Research, Development and Application of Raman Scattering Technology

A special issue of Photonics (ISSN 2304-6732).

Deadline for manuscript submissions: 27 September 2025 | Viewed by 3006

Special Issue Editors


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Guest Editor
Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
Interests: nanophotonics; tip-enhanced Raman spectroscopy; heterogeneous catalysis

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Guest Editor
Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing, School of Ocean Information Engineering, Jimei University, Xiamen 361021, China
Interests: nanophotonics; plasmonics; surface-enhanced Raman scattering

Special Issue Information

Dear Colleagues,

Raman scattering, a phenomenon initially uncovered by the pioneering Indian physicist C. V. Raman in 1928, stands as a pivotal milestone in the realm of spectroscopy. Diverging from Rayleigh scattering, Raman scattering manifests as an inelastic scattering process, characterized by frequency shifts that match the vibrational modes and energy levels intrinsic to molecules. Consequently, this phenomenon plays a pivotal role in identifying the chemical bonds and functional groups within a molecule. Spontaneous Raman scattering is a weak process. However, advancements in laser technology and nanotechnology have promoted the excitation efficiency of Raman scattering and led to the development of a series of related new methods, including surface-enhanced Raman spectroscopy, tip-enhanced Raman spectroscopy, resonance Raman spectroscopy, coherent Raman spectroscopy, and spatial offset Raman spectroscopy.

The sensitivity has been pushed down to a single-molecule level and the spatial resolution has reached that of a single chemical bond under ultrahigh vacuum conditions. The extraordinary capabilities of Raman spectroscopy enable its widespread application, including materials analysis, biochemistry, food inspection, environmental monitoring, chemical production, polymers, and geological exploration. We envision that future developments will include the use of single-molecule Raman spectroscopy for general molecules, achieving sub-molecular spatial resolution under ambient conditions and advancing qualitative analysis for an even broader range of applications.

This Special Issue is designed to provide a comprehensive overview of cutting-edge research in the field. We enthusiastically invite researchers to contribute original state-of-the-art articles that push the boundaries of Raman spectroscopy research. Submissions may encompass a broad array of topics, including but not limited to:

  • Surface-enhanced and tip-enhanced Raman spectroscopy;
  • Coherent Raman spectroscopy;
  • Resonance Raman spectroscopy;
  • Biological applications of Raman spectroscopy;
  • Theoretical and computational advances of Raman spectroscopy;
  • Raman sensing;
  • Raman optical activity.

Dr. Haisheng Su
Dr. Enming You
Guest Editors

Manuscript Submission Information

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Keywords

  • surface-enhanced and tip-enhanced Raman spectroscopy
  • coherent Raman spectroscopy
  • resonance Raman spectroscopy
  • biological applications of Raman spectroscopy
  • theoretical and computational advances in Raman spectroscopy
  • Raman sensing
  • Raman optical activity

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Published Papers (4 papers)

