High-throughput computational screening of bioinspired dual atom alloys for CO2 activation

This is a large DFT dataset on screening materials (dual atom alloys in Cu 111 surface) for aptitude for binding CO and CO2, as well as their relative formation energy and relevant machine learning features. Methods This dataset was collected with atomic relaxations using density functional theory and processed with machine learning algorithms from SKLearn.