30 July 2026, Volume 38 Issue 2
    

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  • Application and Innovation of Reflectance Transformation Imaging in Forensic Comparison
    DONG Yang, DONG Xiaoyu, HUANG Rui
    Chinese Journal of Light Scattering. 2026, 38(2): 323-330. https://doi.org/10.13883/j.issn1004-5929.202602001
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    In the current era of rapidly advancing digital technology, traditional examination techniques struggle to meet the practical demands of forensic examination when dealing with complex cases. Through a combination of literature review and controlled experiments, this study examines the current state of RTI research and its applications, validates its practical effectiveness, and analyzes its distinctive characteristics and advantages, and summarizes its application scenarios in trace evidence examination and document examination. The findings indicate that RTI is a non-contact detection method that bridges both high microscopic resolution and a large macroscopic field of view. It can significantly improve the identification accuracy of target features and provide objective inspection data.
  • RamanPro: A Multi-Scale Spectral Analysis Method for Diamond Anvil Cell (DAC) High-Pressure Experiments
    LI Jingye, LEI Li
    Chinese Journal of Light Scattering. 2026, 38(2): 331-337. https://doi.org/10.13883/j.issn1004-5929.202602002
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    To satisfy the comprehensive spectroscopic analysis requirements in high-pressure and high-temperature experiments based on the diamond anvil cell (DAC), including pressure and temperature calibration, batch data processing of high-pressure Raman and fluorescence spectra, and Raman mapping of the high-pressure sample chamber, we have developed RamanPro, a Python-based high-pressure spectroscopic analysis software system. The system integrates multiple functional modules, including automated ruby fluorescence peak identification and pressure calibration, diamond Raman high-frequency edge data extraction and pressure conversion, batch fitting and Raman mapping, pressure matrix generation, two-dimensional pressure distribution reconstruction, as well as temperature determination derived from Planck’s law of blackbody radiation and anti-Stokes/Stokes Raman intensity ratios. RamanPro facilitates the rapid extraction of pressure, temperature, and spatial stress distribution profiles directly from raw spectroscopic datasets, thereby streamlining the batch processing of high-pressure Raman spectra, P-T calibration, and visual analysis of pressure fields. Through Raman mapping experiments at various depths within the DAC, the software’s capability for diamond Raman edge identification, pressure calibration, and stress-distribution analysis under high-pressure conditions was rigorously validated. With RamanPro, we investigated the pressure distribution characteristics within localized loading zones and across various axial depths of the anvil under different high-pressure regimes. The results demonstrate pronounced discrepancies in pressure distribution at varying depths within the DAC, significant spatial heterogeneity of the pressure field in the vicinity of the sample chamber, and a progressive reduction in the dispersion of pressure distribution with increasing depth. Furthermore, the single-point axial pressure profile exhibits a characteristic trend of relatively high pressure in the shallow layers, rapid attenuation in the intermediate region, and a gradual decrease in the deeper regions. In summary, the RamanPro constitutes an efficient and robust analytical tool for pressure calibration, temperature determination, mapping data processing, stress field analysis, and the evaluation of anvil stress states under high-temperature and high-pressure DAC environments.
