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High-quality curated materials property databases are valuable resources for a variety of applications, such as property prediction (e.g. machine learning methods) and material screening through sophisticated ab initio simulations, using them as a starting point. In my talk, I will present our efforts in creating a fully provenance-based crystal structure 3D materials database, which is derived from experimentally realizable compounds. I will discuss our approach, the tools that enable this effort as well as potential future extensions
Laboratory for Materials Simulations (LMS)