ArticleNature communications2025
Dispersive Meta-lens Thermometry for High-temperature Measurements.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- A Spectral-Emissivity-Corrected Method for Temperature Inversion from CCD Images.Sensors (Basel, Switzerland) · 2026Article
- Metasurface-Enabled Helical Wavefront Fingerprint Metrology for Quantitative Retrieval of Liquid Optical Constants.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Compact Snapshot Hyperspectral Imaging With Neural Dispersion-Engineered Metalens.Nanophotonics (Berlin, Germany) · 2026Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Temperature is a fundamental parameter that governs the rate and extent of thermal energy transfer. Accurate measurement is crucial for safe and efficient energy exchange. Radiation thermometry, favoured for high-temperature measurement due to its non-invasive nature, often requires bulky optics like interference filters. Meta-lenses, which separates incoming thermal radiation across a wide spectrum, offers a promising path toward integrated and miniaturized solutions. This work proposes a Dispersive Meta-lens Thermometry (DMT) for high-temperature measurements, employing a dispersive meta-lens with controllable dispersion to encode hyperspectral information into a compressed image. This is deciphered using convex spectral compress sensing and a deep reverse dispersive network. Experimental results show DMT achieved a 6-fold reduction in measurement error ( < 0.32%) over recent multi-spectral light-field thermometry approaches, and measurement errors for flame impingements maintained below 1.5%. No doubt further integration is required, this work demonstrates the potential for miniaturized hyperspectral high-temperature thermometry.
Identifiers
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Registered trials
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