Enhancing Access to Data. In collaboration with DMR-1729489, we are working to deliver an open data/software ecosystem by disseminating broadly research data through the Metals and Insulators through Structural Tuning (MIST) website hosted on data.world (https://data.world/dmref-mist).  Both open and private repositories of data and code are accessible to team members and general community users. The ecosystem currently includes:

• >50 different features for machine learning

• >100 MIT compounds for model training

• >100 temperature-dependent transport data (contributed by many)

 Bringing Advances into the Classroom. Rondinelli developed a new graduate course titled “Displacive and Nonmetal-to-Metal Transitions,” which leverages use-cases from the DMREF project and course material developed from Seshadri (DMR-1729489) on structure-driven MITs.