  • Refractive Index Measurement and Sensing Characteristics of Gold-Coated Three-Core Photonic Crystal Fiber
    GAO Zhijun, ZHANG Wenzhou, YING Yu
    Chinese Journal of Light Scattering. 2026, 38(2): 338-346. https://doi.org/10.13883/j.issn1004-5929.202602003
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    A novel gold-film-coated three-core photonic crystal fibre sensor has been proposed for accurate refractive index measurement and sensing characteristic analysis.This design involves a photonic crystal fibre with three air holes of varying diameters,all covered by a gold film.Numerical simulations and analysis using the full-vector finite element method revealed that sensor performance can be markedly tailored by adjusting the air hole diameters and gold film thickness.Notably,the sensor excels when the refractive index(RI) of the sample is between 1.36 and 1.41,with peak performance at an RI of 1.41.It achieves a maximum confinement loss of 75 dB·cm-1,a high amplitude sensitivity of 421 nm RIU-1,and a satisfactory resolution of 6.67×10-6 RIU.These attributes are essential for applications demanding high precision in research and industry.This research offers a fresh perspective on three-core photonic crystal fibre design and solidifies the foundation for advancements in fibre optic sensor technology.The innovative use of gold film could pave the way for developing more high-performance sensors,potentially broadening the scope of photonic crystal fibre applications.As sensor performance advances,the commercial viability of related technologies becomes increasingly promising.These high-performance sensors are poised for widespread adoption in emerging sectors such as intelligent manufacturing,automated monitoring systems,and the Internet of Things,significantly propelling their growth.The application of gold film in sensors highlights the potential for incorporating new materials in fibre optic sensors.This suggests that future research may explore other metals or composite materials to achieve further performance enhancements.The evolution of sensor technology is set to expand its applications across various domains,contributing to technological innovation and industry growth.
  • Object Shape Reconstruction in a Laser Curtain Network Based on Interpolation and Fourier Analysis
    HUANG Yuntian, ZHU Xu, TANG Ziqiang, LU Renxi, TAN Yadong, ZHOU Minghao, JIANG Leyan, DONG Yao, WU Xiaoshan
    Chinese Journal of Light Scattering. 2026, 38(2): 347-355. https://doi.org/10.13883/j.issn1004-5929.202602004
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    With the rapid development of laser scanning technology, laser scanners have been increasingly applied in environmental modeling and object detection. Although laser scanning point cloud data can provide abundant spatial information, factors such as data sparsity, noise interference, and environmental complexity pose significant challenges to precise shape reconstruction in practical applications. This paper proposes a laser curtain mesh shape reconstruction algorithm that combines interpolation methods with Fourier analysis to enhance the accuracy, stability, and efficiency of point cloud data processing. By comparing different interpolation algorithms—including IDW interpolation, Kriging interpolation, and least squares polynomial interpolation—and integrating Fourier analysis, the proposed algorithm not only extracts edge features of objects intersecting the laser curtain mesh but also effectively suppresses noise and improves detection accuracy. The final results have been successfully applied and validated in actual power station scenarios using a self-developed system.
  • Prediction of Metasurface Structural Colors Based on Fully Connected Neural Networks (FCNN)
    YANG Renxiang, FENG Jie, SUN Rong, LI Xinting, CHENG Qingbiao
    Chinese Journal of Light Scattering. 2026, 38(2): 356-362. https://doi.org/10.13883/j.issn1004-5929.202602005
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    Metasurfaces, which are artificial microstructure arrays at the scale of wavelengths, hold significant potential in applications such as structural color display and biosensing due to their ability to precisely regulate light fields. Deep learning offers a novel data-driven approach for modeling metasurfaces. This paper employs the FCNN-based method for predicting the structural color of metasurfaces, achieving a nonlinear mapping between “structure parameters and chromaticity values.”The experimental model’s average mean squared error (MSE) loss on the test set was 0.00071, while the mean absolute error (MAE) was 0.0161. The relative errors for the predictions of five representative samples were all below 4%. The reasoning efficiency of this model is approximately 104 times greater than that of the finite-difference time-domain (FDTD) model, with a single-sample prediction time of 37.05 times, thereby satisfying real-time requirements. Output reconstruction verification indicates that the MAE of the forward-predicted chromaticity values, when compared to the original target output, is less than 0.01, thereby confirming the model’s validity.
  • Rapid Identification of Streptococcus Suis Using Surface-Enhanced Raman Spectroscopy Combined with Random Forest Model
    JIANG Hong, ZHOU Guanxu, XU Xuefang
    Chinese Journal of Light Scattering. 2026, 38(2): 363-368. https://doi.org/10.13883/j.issn1004-5929.202602006
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    To establish a rapid analytical method for identifying four serotypes of Streptococcus suis, surface-enhanced Raman spectroscopy (SERS) was employed for the detection and analysis of these serotypes. Based on the differences in Raman characteristic peaks among the samples, a recognition model was constructed using the random forest algorithm combined with data dimensionality reduction. The model performance was evaluated using multiple metrics. The experimental results demonstrated that the SERS substrate effectively enhanced the Raman signals of S. suis, and the feature extraction algorithm significantly improved the model performance, achieving an overall accuracy of 93%. Therefore, the combination of SERS and the random forest algorithm offers an effective approach for the rapid identification of Streptococcus suis.
