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Integrated near-infrared spectral sensing

Author

Listed:
  • Kaylee D. Hakkel

    (Eindhoven University of Technology)

  • Maurangelo Petruzzella

    (Eindhoven University of Technology)

  • Fang Ou

    (Eindhoven University of Technology)

  • Anne Klinken

    (Eindhoven University of Technology)

  • Francesco Pagliano

    (Eindhoven University of Technology)

  • Tianran Liu

    (Eindhoven University of Technology)

  • Rene P. J. Veldhoven

    (Eindhoven University of Technology)

  • Andrea Fiore

    (Eindhoven University of Technology)

Abstract

Spectral sensing is increasingly used in applications ranging from industrial process monitoring to agriculture. Sensing is usually performed by measuring reflected or transmitted light with a spectrometer and processing the resulting spectra. However, realizing compact and mass-manufacturable spectrometers is a major challenge, particularly in the infrared spectral region where chemical information is most prominent. Here we propose a different approach to spectral sensing which dramatically simplifies the requirements on the hardware and allows the monolithic integration of the sensors. We use an array of resonant-cavity-enhanced photodetectors, each featuring a distinct spectral response in the 850-1700 nm wavelength range. We show that prediction models can be built directly using the responses of the photodetectors, despite the presence of multiple broad peaks, releasing the need for spectral reconstruction. The large etendue and responsivity allow us to demonstrate the application of an integrated near-infrared spectral sensor in relevant problems, namely milk and plastic sensing. Our results open the way to spectral sensors with minimal size, cost and complexity for industrial and consumer applications.

Suggested Citation

  • Kaylee D. Hakkel & Maurangelo Petruzzella & Fang Ou & Anne Klinken & Francesco Pagliano & Tianran Liu & Rene P. J. Veldhoven & Andrea Fiore, 2022. "Integrated near-infrared spectral sensing," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-021-27662-1
    DOI: 10.1038/s41467-021-27662-1
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    Cited by:

    1. Sandra Benter & Adam Jönsson & Jonas Johansson & Lin Zhu & Evangelos Golias & Lars-Erik Wernersson & Anders Mikkelsen, 2023. "Geometric control of diffusing elements on InAs semiconductor surfaces via metal contacts," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    2. Shukui Zhang & Hanxue Jiao & Yan Chen & Ruotong Yin & Xinning Huang & Qianru Zhao & Chong Tan & Shenyang Huang & Hugen Yan & Tie Lin & Hong Shen & Jun Ge & Xiangjian Meng & Weida Hu & Ning Dai & Xudon, 2024. "Multi-dimensional optical information acquisition based on a misaligned unipolar barrier photodetector," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    3. Ekici, Selcuk & Ayar, Murat & Hikmet Karakoc, T., 2023. "Fuel-saving and emission accounting: An airliner case study for green engine selection," Energy, Elsevier, vol. 282(C).
    4. Dohyun Kwak & Dmitry K. Polyushkin & Thomas Mueller, 2023. "In-sensor computing using a MoS2 photodetector with programmable spectral responsivity," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    5. Zhuo, Sheng & Zhou, Wenwu & Fang, Ping & Ye, Jianyong & Luo, Haoze & Li, Hejun & Wu, Changzi & Chen, Weifan & Liu, Yue, 2024. "Cost-effective pearlescent pigments with high near-infrared reflectance and outstanding energy-saving ability for mitigating urban heat island effect," Applied Energy, Elsevier, vol. 353(PA).

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