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Abstract Thanks to the unique molecular fingerprints in the mid-infrared spectral region, absorption spectroscopy in this regime has attracted widespread attention in recent years. Contrary to commercially available infrared spectrometers, which are limited by being bulky and cost-intensive, laboratory-on-chip infrared spectrometers can offer sensor advancements including raw sensing performance in addition to utilization such as enhanced portability. Several platforms have been proposed in the past for on-chip ethanol detection. However, selective sensing with high sensitivity at room temperature has remained a challenge. Here, we experimentally demonstrate an on-chip ethyl alcohol sensor based on a holey photonic crystal waveguide on silicon on insulator-based photonics sensing platform offering an enhanced photoabsorption thus improving sensitivity. This is achieved by designing and engineering an optical slow-light mode with a high group-index ofng = 73 and a strong localization of the modal power in analyte, enabled by the photonic crystal waveguide structure. This approach includes a codesign paradigm that uniquely features an increased effective path length traversed by the guided wave through the to-be-sensed gas analyte. This PIC-based lab-on-chip sensor is exemplary, spectrally designed to operate at the center wavelength of 3.4 μm to match the peak absorbance for ethanol. However, the slow-light enhancement concept is universal offering to cover a wide design-window and spectral ranges towards sensing a plurality of gas species. Using the holey photonic crystal waveguide, we demonstrate the capability of achieving parts per billion levels of gas detection precision. High sensitivity combined with tailorable spectral range along with a compact form-factor enables a new class of portable photonic sensor platforms when integrated with quantum cascade laser and detectors.
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Multi-mode interference waveguide chip-scale spectrometer (invited)
Spectral analysis of light is one of the oldest and most versatile scientific methods and the basis of countless techniques and instruments. Miniaturized spectrometers have recently seen great advances, but challenges remain before they are widely deployed. We report an integrated photonic spectrometer that achieves high performance with minimal component complexity by combining imaging of light propagation patterns in multi-mode interference waveguides with machine learning analysis. We demonstrate broadband operation in the visible and near-infrared, 0.05 nm spectral resolution, and an array of four spectrometers on a single chip. Two canonical applications are implemented: spectral analysis of the solar spectrum with neural network reconstruction and detection of Rayleigh scattering from microbeads on an optofluidic chip using principal component classification. These results illustrate the potential of this approach for high-performance spectroscopy across disciplines.
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- Award ID(s):
- 2206259
- PAR ID:
- 10594376
- Publisher / Repository:
- American Institute of Physics
- Date Published:
- Journal Name:
- APL Photonics
- Volume:
- 9
- Issue:
- 10
- ISSN:
- 2378-0967
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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