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Nature Computational Science
@natcomputsci.nature.com

📢 @emorychannano.bsky.social, @samblau.bsky.social and colleagues develop a DL approach for optimizing the nonlinear optical properties of core-shell upconverting nanoparticles, uncovering photophysical design rules and a roadmap for DL in nanoscience. www.nature.com/articles/s43... 🔓 rdcu.be/eTH72

nature.comGradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs - Nature Computational ScienceGraph neural networks built on physically motivated representations enable gradient-based optimization of complex upconverting nanoparticle heterostructures, revealing photophysical design rules and a...
Nature Computational Science
@natcomputsci.nature.com

An accompanying Research Briefing is now available for this paper! www.nature.com/articles/s43... 🔓 rdcu.be/eUVIw

nature.comDeep learning accelerates discovery of complex nanomaterials - Nature Computational ScienceA physics-infused heterogeneous graph neural network has been developed to address challenges in designing complex nanomaterials with spatially varying compositions. This fully differentiable model en...

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