The 3D X-ray microscopy of frozen hydrated biological specimens is currently approaching a limit to specimen thickness, the surpassing of which violates the pure projection approximation (PPA) needed for standard tomographic imaging. Sufficient understanding of the underlying problem has enabled development of a novel approach to beyond-pure-projection X-ray image construction utilizing powerful--but computationally demanding--methods. This project aims to scale up these methods to meet the challenge of high-resolution X-ray imaging beyond the PPA, benefitting not just cell and brain imaging but the full range of future nanoscale imaging activities at DOE light sources. The discovery of 2D ferromagnetic materials in 2017 ushered in a new era of studies on magnetic order. Using a data-driven approach, this project will combine machine learning and high-throughput density functional theory calculations to study van der Waals layered materials and predict their magnetic and thermodynamic properties.