  • Fabrication and Quantitative Analysis of Paper-Based SERS Substrates Synergistically-Modified with KI and AgNO3
    WANG Xiaojing#, SUN Haoran#, ZHANG Huijuan, ZHANG Xuegang, ZHAO Yan, WANG Yue, YAN Yinzhou
    Chinese Journal of Light Scattering. 2026, 38(2): 369-381. https://doi.org/10.13883/j.issn1004-5929.202602007
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    Surface-enhanced Raman spectroscopy (SERS), as a highly sensitive molecular fingerprinting technique, holds great potential in the detection of trace substances. Due to the low cost, flexible structure, and excellent environmental compatibility, filter paper has been widely used in the construction of paper-based SERS substrates. However, the inherently random distribution of natural fibers results in highly heterogeneous surface morphology and uncontrollable hotspot distribution, thereby limiting signal uniformity and detection sensitivity. To address this issue, a co-modification strategy using potassium iodide (KI) and silver nitrate (AgNO3) is developed in this study. By adjusting the ratio of the reaction solution, the AgI shells are formed in situ on the paper-based substrate, effectively anchoring the analyte molecules onto the plasmonic nanostructures. Rhodamine 6G (R6G) is then employed as a probe molecule for performance evaluation. The results show that the modified substrate exhibits 6.2-fold Raman enhancement with fluorescence quenching, which improves signal quality and suppresses the background interference. Furthermore, a digital SERS (dSERS) analytical technique is introduced to construct a highly reproducible quantitative model based on binary statistical analysis of the occurrence probability in Raman signals. It demonstrates that the KI/AgNO3 synergistically-modified paper-based SERS substrate enables quantitative detection in the concentration range of 10-7 to 10-5 mol/L, with a good correlation coefficient (R2) of 0.9964. This strategy effectively overcomes the challenges of hotspot randomness and signal fluctuations in the traditional paper-based SERS substrates, providing a feasible pathway for the development of high-performance paper-based SERS substrates.
  • Theoretical Spectral Simulation of 2-Fluorodeschloroketamine
    GUAN Lichang, LONG Tangqi, ZENG Zeng, FENG Lei, ZHAO Nan, JIANG Xuemei
    Chinese Journal of Light Scattering. 2026, 38(2): 382-390. https://doi.org/10.13883/j.issn1004-5929.202602008
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    Density functional theory and time-dependent density functional theory methods at the B3LYP/6-311++G(d, p) and CAM-B3LYP/def2TZVP levels were used to systematically investigate the structural properties, frontier molecular orbitals, electrostatic potential, IR spectra, Raman spectra, and UV spectra of 2-Fluorodeschloroketamine (2-FDCK). The results indicate that both the highest occupied molecular orbital and the lowest unoccupied molecular orbital of 2-FDCK are alpha + beta orbitals, with energies of -6.51 eV and -0.86 eV, respectively, and an energy gap of 5.65 eV. The linear fitting equation between the experimental and calculated IR spectra is y=0.9988x+0.3041 (R2=0.9997), while that for the Raman spectra is y=1.0173x-16.092 (R2=0.9989), which confirms the high reliability of the theoretical calculations. The electrostatic potential distribution on the molecular surface of 2-FDCK ranges from -40 to 32 kcal/mol, with 13 localized maxima and 5 localized minima identified. UV spectral analysis reveals that the UV absorption of 2-FDCK is mainly dominated by the S3, S8, S10, and S12. Through the hole-electron analysis method, the S0→S3 transition is identified as a π-π* localized excitation on the benzene ring. The S0→S8 transition exhibits mixed excitation characteristics, including π-π* charge transfer excitation from the benzene ring to the cyclohexanone ring and π-π* localized excitation on the benzene ring. The S0→S10 transition is a π-π* localized excitation on the benzene ring. The S0→S12 transition involves both π-π* localized excitation on the benzene ring and π-π* localized excitation on the carbonyl group of the cyclohexanone ring.
