Upconversion time-stretch infrared spectroscopy.
Kazuki HashimotoTakuma NakamuraTakahiro KageyamaVenkata Ramaiah BadarlaHiroyuki ShimadaRyoich HorisakiTakuro IdeguchiPublished in: Light, science & applications (2023)
High-speed measurement confronts the extreme speed limit when the signal becomes comparable to the noise level. In the context of broadband mid-infrared spectroscopy, state-of-the-art ultrafast Fourier-transform infrared spectrometers, in particular dual-comb spectrometers, have improved the measurement rate up to a few MSpectra s -1 , which is limited by the signal-to-noise ratio. Time-stretch infrared spectroscopy, an emerging ultrafast frequency-swept mid-infrared spectroscopy technique, has shown a record-high rate of 80 MSpectra s -1 with an intrinsically higher signal-to-noise ratio than Fourier-transform spectroscopy by more than the square-root of the number of spectral elements. However, it can measure no more than ~30 spectral elements with a low resolution of several cm -1 . Here, we significantly increase the measurable number of spectral elements to more than 1000 by incorporating a nonlinear upconversion process. The one-to-one mapping of a broadband spectrum from the mid-infrared to the near-infrared telecommunication region enables low-loss time-stretching with a single-mode optical fiber and low-noise signal detection with a high-bandwidth photoreceiver. We demonstrate high-resolution mid-infrared spectroscopy of gas-phase methane molecules with a high resolution of 0.017 cm -1 . This unprecedentedly high-speed vibrational spectroscopy technique would satisfy various unmet needs in experimental molecular science, e.g., measuring ultrafast dynamics of irreversible phenomena, statistically analyzing a large amount of heterogeneous spectral data, or taking broadband hyperspectral images at a high frame rate.
Keyphrases
- high speed
- high resolution
- optical coherence tomography
- atomic force microscopy
- energy transfer
- air pollution
- mass spectrometry
- photodynamic therapy
- single molecule
- public health
- quantum dots
- tandem mass spectrometry
- electronic health record
- magnetic resonance imaging
- convolutional neural network
- deep learning
- density functional theory
- artificial intelligence
- magnetic resonance
- contrast enhanced
- molecular dynamics