Our collaborative paper with Pacific Northwest National Laboratory is out in npj Computational Materials. Former Auburn Ph.D. student Rajendra Paudel grew LaFeO3 films on SrTiO3 that PNNL characterized using electron microscopy and irradiated with Au ions to model radiation damage in materials. Their team used machine learning models to segment the images and classify them. The work advances computer vision for electron microscopy to improve automation and complements our ongoing work in machine learning for thin film growth. The work at Auburn and UD was supported by NSF under DMR-1809847 and DMR-2045993.