  • High-Temperature Spectroscopy of the B′3 Σ u--B3 П gTransition Band System of Nitrogen Molecule was Investigated Using Ab initio
    NI Chao, CHENG Xinlu
    Chinese Journal of Light Scattering. 2026, 38(2): 391-397. https://doi.org/10.13883/j.issn1004-5929.202602009
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    Using highly correlated multi-reference configuration interaction (MRCI) approaches, and combined with ab initial theory. Under the framework of high-precision computation, systematic and accurate calculations were performed on the potential energy, transition dipole moments, vibrational and rotational spectral constants, and spectral line intensities of the B’3Σ-u- B3Πg transition bands of the N2 molecule. The obtained potential energy is very consistent with the potential energy curve fitted by RKR, and the calculated transition dipole moment is accurate and reliable. The variation of the vibrational rotational spectral constants of the B3Σu- electronic state of N2 molecule with respect to the vibrational quantum number v is consistent with existing experimental observation data. Meanwhile, the spectral line intensities of 22 lower vibrational bands, including 0-0, 0-1, and 0-2 etc. of the N2 molecule’s B′3∑-u - B3Пg band system were obtained at temperatures up to 5000 K, and the variation characteristics of the spectral line intensities with temperature were analyzed. For example, the band intensities of the 0-0 band at temperatures as high as 3000 K and 5000 K are 6.78×10-17cm-1/(molecular cm-2) and 2.82×10-17cm-1/(molecular cm-2), respectively. These results have important value for further studying the transitions between the electronic excited states of N2, and are of great significance in improving nitrogen molecule spectra and modeling high-temperature atmospheres, etc.
  • Study on Spectral and Electrochemical Properties of Nickel-Based Prussian Blue Analogue Modified by Reflux Method
    FENG Jiajin, WANG Da, ZENG Qingguang
    Chinese Journal of Light Scattering. 2026, 38(2): 398-403. https://doi.org/10.13883/j.issn1004-5929.202602010
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    Prussian blue analogues (PBAs) are promising cathode materials for sodium-ion batteries owing to their low cost and open framework structure. However, the presence of lattice water in PBAs induces undesirable side reactions, which significantly deteriorate their electrochemical performance. Here, we report a modified nickel-based hexacyanoferrate (NiHCF) material, designated as NiHCF-EC, through a condensation reflux method that facilitates the incorporation of ethylene carbonate (EC) solvent into the crystal lattice, effectively displacing lattice water. The resultant NiHCF-EC cathode exhibits remarkable cycling stability, delivering a reversible capacity of 56 mAh·g-1 after 100 cycles at a current density of 20 mA·g-1, which corresponds to a capacity retention of 90.3%. In situ IR spectroscopy further reveals the co-intercalation behavior of ［Na+-DME］ complexes during the discharge process. This work offers a reference for the strategic modification and mechanistic investigation of Prussian blue analogue-based electrodes.
  • Study on Gas Concentration Prediction Method for Lithium Battery Thermal Runaway Based on SSA-VMD-RF Algorithm and Raman Spectroscopy
    PEI Linlin, YUE Ting , CHEN Da
    Chinese Journal of Light Scattering. 2026, 38(2): 404-417. https://doi.org/10.13883/j.issn1004-5929.202602011
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    As safety risks associated with lithium battery thermal runaway become increasingly prominent, there is an urgent need to develop an analytical method capable of real-time, high-precision monitoring of characteristic gases amidst complex noise interference. This paper proposes a hybrid predictive model combining SSA-VMD-RF. Based on a laboratory-built Raman spectroscopy-based lithium battery thermal runaway gas monitoring system, Raman spectral data were collected for four types of lithium battery thermal runaway standard gases across different concentration gradients. VMD decomposition was employed to extract multi-frequency domain features, which were then flattened and input into an RF regression model for prediction. To optimize model performance, the SSA algorithm was introduced to simultaneously optimize key parameters of VMD and RF. Five-fold cross-validation was applied to enhance model generalization capability. Ultimately, the SSA-VMD-RF model demonstrated robust adaptability with superior signal-to-noise ratios over SVM, XGBoost, and PLSR, achieving R2 values exceeding 98.5%. Experimental validation using thermal runaway data from four different State-of-Charge (SOC) conditions confirmed the model’s capability to accurately reconstruct lithium battery thermal runaway gas concentration changes. This provides a reliable technical pathway and theoretical foundation for early warning and safety assessment of lithium battery thermal runaway.
