ReviewLight, science & applications2023
Recent advances in metasurface design and quantum optics applications with machine learning, physics-informed neural networks, and topology optimization methods.
Review in Light, science & applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Design of Polymeric 3D Printable Materials for THz Technology Applications.ACS applied polymer materials · 2026Article
- Artificial Intelligence-Driven Metasurfaces Spanning Multidimensional Light Field Control and Free Space Computing.Micromachines · 2026Review
- Dispersion-Engineered Broadband Transparent Meta-Cloak.Nanophotonics (Berlin, Germany) · 2026Article
- MxDiffusion: A Physics-Aware Maxwell's Law-Guided Diffusion Model Strategy for Inverse Photonic Metasurface Design.Nano letters · 2026Article
- Tunable dual-band THz metamaterial absorber with regression-learning-enabled numerical redesign.Scientific reports · 2026Article
- Full-space inverse-designed meta-optics for complex vector field shaping of intracavity landscapes.Light, science & applications · 2026Article
- Design and Optimization of Full-Stokes Hyperspectro-Polarimetric Encoding Metasurfaces Based on Conditional Multi-Task Deep Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Electromagnetic Sculptor: a differentiable geometric optimization framework to manipulate electromagnetic fields.Communications engineering · 2026Article
- Metaoptics merging computational optics and optical computing toward intelligent visual perception.Science advances · 2026Review
- Full-parameter-modulated three-dimensional vectorial generalized vortex array.Light, science & applications · 2026Article
- Interdisciplinary Nanomaterials for Biomedical Imaging and Sensing Applications.Nanomaterials (Basel, Switzerland) · 2025Review
- Demonstration of Advanced Timing Schemes in Time-Resolved X‑ray Diffraction Measurements.ACS omega · 2025Article
- 3D-printed mirror-less helicity preserving metasurface "mirror" for THz applications.Nanophotonics (Berlin, Germany) · 2025Article
- From pixels to camera: scaling superconducting nanowire single-photon detectors for imaging at the quantum-limit.Nano convergence · 2025Review
- Dynamic Collision Fingerprints (DCF): Introducing a New Descriptor Linking Lattice Interactions to 2D Structural Data Signatures.Journal of chemical theory and computation · 2025Article
- Reliable, efficient, and scalable photonic inverse design empowered by physics-inspired deep learning.Nanophotonics (Berlin, Germany) · 2025Article
- Nanomaterials in PCR: exploring light-to-heat conversion mechanisms and microfluidic integration.Microsystems & nanoengineering · 2025Review
- Bio-inspired multispectral camouflage material for microwave, infrared, and visible bands based on single hierarchical metasurface.Nanophotonics (Berlin, Germany) · 2025Article
- Quantum CZ gates on a single gradient metasurface.Light, science & applications · 2025Article
- MethPriorGCN: a deep learning tool for inferring DNA methylation prior knowledge and guiding personalized medicine.Briefings in bioinformatics · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As a two-dimensional planar material with low depth profile, a metasurface can generate non-classical phase distributions for the transmitted and reflected electromagnetic waves at its interface. Thus, it offers more flexibility to control the wave front. A traditional metasurface design process mainly adopts the forward prediction algorithm, such as Finite Difference Time Domain, combined with manual parameter optimization. However, such methods are time-consuming, and it is difficult to keep the practical meta-atom spectrum being consistent with the ideal one. In addition, since the periodic boundary condition is used in the meta-atom design process, while the aperiodic condition is used in the array simulation, the coupling between neighboring meta-atoms leads to inevitable inaccuracy. In this review, representative intelligent methods for metasurface design are introduced and discussed, including machine learning, physics-information neural network, and topology optimization method. We elaborate on the principle of each approach, analyze their advantages and limitations, and discuss their potential applications. We also summarize recent advances in enabled metasurfaces for quantum optics applications. In short, this paper highlights a promising direction for intelligent metasurface designs and applications for future quantum optics research and serves as an up-to-date reference for researchers in the metasurface and metamaterial fields.
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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.