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Inverse Design of Complex Nanoparticle Heterostructures via Deep Learning on Heterogeneous Graphs

Abstract Applications of deep learning (DL) to design nanomaterials are hampered by a lack of suitable data representations and training data. We report efforts to overcome these limitations and leverage DL to optimize the nonlinear optical properties of core-shell upconverting nanoparticles (UCNPs). UCNPs, which have applications in e.g., biosensing, super-resolution microscopy, and 3D printing, can emit visible and ultraviolet light from near-infrared excitations. We report the first large-sca...

Read more at chemrxiv.org

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