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Neural network enabled nanoplasmonic hydrogen sensors with 100 ppm limit of detection in humid air

Author

Listed:
  • David Tomeček

    (Chalmers University of Technology)

  • Henrik Klein Moberg

    (Chalmers University of Technology)

  • Sara Nilsson

    (Chalmers University of Technology)

  • Athanasios Theodoridis

    (Chalmers University of Technology)

  • Iwan Darmadi

    (Chalmers University of Technology)

  • Daniel Midtvedt

    (University of Gothenburg)

  • Giovanni Volpe

    (University of Gothenburg)

  • Olof Andersson

    (Insplorion AB)

  • Christoph Langhammer

    (Chalmers University of Technology)

Abstract

Environmental humidity variations are ubiquitous and high humidity characterizes fuel cell and electrolyzer operation conditions. Since hydrogen-air mixtures are highly flammable, humidity tolerant H2 sensors are important from safety and process monitoring perspectives. Here, we report an optical nanoplasmonic hydrogen sensor operated at elevated temperature that combined with Deep Dense Neural Network or Transformer data treatment involving the entire spectral response of the sensor enables a 100 ppm H2 limit of detection in synthetic air at 80% relative humidity. This significantly exceeds the

Suggested Citation

  • David Tomeček & Henrik Klein Moberg & Sara Nilsson & Athanasios Theodoridis & Iwan Darmadi & Daniel Midtvedt & Giovanni Volpe & Olof Andersson & Christoph Langhammer, 2024. "Neural network enabled nanoplasmonic hydrogen sensors with 100 ppm limit of detection in humid air," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45484-9
    DOI: 10.1038/s41467-024-45484-9
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    References listed on IDEAS

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    1. Hoang Mai Luong & Minh Thien Pham & Tyler Guin & Richa Pokharel Madhogaria & Manh-Huong Phan & George Keefe Larsen & Tho Duc Nguyen, 2021. "Sub-second and ppm-level optical sensing of hydrogen using templated control of nano-hydride geometry and composition," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
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