The proposal titled “New Frontiers for Material Modeling via Machine Learning Techniques with Quantum Monte Carlo” was awarded a 2019 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) grant by the U.S. Department of Energy’s Office of Science. The project lead by Dario Alfè and in collaboration with Gábor Csányi in Cambridge involves Angelos, Andrea and Gerit, who will have access to 1.25 million node-hours on some of the most powerful U.S. supercomputers. These resources are required to perform computationally very demanding quantum Monte Carlo simulations to provide highly accurate reference data for the adsorption of water on graphene, which will be used to build a machine learning potential. The importance of this work is stressed by being presented as one of six allocation highlights in the INCITE award announcement. You can find out more about the projects here.