ArticleNature communications2021
Phase-to-pattern inverse design paradigm for fast realization of functional metasurfaces via transfer learning.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
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Who cites it
37 citing papers in PubMed.
- End-to-End Deep Learning Framework for Freeform Metasurfaces via Non-Uniform Rational B-Splines Meta-Atoms.Nanophotonics (Berlin, Germany) · 2026Article
- Decoupling Backward Scattering Control and Forward Beamformed Communication in a Shared-Aperture Retro-Reflective/Transmissive Metasurface.Nanophotonics (Berlin, Germany) · 2026Article
- Large-scale data-driven inverse EM design based on metacircuit-embedded surface.Nature communications · 2026Article
- Creation of a computational space with model-free metasurface neural network.Nature communications · 2026Article
- Holographic lasing with dielectric metasurfaces.Science advances · 2026Article
- Artificial Intelligence-Driven Metasurfaces Spanning Multidimensional Light Field Control and Free Space Computing.Micromachines · 2026Review
- Near real-time full-wave inverse design of electromagnetic devices.Nature communications · 2026Article
- High-Asymmetry Metasurface: A New Solution for Terahertz Resonance via Active Learning-Augmented Diffusion Model.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Physics-informed deep learning for plasmonic sensing of nanoscale protein dynamics in solution.Science advances · 2025Article
- Reliable, efficient, and scalable photonic inverse design empowered by physics-inspired deep learning.Nanophotonics (Berlin, Germany) · 2025Article
- Polarization dependent bound states in continuum in a tetramer metasurface discovered by random forest algorithm.Scientific reports · 2025Article
- Transfer Learning Empowered Multiple-Indicator Optimization Design for Terahertz Quasi-Bound State in the Continuum Biosensors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Customizing the electric field of metalens with high degrees of freedom based on neural network.Nanophotonics (Berlin, Germany) · 2025Article
- Article
- Frequency transfer and inverse design for metasurface under multi-physics coupling by Euler latent dynamic and data-analytical regularizations.Nature communications · 2025Article
- A guidance to intelligent metamaterials and metamaterials intelligence.Nature communications · 2025Review
- Design of a Deep Learning-Based Metalens Color Router for RGB-NIR Sensing.Nanomaterials (Basel, Switzerland) · 2024Article
- Meta-Attention Deep Learning for Smart Development of Metasurface Sensors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Physics-Informed Inverse Design of Programmable Metasurfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Nested deep transfer learning for modeling of multilayer thin films.Advanced photonics · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Metasurfaces have provided unprecedented freedom for manipulating electromagnetic waves. In metasurface design, massive meta-atoms have to be optimized to produce the desired phase profiles, which is time-consuming and sometimes prohibitive. In this paper, we propose a fast accurate inverse method of designing functional metasurfaces based on transfer learning, which can generate metasurface patterns monolithically from input phase profiles for specific functions. A transfer learning network based on GoogLeNet-Inception-V3 can predict the phases of 2
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.