Research Data Infrastructure for Data-Driven Experimental Materials Science

Hight throughput experiments and the resulting materials databases can greatly accelerate the pace of data-driven discovery and design of new materials for energy generation, conversion and storage applications, by making data accessible to new and rapidly evolving data analysis methods. This experimental materials data need motivates the creation of research data infrastructure to aggregate valuable high throughput experimental materials data and make these data available through public databases, so to increase their usefulness for future data-driven materials research studies.<br/>This presentation will describe the Research Data Infrastructure for the High-Throughput Experimental Materials Science [1], to illustrate the best practices currently used for materials data management at National Renewable Energy Laboratory (NREL). The Research Data Infrastructure (RDI) is a set of custom data tools at NREL that collect, process, and store experimental data and metadata. This includes tools for data collection (Data Harvesters, and Laboratory Metadata Collector), data processing (Extract-Transform-Load), and storage and access (Data Warehouse and HTEM-DB). In turn, these RDI tools act as a communication pipeline to the High-Throughput Experimental Materials Database (HTEM-DB, htem.nrel.gov), which is the endpoint repository for inorganic thin-film materials data collected during combinatorial experiments at the NREL.<br/>The described RDI tools used for curating experimental data at NREL can be applied to other materials research laboratory settings, paving the way for increased application of machine learning to materials science. They also may provide an avenue to expand NREL’s emerging autonomous experimentation capabilities from autonomous data analysis, through sample characterization and materials synthesis, and all the way to autonomous materials discovery and design. In turn, the resulting new materials and new knowledge will benefit the society by advancing new technologies in energy conversion, storage, and other important areas.<br/><br/>[1] Research Data Infrastructure for High-Throughput Experimental Materials Science, Kevin R. Talley, Robert White, Nick Wunder, Matthew Eash, Marcus Schwarting, Dave Evenson, John D. Perkins, William Tumas, Kristin Munch, Caleb Phillips, Andriy Zakutayev, Patterns (2021) arXiv:2105.05160