Chemistry and Biochemistry
Inorganic, materials, and magnetochemistry
The Rinehart Group studies materials at the interface of quantum and classical scales with interesting magnetic dynamics. Their work emphasizes the development of intuitive models for bottom-up control of magnetic properties design and new methods for large-scale quantitative data verification, parameterization, and organization. Current materials science projects involve the development of new software (Python-based) to address needs in data processing and alignment with FAIR data principles, facilitate analyses of large, modular datasets, and provide a realistic entry point for machine learning models in magnetic materials research involving large and multicomponent inputs including those of synthetic, structural, and physical origin.