Data sciences are now also entering theoretical catalysis and energy related research with full might. Automatized workflows and the training of machine learning approaches with first-principles data generate predictive-quality insight into elementary processes and process energetics at undreamed-of pace. Computational screening and data mining allows to explore these data bases for promising...
As an integral part of the FAIR-DI/FAIRmat initiatives, NOMAD is extending it's scope. NOMAD evolves from a central repository for publishing electronic structure codes data into a federated data management network that covers all branches of materials science. Instead of just using NOMAD to publish final results, we want to show how on-site installations of NOMAD can help to manage your local...
Transmission electron microscopy data is rich in quantitative information about materials, information that could in theory be coupled to atomistic simulations, but extracting and harnessing that information is non-trivial. Machine learning approaches may facilitate this, but these are hampered by the limited availability and interoperability of the data. In this talk we present approaches,...
