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<p>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 ( &lt; 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.</p>

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Dispersive Meta-lens Thermometry for High-temperature Measurements

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月18日

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  • Yulun He,
  • Mu Ku Chen,
  • Mingrui Huang,
  • Yifei Zhang,
  • Xiaoyuan Liu,
  • Zhendong Luo,
  • Chunhui Yao,
  • Hao Li,
  • Fei Zeng,
  • Zihan Geng,
  • Fei Qi,
  • Shumin Xiao,
  • Shengxian Shi,
  • Din Ping Tsai

摘要

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.