  • Kinetics of Fe(III)-Catalyzed Heterogeneous Oxidation of SO2 on Fine Particle Surfaces Using Optical Tweezers-Enhanced Stimulated Raman Spectroscopy
    CAO Xue, CAI Hua, ZHANG Yunhong, SUN Jiuyi, WANG Caili, LI Keshu, ZHAO Xuan, CHEN Ze, ZHANG Dinghao, QIAO Wang, MA Mengnan, LI Xiang,
    Chinese Journal of Light Scattering. 2026, 38(2): 418-428. https://doi.org/10.13883/j.issn1004-5929.202602012
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    The rapid formation mechanism of sulfate in atmospheric fine particulate matter (PM2.5) was critical to explaining severe winter “haze pollution” in North China, yet traditional SO2 oxidation theories fail to resolve the significant discrepancies between observations and model predictions. This study investigates the interfacial catalytic mechanism of transition metal ions (Fe(III)) in real aerosol environments by employing aerosol optical tweezers (AOT) combined with cavity-enhanced Raman spectroscopy (CERS) to in situ resolve the kinetics of Fe(III)-catalyzed SO2 oxidation in single (NH4)2SO4 (or (NH4)2SO4+NH4HSO4) droplets. Through precise control of microdroplet parameters-particle size, pH (3~5), ionic strength (17~35 mol·kg-1), and SO2 concentration (0.025~1 ppm), we revealed a first-order kinetic relationship between Fe(III)-catalyzed reaction rates and SO2 concentration, with reactions predominantly occurring at aerosol surfaces. Experiments demonstrated that high ionic strength (I=35 mol·kg-1) enhances interfacial interactions between neutral SO2 molecules and Fe(III) via the kinetic salt effect, while increased pH elevates catalytic efficiency by 3~4 orders of magnitude, uncovering a hydroxyl-Fe(III) complex-mediated oxidation pathway at aerosol interfaces. This work confirms the interfacial catalytic activity of Fe(III), providing pivotal experimental evidence for refining sulfate formation mechanisms in atmospheric models and advancing targeted PM2.5 control strategies.
  • Using LightGBM Algorithm to Assist Raman Spectroscopy in Detecting Turmeric Fraud
    REN Xiaoge, WANG Xu
    Chinese Journal of Light Scattering. 2026, 38(2): 429-437. https://doi.org/10.13883/j.issn1004-5929.202602013
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    Turmeric is an important medicinal and edible raw material, and its adulteration in the market (such as the adulteration of starch, related species, or industrial dyes) not only disturbs the market order but also may introduce heavy metal pollution and threaten the health of consumers. The traditional chromatographic analysis method is cumbersome and time-consuming, making it difficult to meet the needs of on-site rapid screening. Although Raman spectroscopy technology has the advantages of being fast and lossless, its complex spectral characteristics and subtle spectral differences pose a challenge to the construction of a classification model. This study proposes a Raman spectrum analysis method based on the LightGBM machine learning algorithm to achieve efficient and accurate identification of turmeric adulteration. By collecting Raman spectrum data of pure turmeric and common adulterants (corn starch, maltodextrin, chrome yellow), the original spectrum was smoothed, baseline corrected, and normalized to effectively suppress noise and fluorescence background interference. Taking the preprocessed full-band spectral data as feature input, a classification model based on lightgbm is constructed, and its feature importance evaluation function is used to screen the key spectral features. Compared with traditional methods such as support vector machine (SVM) and partial least squares discriminant analysis (PLS-DA), the lightgbm model has an accuracy rate of 97.92%, an accuracy rate of 78.57%, and a recall rate of 91.67% in the task of turmeric authenticity classification, and has faster training and prediction speed. In this study, lightgbm algorithm was successfully combined with Raman spectroscopy technology to build a high-precision, high-efficiency and strong robustness identification model of turmeric adulteration, which gave full play to the advantages of lightgbm in processing high-dimensional spectral data, mining fine features and automatically screening key bands, providing effective algorithm support for the application of Raman spectroscopy in the rapid analysis of complex matrices, and also providing a feasible technical path for the quality and safety of food and traditional Chinese medicine on-site detection.
