ArticleNanophotonics (Berlin, Germany)2026
End-to-End Deep Learning Framework for Freeform Metasurfaces via Non-Uniform Rational B-Splines Meta-Atoms.
Article in Nanophotonics (Berlin, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Conventional metasurface designs face fundamental trade-offs among geometric freedom, fabrication fidelity, and optical functionality. Here, we transcend these limitations through Non-Uniform Rational B-Splines (NURBS)-enabled computational co-design, establishing a paradigm in which freeform curvature control, deep learning optimization, and nanoscale lithography act synergistically. Unlike topology-constrained meta-atoms requiring iterative electromagnetic simulations, our framework deploys a Transformer-based differentiable surrogate to harness the parametric continuity of NURBS for arbitrary wavefront sculpting. Crucially, we introduce dose curvature proximity compensated lithography, which restores symmetry between design intent and fabricated structure through geometry dependent electron beam modulation. Experimental validation demonstrates achromatic wavelength scale focusing across 405-633 nm, with refined focal plane line profile analysis yielding full-width-at-half-maximum (FWHM) values of 1.15
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