A machine learning method, DOSnet, was used to extract key features from the electronic density of states and provide accurate predictions of adsorption energies for catalysis.
Significance and Impact
DOSnet provides an electronic latent space, which can be freely explored without additional ab initio calculations, greatly accelerating materials discovery and design.
Victor Fung, Guoxiang Hu, P. Ganesh, and Bobby G. Sumpter, “Machine Learned Features from Density of States for Accurate Adsorption Energy Prediction," Nature Communications (2021). DOI: 10.1038/s41467-020-20342-6