  • Classification and Identification of Lead-Containing Mineral Drugs Based on Raman Spectroscopy Combined with PCA-SVM Algorithm
    FENG Meiling, LI Zengming, HAN Siqingaowa, HASI Wuliji
    Chinese Journal of Light Scattering. 2026, 38(2): 438-444. https://doi.org/10.13883/j.issn1004-5929.202602014
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    In order to rapidly classify and identify lead-containing mineral medicines and their processed products. This study used Raman spectroscopy combined with principal component analysis (PCA)-support vector machine (SVM) algorithm for classifying and identifying red lead, litharge, lead powder, litharge from different origins, and its processed (water-flying) products. The results showed that red lead, litharge, and lead powder, due to significant differences in their Raman spectral features, could be accurately identified by visual inspection and the PCA-SVM model. However, raw realgar from different origins and its processed (water-flying) products, with similar appearance and Raman characteristic peaks, were difficult to distinguish by visual inspection alone. Nevertheless, the PCA-SVM algorithm still achieved 100% classification accuracy. This method is characterized by its speed, accuracy, non-destructiveness, convenience, portability of the instrumentation, and low cost. It holds significant application value for the classification and identification of mineral medicines as well as their quality control.
  • Feature analysis of Raman Spectra of Multi-site Clinical Calculi Based on Unsupervised Clustering
    ZHU Tingting, YI Zili, CHEN Aijia, WU Changqiang, LI Wenxue,
    Chinese Journal of Light Scattering. 2026, 38(2): 445-453. https://doi.org/10.13883/j.issn1004-5929.202602015
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    Calculi in the kidney, ureter, bladder, and prostate are clinically common. The differences in their composition are closely associated with their pathogenic mechanisms, treatment strategies, and recurrence risks. Raman spectroscopy, with its notable advantages such as rich informational output, high spectral resolution, and non-destructive analysis, serves as an ideal tool for investigating the composition of complex biological samples. This study innovatively established an integrated framework combining Raman spectroscopy, multi-dimensional dimensionality reduction algorithms, and clustering algorithms to analyze calculus samples from these multiple anatomical sites. The results demonstrated that the Uniform Manifold Approximation and Projection (UMAP) coupled with K-means clustering achieved the optimal clustering performance, with a silhouette score of 0.65 and a Calinski-Harabasz index of 498.5. Furthermore, the clustering outcomes showed a correlation with calculus composition. Compositional analysis, site-specific distribution, and spectral characteristics revealed that characteristic peaks of common calculus components coexisted across all clusters. However, the key factor driving cluster separation was the difference in peak intensities among clusters, reflecting the intrinsic relationship between the composition, proportional makeup of calculi, and their formative microenvironment. This research provides a novel technical pathway for efficient and objective investigation into the compositional differences of calculi across multiple locations.
