ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024
Meta-Attention Deep Learning for Smart Development of Metasurface Sensors.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Shadow-Calibrated Stereo Vision for Colorimetric Sweat Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Flatland Metasurfaces for Optical Gas Sensing.Sensors (Basel, Switzerland) · 2026Review
- Deep Learning-Powered Nanoplasmonic Biosensing Approach Enables Ultrasensitive Extracellular Vesicles Profiling for Cancer Screening.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Inverse-designed plasmonic biosensors with LSPR-SPP-wood anomaly coupling enhanced for biomolecular analysis.Journal of nanobiotechnology · 2025Article
- Enabling highly efficient infrared silicon photodetectors via disordered metasurfaces with upconversion nanoparticles.Science advances · 2025Article
- Spectral Demodulation of Mixed-Linewidth FBG Sensor Networks Using Cloud-Based Deep Learning for Land Monitoring.Sensors (Basel, Switzerland) · 2025Article
- Anchor-controlled generative adversarial network for high-fidelity electromagnetic and structurally diverse metasurface design.Nanophotonics (Berlin, Germany) · 2025Article
- Transfer Learning Empowered Multiple-Indicator Optimization Design for Terahertz Quasi-Bound State in the Continuum Biosensors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Topology-Optimized Bound States in the Continuum with High-Q Acoustic Field Enhancement.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Optical multilayer thin film structure inverse design: From optimization to deep learning.iScience · 2025Review
- Empowering nanophotonic applications via artificial intelligence: pathways, progress, and prospects.Nanophotonics (Berlin, Germany) · 2025Review
- Advances in Nanoengineered Terahertz Technology: Generation, Modulation, and Bio-Applications.Research (Washington, D.C.) · 2025Review
- Meta-Attention Deep Learning for Smart Development of Metasurface Sensors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Optical metasurfaces with pronounced spectral characteristics are promising for sensor applications. Currently, deep learning (DL) offers a rapid manner to design various metasurfaces. However, conventional DL models are usually assumed as black boxes, which is difficult to explain how a DL model learns physical features, and they usually predict optical responses of metasurfaces in a fuzzy way. This makes them incapable of capturing critical spectral features precisely, such as high quality (Q) resonances, and hinders their use in designing metasurface sensors. Here, a transformer-based explainable DL model named Metaformer for the high-intelligence design, which adopts a spectrum-splitting scheme to elevate 99% prediction accuracy through reducing 99% training parameters, is established. Based on the Metaformer, all-dielectric metasurfaces based on quasi-bound states in the continuum (Q-BIC) for high-performance metasensing are designed, and fabrication experiments are guided potently. The explainable learning relies on spectral position encoding and multi-head attention of meta-optics features, which overwhelms traditional black-box models dramatically. The meta-attention mechanism provides deep physics insights on metasurface sensors, and will inspire more powerful DL design applications on other optical devices.
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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.