Time-domain fit for improved contrast in quantitative coherent anti-Stokes Raman spectroscopy.

Among the multiple coherent anti-Stokes Raman scattering (CARS) techniques that provide important quantitative molecular microscopic contrast, Fourier-transform CARS (FT-CARS) stands out with the immunity to nonresonant background and high-speed detection capacity. However, by using FFT for the exponentially decaying signal, FT-CARS faces the dilemma of choosing the delay range of the signal for high SNR or high resolution, the lack of either of which is detrimental to the quantitative contrast of imaging. Here, time-domain fit (TDF) is proposed to fully utilize the time-domain information of FT-CARS, providing optimized SNR and vibrational feature distinguishment. The capacity of noise restriction and feature distinguishment of the traditional FFT and the proposed TDF is analysed with theoretical examination and simulation. Exploiting the matrix pencil extraction of vibrational parameters, TDF is performed for quantitative analysis for simulated FT-CARS signal, and shows more accurate and consistent performance than the FFT method. FT-CARS coupled with TDF intensity evaluation holds the promise to provide micro-spectroscopic contrast with higher SNR and free of spectral overlapping, contributing to a more powerful diagnostic tool.

A Fano-resonance plasmonic assembly for broadband-enhanced coherent anti-Stokes Raman scattering.

Surface-enhanced coherent anti-Stokes Raman scattering (SECARS) technique has triggered huge interests due to the significant signal enhancement for high-sensitivity detection. Previous SECARS work has tended to focus only on the enhancement effect at a certain combination of frequencies, more suitable for single-frequency CARS. In this work, based on the enhancement factor for broadband SECARS excitation process, a novel Fano resonance plasmonic nanostructure for SECARS is studied. In addition to the 12 orders of magnitude enhancement effect that can be realized under single-frequency CARS, this structure also shows huge enhancement under broadband CARS in a wide wavenumber region, covering most of the fingerprint region. This geometrically-tunable Fano plasmonic nanostructure provides a way to realize broadband-enhanced CARS, with potentials in single-molecular monitoring and high-selectivity biochemical detection.

Rapid coherent Raman hyperspectral imaging based on delay-spectral focusing dual-comb method and deep learning algorithm.

Rapid coherent Raman hyperspectral imaging shows great promise for applications in sensing, medical diagnostics, and dynamic metabolism monitoring. However, the spectral acquisition speed of current multiplex coherent anti-Stokes Raman scattering (CARS) microscopy is generally limited by the spectrometer integration time, and as the detection speed increases, the signal-to-noise ratio (SNR) of single spectrum will decrease, leading to a terrible imaging quality. In this Letter, we report a dual-comb coherent Raman hyperspectral microscopy imaging system developed by integrating two approaches, a rapid delay-spectral focusing method and deep learning. The spectral refresh rate is exploited by focusing the relative delay scanning in the effective Raman excitation region, enabling a spectral acquisition speed of 36 kHz, ≈4 frames/s, for a pixel resolution of 95 × 95 pixels and a spectral bandwidth no less than 200 cm-1. To improve the spectral SNR and imaging quality, the deep learning models are designed for spectral preprocessing and automatic unsupervised feature extraction. In addition, by changing the relative delay focusing region of the comb pairs, the detected spectral wavenumber region can be flexibly tuned to the high SNR region of the spectrum.

Sensitive impulsive stimulated Brillouin spectroscopy by an adaptive noise-suppression Matrix Pencil.

Impulsive stimulated Brillouin spectroscopy (ISBS) plays a critical role in investigating mechanical properties thanks to its fast measurement rate. However, traditional Fourier transform-based data processing cannot decipher measured data sensitively because of its incompetence in dealing with low signal-to-noise ratio (SNR) signals caused by a short exposure time and weak signals in a multi-peak spectrum. Here, we propose an adaptive noise-suppression Matrix Pencil method for heterodyne ISBS as an alternative spectral analysis technique, speeding up the measurement regardless of the low SNR and enhancing the sensitivity of multi-component viscoelastic identification. The algorithm maintains accuracy of 0.005% for methanol sound speed even when the SNR drops 33 dB and the exposure time is reduced to 0.4 ms. Moreover, it proves to extract a weak component that accounts for 6% from a polymer mixture, which is inaccessible for the traditional method. With its outstanding ability to sensitively decipher weak signals without spectral a priori information and regardless of low SNRs or concentrations, this method offers a fresh perspective for ISBS on fast viscoelasticity measurements and multi-component identifications.

Dual-wavelength excitation combined Raman spectroscopy for detection of highly fluorescent samples.

As fluorescence is the major limitation in Raman scattering, near-infrared excitation wavelength (>780nm) is preferred for fluorescence suppression in Raman spectroscopy. To reduce the risk of fluorescence interference, we developed a dual-wavelength excitation combined Raman spectroscopy (DWECRS) system at 785 and 830 nm. By a common optical path, each laser beam was focused on the same region of the sample by a single objective lens, and the dual-wavelength excitation Raman spectra were detected by a single CCD detector; in addition, 785 and 830 nm excitation Raman spectra can be directly constructed as combined Raman spectrum in the DWECRS system. The results of pure peanut oil and glycerol indicate that the combined Raman spectrum cannot only reduce fluorescence interference but also keep a high signal-to-noise ratio in the high-wavenumber region. The results of dye-ethanol solutions with different concentrations show that the handheld DWECRS system can be used as a smart method to dodge strong fluorescence. Furthermore, we developed a peak intensity ratio method with the DWECRS system to distinguish different types of edible oils. The peak intensity ratio distribution chart of edible oils showed each oil normalized center was relatively independent and nonoverlapped, which can be used as the basis of edible oil classification analysis. In the future, the DWECRS system has potential to be used as a tool for more complex applications.

Surface-enhanced shifted excitation Raman difference spectroscopy for trace detection of fentanyl in beverages.

In recognition of the misuse risks of fentanyl, there is an urgent need to develop a useful and rapid analytical method to detect and monitor the opioid drug. The surface-enhanced shifted excitation Raman difference spectroscopy (SE-SERDS) method has been demonstrated to suppress background interference and enhance Raman signals. In this study, the SE-SERDS method was used for trace detection of fentanyl in beverages. To prepare the simulated illegal drug-beverages, fentanyls were dissolved into distilled water or Mizone as a series of test samples. Based on our previous work, the surface-enhanced Raman spectroscopy detection was performed on the beverages containing fentanyl by the prepared AgNPs and the SE-SERDS spectra of test samples were collected by the dual-wavelength rapid excitation Raman difference spectroscopy system. In addition, the quantitative relationship between fentanyl concentrations and the Raman peaks was constructed by the Langmuir equation. The experimental results show that the limits of quantitation for fentanyl in distilled water and Mizone were 10 ng/mL and 200 ng/mL, respectively; the correlation coefficients for the nonlinear regression were as high as 0.9802 and 0.9794, respectively; and the relative standard deviation was less than 15%. Hence, the SE-SERDS method will be a promising method for the trace analyses of food safety and forensics.

Segment-Resolved Gas Concentration Measurements by a Time Domain Multiplexed Dual Comb Method.

Locating gas concentration changes in widespread locations can be conducive to environmental atmospheric detection, gas emissions monitoring, production process control, etc. A time domain multiplexed dual-comb system for segment-resolved gas concentration measurement is reported in this work. Both absorption spectra and path lengths for multiple path-segments in a target path can be derived from the time domain separated interferograms and then the equivalent gas concentrations in each segment can be retrieved separately. A benchtop experiment aiming at a target path with three path-segments of different gases has been demonstrated. The relative deviation of gas concentration retrieval is 1.08% in 1 s. Besides, additional numerical simulations prove that the crosstalk between the interference signals affects the spectrum analysis by no more than 0.1% for a kilometer-long atmospheric absorption detection. Therefore, achieving a gridded measurement of regional gas concentration in the open air can be foreseen using this method.