  • Analysis of Four Taxus Leaves Using Raman Spectroscopy
    WANG Min, SI Minzhen,
    Chinese Journal of Light Scattering. 2026, 38(2): 454-459. https://doi.org/10.13883/j.issn1004-5929.202602016
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    Taxus is a long-standing first-class protected plant with high ornamental and medicinal value. Currently, most studies on Taxus focus on paclitaxel, but there has been little research on the content of the photosynthetic pigment lutein. Lutein, due to its oxidation properties, plays an important role in human brain and eye health. In order to study the content of lutein in the Taxus and expand its application value, this work studied the leaves of four Taxus: Taxus chinensis, Taxus wallichiana, Taxus yunnanensis and Torreya yunnanensis using Raman spectroscopy. From the obtained spectra, there were strong Raman peaks around 1523, 1187, 1158 and 1004 cm-1, which were consistent with the spectrum of lutein, it could be seen that the main component of Taxus leaves contained lutein, and the content of lutein in Taxus was much higher than that in other plants such as Dendrobium wardianum, Laggera pterodonta and so on.

  • Intelligent Raman Spectroscopic Identification and Quantification of Residual Methanol in Ethanol Disinfectants
    LI Bogang
    Chinese Journal of Light Scattering. 2026, 38(2): 460-470. https://doi.org/10.13883/j.issn1004-5929.202602017
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    Disinfectant ethanol is an essential material widely used in healthcare, public-area sanitation, and industrial cleaning, and its quality and safety are directly related to disinfection efficacy and public health. In recent years, incidents of methanol misblending, substitution, or contamination have occasionally been reported in some products. Although conventional methods such as gas chromatography offer high analytical accuracy, they generally suffer from cumbersome sample pretreatment, relatively long analysis times, and limited suitability for rapid on-site screening in grassroots regulation and field law enforcement. To address these limitations, this study proposes an intelligent Raman spectroscopic method for the identification and quantification of methanol in disinfectant ethanol for on-site quality control, with particular emphasis on establishing a rapid and nondestructive detection framework under through-container, unopened-bottle conditions. Based on the differential Raman responses of methanol and ethanol molecular vibrational features, and considering the influence of transparent packaging containers on excitation-light transmission and Raman-scattered-light propagation, a spectral acquisition and quality-control strategy for through-container measurements was developed. Furthermore, to overcome challenges such as bottle-wall interference, fluorescence background, overlap of weak characteristic peaks, and the difficulty of detecting low-level methanol, systematic studies on spectral preprocessing, characteristic band selection, and intelligent modeling were conducted. A machine-learning model balancing identification accuracy and quantitative stability was then established to enable rapid discrimination and concentration inversion of methanol in disinfectant ethanol. In addition, systematic validation using samples with different methanol adulteration levels under through-container testing conditions was carried out to evaluate the robustness, detection capability, and generalization performance of the proposed method in complex field scenarios. The outcome is a portable Raman-based rapid screening approach applicable to market supervision, product spot checks, and grassroots law-enforcement settings, thereby providing efficient, nondestructive, and low-cost technical support for the quality and safety regulation of disinfectant ethanol, while also offering theoretical and methodological references for expanding the application of Raman spectroscopy combined with intelligent algorithms in rapid on-site law-enforcement inspection.
  • Three-level Mid-Infrared Spectroscopy Study on the Structure and Thermal Stability of Ethylcellulose as a Pharmaceutical Excipient
    LEI Xiaojing, WANG Chunrun, ZHANG Yong, CHANG Ming, XU Yuanyuan, YU Hongwei
    Chinese Journal of Light Scattering. 2026, 38(2): 471-480. https://doi.org/10.13883/j.issn1004-5929.202602018
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    Ethylcellulose (EC) is a critical pharmaceutical excipient. The structure and thermal stability of ethylcellulose were investigated through three-level mid infrared spectroscopy. The results showed that the characteristic infrared absorption bands corresponding to key vibrational modes, including νO—H-free, νO—H-dimer, νO—H-polymer, νasCH3, νasCH2, νsCH3, δsCH3, νC—O and νOC2H5. With increasing temperature, measurable change were observed in the infrared absorption frequency and intensity of the major functional groups, resulting in a further decrease in the thermal stability of ethylcellulose. Under thermal perturbation, the temperature sensitivity of the absorption peaks corresponding to free O—H functional groups, dimer O—H functional groups, and CH3/CH2 functional groups were systematically evaluated, establishing a hierarchical order of their variation rates.The findings of this study establish a methodological framework for investigating the structural and thermal stability of ethylcellulose as a pharmaceutical excipient, offering significant application value in excipient characterization and formulation development.
