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Using organic photodetectors for multispectral sensing is attractive due to their unique capabilities to tune spectral response, transmittance, and polarization sensitivity. Existing methods lack tandem multicolor detection and exhibit high spectral cross talk. We exploit the polarization sensitivity of organic photodetectors, together with birefringent optical filters to design single-pixel multispectral detectors that achieve high spectral selectivity and good radiometric performance. Two different architectures are explored and optimized, including the Solc-based and multitwist-retarder-based organic photodetectors. Although the former demonstrated a higher spectral resolution, the latter enables a more compact sensor as well as greater flexibility in device fabrication.
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This content will become publicly available on May 17, 2025
Nonlinear self-calibrated spectrometer with single GeSe-InSe heterojunction device
Computational spectrometry is an emerging field that uses photodetection in conjunction with numerical algorithms for spectroscopic measurements. Compact single photodetectors made from layered materials are particularly attractive since they eliminate the need for bulky mechanical and optical components used in traditional spectrometers and can easily be engineered as heterostructures to optimize device performance. However, such photodetectors are typically nonlinear devices, which adds complexity to extracting optical spectra from their response. Here, we train an artificial neural network to recover the full nonlinear spectral photoresponse of a single GeSe-InSe p-n heterojunction device. The device has a spectral range of 400 to 1100 nm, a small footprint of ~25 × 25 square micrometers, and a mean reconstruction error of 2 × 10−4for the power spectrum at 0.35 nanometers. Using our device, we demonstrate a solution to metamerism, an apparent matching of colors with different power spectral distributions, which is a fundamental problem in optical imaging.
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- PAR ID:
- 10544261
- Publisher / Repository:
- AAAS
- Date Published:
- Journal Name:
- Science Advances
- Volume:
- 10
- Issue:
- 20
- ISSN:
- 2375-2548
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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