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Research

16 pages, 1395 KiB  
Article
Multiplet Network for One-Shot Mixture Raman Spectrum Identification
by Bo Wang, Pu Zhang, Xiangping Zhu, Hua Wang, Wenzhen Ren, Chuan Jin and Wei Zhao
Photonics 2025, 12(4), 295; https://doi.org/10.3390/photonics12040295 - 21 Mar 2025
Viewed by 119
Abstract
Raman spectroscopy is widely used for material identification, but mixture analysis remains challenging due to noise and fluorescence interference. To tackle this issue, we propose the Multiplet Network, an advanced deep-learning model specifically designed for identifying components in mixtures. This model employs a [...] Read more.
Raman spectroscopy is widely used for material identification, but mixture analysis remains challenging due to noise and fluorescence interference. To tackle this issue, we propose the Multiplet Network, an advanced deep-learning model specifically designed for identifying components in mixtures. This model employs a shared-weight residual network to map both mixture and candidate spectra into a unified feature space, where least-squares regression is utilized to predict the components. Our framework enhances feature extraction and component identification capabilities, outperforming traditional regression methods. Experimental evaluations on the RRUFF dataset showed that our model achieved superior accuracy, especially as the number of candidate spectra increased. Furthermore, it exhibited remarkable robustness against Gaussian noise and baseline variations, maintaining high accuracy under challenging conditions. To assess the real-world applicability, the model was tested on experimentally collected mixture spectra with significant noise and baseline shifts. The results confirmed that it effectively identified major components under complex spectral conditions. Additionally, the unique structure of the model’s feature extraction combined with least squares allowed it to handle varying sizes of spectral libraries, ensuring both flexibility and scalability. Overall, our approach provides a robust and adaptable solution for Raman mixture analysis, with strong potential for complex chemical and material identification in practical applications. Full article
(This article belongs to the Special Issue Research, Development and Application of Raman Scattering Technology)
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13 pages, 2866 KiB  
Article
Non-Uniform Microlens Array Based on Photonic Nanojets for Remote Raman Sensing of Subsurface Analytes
by Xiang-Yu Li, Han-Yu Lin, Wen-Ding Ye, En-Ming You and Jing Liu
Photonics 2025, 12(3), 180; https://doi.org/10.3390/photonics12030180 - 21 Feb 2025
Viewed by 373
Abstract
Raman spectroscopy is a powerful technique for surface molecular analysis due to its ability to provide molecular fingerprint information. However, its application to subsurface analytes is limited by destructive or invasive methods that compromise the detection accuracy. To address this, we introduce a [...] Read more.
Raman spectroscopy is a powerful technique for surface molecular analysis due to its ability to provide molecular fingerprint information. However, its application to subsurface analytes is limited by destructive or invasive methods that compromise the detection accuracy. To address this, we introduce a non-uniform microlens array based on the photonic nanojet (PNJ) principle to realize subsurface remote Raman sensing. Using finite element simulations, the microlens design was optimized with a central lens radius of 5 μm and side lenses of half this radius, achieving a 52% increase in the focal length and a subwavelength spatial resolution compared to a single microlens. The non-uniform design also enhanced the Raman intensity by 85%, enabling sensitive detection of the subsurface analytes. The design’s versatility was validated with a rectangular microlens array, which showed similar improvements. Fabrication using 3D printing produced experimental results closely aligned with those of simulations, with focal length deviations of less than 9% at 1550 nm. These findings demonstrate that non-uniform microlens arrays are scalable, non-invasive, and effective tools for Raman spectroscopy, offering potential applications in biomedicine, materials science, and environmental monitoring, advancing the capabilities of subsurface sensing technologies. Full article
(This article belongs to the Special Issue Research, Development and Application of Raman Scattering Technology)
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17 pages, 7298 KiB  
Article
Temperature-Dependent Raman Scattering and Correlative Investigation of AlN Crystals Prepared Using a Physical Vapor Transport (PVT) Method
by Zhe Chuan Feng, Manika Tun Nafisa, Yao Liu, Li Zhang, Yingming Wang, Xiaorong Xia, Ze Tao, Chuanwei Zhang, Jeffrey Yiin, Benjamin Klein and Ian Ferguson
Photonics 2024, 11(12), 1161; https://doi.org/10.3390/photonics11121161 - 9 Dec 2024
Viewed by 771
Abstract
Ultrawide bandgap (UWBG) AlN c- and m-face crystals have been prepared using the physical vapor transport (PVT) method and studied penetratively using temperature-dependent (TD) Raman scattering (RS) measurements under both visible (457 nm) and DUV (266 nm) excitations in 80–870 K, plus correlative [...] Read more.
Ultrawide bandgap (UWBG) AlN c- and m-face crystals have been prepared using the physical vapor transport (PVT) method and studied penetratively using temperature-dependent (TD) Raman scattering (RS) measurements under both visible (457 nm) and DUV (266 nm) excitations in 80–870 K, plus correlative atomic force microscopy (AFM) and variable-angle (VA) spectroscopic ellipsometry (SE). VASE identified their band gap energy as 6.2 eV, indicating excellent AlN characteristics and revealing Urbach energy levels of about 85 meV. Raman analyses revealed the residual tensile stress. TDRS shows that the E2(high) phonon lifetime decayed gradually in the 80–600 K range. Temperature has the greater influence on the stress of m-face grown AlN crystal. The influence of low temperature on the E2(high) phonon lifetime of m-plane AlN crystal is greater than that of the high-temperature region. By way of the LO-phonon and plasma coupling (LOPC), simulations of A1(LO) modes and carrier concentrations along different faces and depths in AlN crystals are determined. These unique and significant findings provide useful references for the AlN crystal growth and deepen our understanding on the UWBG AlN materials. Full article
(This article belongs to the Special Issue Research, Development and Application of Raman Scattering Technology)
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11 pages, 2400 KiB  
Article
Application of Gap Mode Ultrasensitive P-GERTs in SERS-Based Rapid Detection
by Mingzhong Zhang, Shanshan Xu, Peng-Cheng Guan, Yue-Jiao Zhang and Jian-Feng Li
Photonics 2024, 11(8), 708; https://doi.org/10.3390/photonics11080708 - 30 Jul 2024
Cited by 1 | Viewed by 1086
Abstract
In surface-enhanced Raman scattering (SERS) detection research, the shape, structure, surface modification, and material selection of nanoparticles can significantly impact the SERS intensity. Petal-like gap-enhanced Raman tags (P-GERTs) possess numerous sharp tips and edges, which generate localized electric field enhancements, further amplifying the [...] Read more.
In surface-enhanced Raman scattering (SERS) detection research, the shape, structure, surface modification, and material selection of nanoparticles can significantly impact the SERS intensity. Petal-like gap-enhanced Raman tags (P-GERTs) possess numerous sharp tips and edges, which generate localized electric field enhancements, further amplifying the electric field enhancement effect on neighboring molecules and enhancing the SERS signal. Additionally, the surface of P-GERTs can be modified with functional molecules, enabling their application in the detection of disease biomarkers. Using COVID-19 as an example, the performance of P-GERTs in disease biomarker detection was validated, demonstrating that the signal intensity of this probe can reach 55 times that of regular gold nanoparticles and 36.7 times that of smooth shell gap-enhanced Raman tags (S-GERTs). Furthermore, in combination with magnetically retrievable magnetic bead substrates, the N-protein antigen was specifically detected in a one-step process. N-protein was detected within 15 min using a portable Raman spectrometer. The limit of detection (LOD) for the standard sample was 4.28 pg/mL, and the LOD for the actual throat swab sample system was 25.4 pg/mL. This workflow can be extended to the detection of other biomarkers, making it widely applicable. Full article
(This article belongs to the Special Issue Research, Development and Application of Raman Scattering Technology)
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