Hyper-spectral imaging with up-converted mid-infrared single-photons

Hyperspectral imaging in the mid-infrared (MIR) spectral range provides unique molecular specificity by probing fundamental vibrational modes of molecular bonds, making it highly valuable for biomedical and biochemical applications. However, conventional MIR imaging techniques often rely on high-intensity illumination that can induce photodamage in sensitive biological tissues. Single-photon MIR imaging offers a label-free, non-invasive alternative, yet its broader adoption is hindered by the lack of efficient, room-temperature MIR single-photon detectors. We present a single-photon hyperspectral imaging platform that combines cavity-enhanced spontaneous parametric down-conversion (SPDC) with nonlinear frequency up-conversion. This approach enables MIR spectral imaging using cost-effective, visible-wavelength silicon single-photon avalanche diodes (Si-SPADs), supporting room-temperature, low-noise, and high-efficiency operation. By leveraging time gating and intensity correlations of photon pairs generated via SPDC, we can effectively suppress classical background noise and enhance the signal-to-noise ratio, approaching the shot-noise limit. We demonstrate chemically specific single-photon imaging across the 2.9-3.6 [Formula: see text]m range on biological (egg yolk, yeast) and polymeric (polystyrene, polyethylene) samples. This platform paves the way toward scalable, quantum-enabled MIR imaging for applications in molecular diagnostics, environmental sensing, and biomedical research.

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Publication Details

Journal
Scientific Reports
Published
2025-12-12
DOI
https://doi.org/10.1038/s41598-025-32361-8
Citations
1
Primary Topic
Advanced Fiber Laser Technologies
Type
article
Field-Weighted Citation Impact
1.25
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article

Hyper-spectral imaging with up-converted mid-infrared single-photons

Mikael Lassen, Asbjørn Arvad Jørgensen, Søren Friis, Yijian Meng et al.
1 citations
Scientific Reports
Advanced Fiber Laser Technologies
1.25
article

Hyper-spectral imaging with up-converted mid-infrared single-photons

Mikael Lassen, Asbjørn Arvad Jørgensen, Søren Friis, Yijian Meng, Andreas N. Rasmussen, Lasse Høgstedt
article en
1 citations

Abstract

Hyperspectral imaging in the mid-infrared (MIR) spectral range provides unique molecular specificity by probing fundamental vibrational modes of molecular bonds, making it highly valuable for biomedical and biochemical applications. However, conventional MIR imaging techniques often rely on high-intensity illumination that can induce photodamage in sensitive biological tissues. Single-photon MIR imaging offers a label-free, non-invasive alternative, yet its broader adoption is hindered by the lack of efficient, room-temperature MIR single-photon detectors. We present a single-photon hyperspectral imaging platform that combines cavity-enhanced spontaneous parametric down-conversion (SPDC) with nonlinear frequency up-conversion. This approach enables MIR spectral imaging using cost-effective, visible-wavelength silicon single-photon avalanche diodes (Si-SPADs), supporting room-temperature, low-noise, and high-efficiency operation. By leveraging time gating and intensity correlations of photon pairs generated via SPDC, we can effectively suppress classical background noise and enhance the signal-to-noise ratio, approaching the shot-noise limit. We demonstrate chemically specific single-photon imaging across the 2.9-3.6 [Formula: see text]m range on biological (egg yolk, yeast) and polymeric (polystyrene, polyethylene) samples. This platform paves the way toward scalable, quantum-enabled MIR imaging for applications in molecular diagnostics, environmental sensing, and biomedical research.

Scientific ReportsVol. 16(1)
Statistics Denmark (DK), All-Russian research Institute of metrological service (RU)
Openalex Percentile: Top 15%
Advanced Fiber Laser Technologies
1.25
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Hyper-spectral imaging with up-converted mid-infrared single-photons — Mikael Lassen, Asbjørn Arvad Jørgensen, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS