Advances in Infrared Spectroscopy and Raman Spectroscopy

A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "New Applications Enabled by Photonics Technologies and Systems".

Deadline for manuscript submissions: closed (20 May 2024) | Viewed by 1680

Special Issue Editors

Institute for Quantum Science and Engineer, Texas A&M University, College Station, TX 77843, USA
Interests: Raman spectroscopy; nonlinear optics; ultrafast spectroscopy; plasmonics

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Guest Editor
Optical Engineer II, The Rockefeller University, New York, NY 10065, USA
Interests: ultrafast spectroscopy and microscopy

Special Issue Information

Dear Colleagues,

Molecules vibrate at specific modes, typically in the infrared (IR) frequency range, allowing us to develop advanced label-free techniques to sense them based on absorption or scattering. For example, IR spectroscopy relies on molecular absorption, while Raman spectroscopy utilizes inelastic scattering between the molecule and photons. Both are widely used to determine the vibrational modes of the detected molecules and quantify their signal intensities. Because a particular molecule or material provides a distinct chemical fingerprint, these label-free methods can be used to characterize and identify the material or distinguish it from others. When combined with confocal microscopy, label-free techniques can be extended to applications achieving real-time, chemical-specific, in situ imaging/mapping with sub-wavelength resolution.

This Special Issue invites manuscripts that introduce the recent advances in “Advances in Infrared Spectroscopy and Raman Spectroscopy”. The topic covers, but is not limited to, molecule detection, identification, and characterization; biomedical screening; light–matter interaction; vibrational coherence; IR spectroscopy; Raman spectroscopy; and time-resolved spectroscopy. All original research and review articles are accepted.

Dr. Zehua Han
Dr. Yujie Shen
Guest Editors

Manuscript Submission Information

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Keywords

  • label-free imaging
  • light–matter interaction
  • absorption
  • scattering
  • IR spectroscopy
  • spontaneous Raman
  • coherent Raman
  • nonlinear spectroscopy/microscopy
  • time-resolved techniques
  • vibrational mode
  • chemical bond

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Published Papers (1 paper)

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Research

12 pages, 5307 KiB  
Article
Research on a Data Preprocessing Method for a Vehicle-Mounted Solar Occultation Flux–Fourier Transform Infrared Spectrometer
by Yasong Deng, Liang Xu, Ling Jin, Yongfeng Sun, Shengquan Shu, Jianguo Liu and Wenqing Liu
Photonics 2024, 11(6), 541; https://doi.org/10.3390/photonics11060541 - 5 Jun 2024
Cited by 1 | Viewed by 901
Abstract
A vehicle-mounted solar occultation flux–Fourier transform infrared spectrometer uses the sun as an infrared light source to quantify molecular absorption in the atmosphere. It can be used for the rapid three-dimensional monitoring of pollutant emissions and the column concentration monitoring of greenhouse gases. [...] Read more.
A vehicle-mounted solar occultation flux–Fourier transform infrared spectrometer uses the sun as an infrared light source to quantify molecular absorption in the atmosphere. It can be used for the rapid three-dimensional monitoring of pollutant emissions and the column concentration monitoring of greenhouse gases. The system has the advantages of high mobility and a capacity for noncontact measurement and measurement over long distances. However, in vehicle-mounted applications, vehicle bumps and obstacles introduce aberrations in the measured spectra, affecting the accuracy of gas concentration inversion results and flux calculations. In this paper, we propose a spectral data preprocessing method that combines a self-organizing mapping neural network and correlation analysis to reject anomalous spectral data measured by the solar occultation flux–Fourier transform infrared spectrometer during mobile observations. Compared to the traditional method, this method does not need to adjust the comparison threshold and obtain the training spectra in advance and has the advantage of automatically updating the weights without the need to set fixed correlation comparison coefficients. The accurate identification of all anomalous simulated spectra in the simulation experiments proved the effectiveness of the method. In the vehicle-mounted application experiment, 342 anomalous spectra were successfully screened from 1739 spectral data points. The experimental results show that the method can improve the accuracy of gas concentration measurement results and can be applied to a vehicle-mounted solar occultation flux–Fourier transform infrared spectrometer system to meet the preprocessing needs of a high number of spectral data in mobile monitoring. Full article
(This article belongs to the Special Issue Advances in Infrared Spectroscopy and Raman Spectroscopy)
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