<p>We demonstrate a computational multispectral metasurface employing a 3<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_6599_Article_IEq1.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">\(\times\)</EquationSource> </InlineEquation>3 photonic crystal array architecture that operates across the longwave infrared spectrum (8–11.5 <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_6599_Article_IEq2.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="12" /> </InlineMediaObject> <EquationSource Format="TEX">\(\upmu\)</EquationSource> </InlineEquation> m). The designed structure achieves remarkable optical performance with peak transmittance reaching 75.8% and broadband energy utilization efficiency of 41.37%. Notably, the inter-channel transmittance correlation coefficient of 0.17 indicates superior spectral discrimination compared to conventional grating-based systems. We also considered the angular dependence of the array on the incident light. Additionally, to evaluate the spectral reconstruction performance of the transmission spectra under different photonic crystals, a spectral reconstruction deep learning network was constructed with the mean squared error is 2.86<InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_6599_Article_IEq3.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="47" /> </InlineMediaObject> <EquationSource Format="TEX">\(\times 10^{-3}\)</EquationSource> </InlineEquation>. This architecture establishes a hardware-algorithm co-design framework for next-generation infrared multispectral systems, demonstrating the potential for integrated superlattice detectors with sub-100 <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_6599_Article_IEq2.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="12" /> </InlineMediaObject> <EquationSource Format="TEX">\(\upmu\)</EquationSource> </InlineEquation> m<InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_6599_Article_IEq5.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="8" /> </InlineMediaObject> <EquationSource Format="TEX">\(^{2}\)</EquationSource> </InlineEquation> pixel pitch, which represents a critical advancement for portable spectroscopic applications.</p>

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Long-wave infrared computational multispectral metasurface and spectral reconstruction method

  • Shang Wang,
  • Lidan Lu,
  • Lianqing Zhu

摘要

We demonstrate a computational multispectral metasurface employing a 3 \(\times\) 3 photonic crystal array architecture that operates across the longwave infrared spectrum (8–11.5 \(\upmu\) m). The designed structure achieves remarkable optical performance with peak transmittance reaching 75.8% and broadband energy utilization efficiency of 41.37%. Notably, the inter-channel transmittance correlation coefficient of 0.17 indicates superior spectral discrimination compared to conventional grating-based systems. We also considered the angular dependence of the array on the incident light. Additionally, to evaluate the spectral reconstruction performance of the transmission spectra under different photonic crystals, a spectral reconstruction deep learning network was constructed with the mean squared error is 2.86 \(\times 10^{-3}\) . This architecture establishes a hardware-algorithm co-design framework for next-generation infrared multispectral systems, demonstrating the potential for integrated superlattice detectors with sub-100 \(\upmu\) m \(^{2}\) pixel pitch, which represents a critical advancement for portable spectroscopic applications.