of CCUS and further de-risk the road to net zero emissions. This is where IBM comes in.

5 in 5 predictions

Each year, IBM Research showcases five ways in which technology will reshape business and society in the next five years. This year’s ‘5 in 5’ predictions focus on accelerated materials discovery to enable a more sustainable future.

IBM predicts that within the next five years, new materials or novel uses of existing ones will help address the global climate challenge – efficiently capturing CO2 to mitigate emissions, finding more sustainable ways to grow crops, rethinking materials that go into batteries and developing more sustainable electronics.

Materials design is a lengthy, complex process because the number of potential molecular combinations is vast and the final properties of materials also depend on the production processes. It typically takes more than 10 years and many tens of million dollars to discover a useful new material. With the help of artificial intelligence (AI), high-performance and quantum computing, generative models and laboratory automation, the time and cost needed for materials discovery could be cut by 90%.

Accelerated materials discovery

To accelerate the discovery of CO2 -absorbing materials for carbon capture, IBM has created a cloud-based screening platform to rapidly sift through millions of potential CO2 adsorbents at the nanoparticle level. This should enable materials engineers to select the best materials for enhancing the absorption of CO2 in a particular application. The platform allows fast searches through large quantities of known structures, enabling faster discovery. Once the most viable candidates are identified, the computational framework can then inform chemical synthesis and material optimisation for accelerating the discovery in the lab.

So how does this work? The AI software can consolidate all available knowledge on a specific topic from a multitude of sources. Then supercomputers and, eventually, quantum simulations can cover knowledge gaps on – in this case – CO2-absorption. Using the full set of data, the AI can then create models to generate hypotheses about new materials with useful properties. What’s more, the manufacture and testing of new materials can also be automated.

IBM’s AI-based approach includes a cloud-powered chemistry lab, which allows researchers to create materials by predicting the outcome of chemical reactions.

IBM scientists are using this automated lab to synthesise materials for carbon capture. The IBM Research team has worked on the discovery of better polymer membranes to separate CO2 from flue gases. Using molecular generative AI modelling, they have identified hundreds of molecular structures that could offer alternatives to existing separation membranes for capturing CO2 from industrial processes. These candidate molecules are then evaluated with the help of automated simulations on high-performance computing clusters.

Simulating carbon separation and conversion

Safely and effectively storing CO2 into geological formations is also a huge challenge. The physics and chemistry of the process at a reservoir rock’s pore scale is not well understood. Furthermore, the efficiency of CO2 conversion and storage also depends on the type of rock and reservoir conditions.

To tackle the issue, IBM has created a cloud-based tool that simulates fluid flow of CO2 in specific types of rock, allowing scientists to evaluate CO2 trapping and conversion scenarios at pore scale. The technology can enable rapid analysis and optimisation of the rock-specific requirements for mineralising and storing CO2 efficiently and long-term.

In these projects, IBM Research combines AI, highperformance computing and cloud technologies to speed up the discovery of new materials. Innovative CCUS materials and approaches are needed in widely different industries such as energy, agriculture and electronics. IBM's 5 in 5 predictions bode well for their accelerated discovery.

*See www.bit.ly/IEANetZero

See also www.bit.ly/IBMCCS