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Low-cost chip-scale spectrometer enabled by equal-thickness interference spectral encoding.

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    Summary
    This summary is machine-generated.

    We developed a low-cost, chip-scale spectrometer using equal-thickness interference. This compact device, enhanced by a physics-constrained neural network (PCNN), achieves high spectral resolution for miniaturized sensing applications.

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    Area of Science:

    • Optics and Photonics
    • Microfabrication
    • Artificial Intelligence in Spectroscopy

    Background:

    • Traditional spectrometers are often bulky and expensive, limiting their application in portable or miniaturized sensing systems.
    • Miniaturization of spectral sensing technology is crucial for expanding applications in fields like environmental monitoring, medical diagnostics, and industrial process control.
    • Interference-based spectral encoding offers a potential pathway for developing compact and cost-effective spectrometers.

    Purpose of the Study:

    • To design and demonstrate a low-cost, chip-scale spectrometer utilizing the principle of equal-thickness interference.
    • To achieve high spectral resolution within a compact form factor for practical spectral sensing.
    • To simplify the calibration process for micro-spectrometer systems.

    Main Methods:

    • A chip-scale spectrometer was designed using a plano-convex lens and a flat glass plate, coated with silver, capturing interferograms with a charge-coupled device (CCD).
    • A physics-constrained neural network (PCNN) was employed to decode the captured interference images for spectral analysis.
    • A simplified calibration method was implemented by capturing the interferogram at a specific wavelength (400 nm) and utilizing a scaling relationship.

    Main Results:

    • The developed micro-spectrometer achieved a spectral resolution better than 4.8 nm across the 400-800 nm wavelength range.
    • The spectrometer has a compact active chip size of 8.6 mm square and an overall form factor of 7 cm.
    • The PCNN-based decoding and simplified calibration significantly enhance the practicality and usability of the device.

    Conclusions:

    • The proposed chip-scale spectrometer offers a compact, low-cost, and practical solution for miniaturized spectral sensing.
    • The integration of equal-thickness interference and PCNN decoding demonstrates a viable approach for high-resolution micro-spectroscopy.
    • This technology has the potential to enable a new generation of portable and accessible spectral analysis tools.