AI enables quicker search for MOFs to soak up carbon dioxide

Two new studies have demonstrated the potential of machine learning to accelerate the discovery of metal–organic frameworks (MOFs) that could be useful for capturing carbon dioxide from ambient air. In the first, researchers in the UK and South Korea screened 8000 candidate MOFs and suggested some new candidates for direct air capture (DAC).¹ In the second, a preprint from the US, researchers at Meta and elsewhere released a machine-learning algorithm trained on 15,000 MOFs. ²