  • Analysis of FTIR Spectra of Two Dried Wild Mushrooms Before and After Mildew Formation
    ZHOU Rui, WANG Min
    Chinese Journal of Light Scattering. 2026, 38(2): 481-491. https://doi.org/10.13883/j.issn1004-5929.202602019
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    Russula virescens and Lactarius volemus are two common wild edible mushrooms with high nutritional and health-promoting value. Drying preservation can extend their consumption period; however, they are prone to mildew during storage, which poses a threat to food safety. This study investigated dried R. virescens and L. volemus before and after mildew using Fourier-transform Infrared (FTIR) spectroscopy. Physicochemical and microbiological analyses showed that mildew caused the total viable counts of both dried wild mushrooms to increase exponentially from the order of 10 or 100 CFU/g to the order of 10 CFU/g, accompanied by substrate acidification, with pH values decreasing from 6.32 and 6.04 to 5.44 and 4.96, respectively. Further analysis of characteristic peaks in the infrared spectra was used to identify differences in functional groups and major chemical components before and after mildew. For dried R. virescens after mildew, the characteristic peaks exhibited the following changes: the absorption peaks in the amide I/II region shifted from 1556 cm-1 to 1595 cm-1, indicating weakened C=O stretching vibration and increased acidity; the glycosidic C—O—C peak shifted by 15 cm-1; the strongest peak shifted from 3283 cm-1 (N—H/O—H stretching) to 1025 cm-1 (characteristic of polysaccharides); the intensity ratio of the doublet peaks (A1086/A1023) decreased from 0.983 to 0.967; and new characteristic peaks appeared at 1744 cm-1 (carbonyl) and 1404 cm-1(C—N). In contrast, for dried L. volemus, comparison of characteristic peaks before and after mildew revealed the following: after mildew, the absorption peak of the amide II band shifted from 1573 cm-1 to 1548 cm-1; the amide III band peak shifted by 15 cm-1; the —CH2 bending vibration shifted by 19 cm-1; the polysaccharide-related C—C peak shifted by 16 cm-1; the strongest peak shifted from 3340 cm-1 to 2924 cm-1 (—CH2); the intensity ratio of the doublet peaks (A1081/A1021) decreased from 1.022 to 1.009; and a new absorption peak emerged at 2958 cm-1 (symmetric —CH2 vibration). The results indicate that, for both dried wild mushrooms, mildew leads to differences in the frequency positions of certain absorption peaks, the relative intensities of absorption peaks, and the position of the strongest peak. Therefore, FTIR spectroscopy can be used to distinguish whether these two dried wild mushrooms have undergone mildew.
  • Experimental Study on the Influence of Different Excitation Wavelengths on the Raman Spectrum of Nephrite Jade
    SU Yue, FANG Ting, LIU Jifu, YANG Mingxing,
    Chinese Journal of Light Scattering. 2026, 38(2): 492-498. https://doi.org/10.13883/j.issn1004-5929.202602020
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    Raman spectroscopy technology has broad application prospects in jade detection, as it can identify different types of jade by measuring characteristic Raman peaks, leveraging its advantages of non-destructiveness, rapidity, and accuracy. However, the inherent fluorescence effect of jade tends to interfere with the Raman spectrum, masking the signals of characteristic peaks and impairing detection accuracy. Currently, research on the spectral response mechanism of nephrite jade under different excitation wavelengths is insufficient, and there is a lack of systematic conclusions regarding the correlation between fluorescence interference and wavelength selection. In this study, Raman spectra of nephrite jade were measured at room temperature using lasers with wavelengths of 355 nm, 457 nm, 532 nm, 633 nm, and 785 nm, to analyze the influence of excitation wavelength on its spectral characteristics. The results showed significant differences in spectral characteristics under different wavelengths, the fluorescence interference was the strongest at 633 nm, with Raman peaks almost completely masked; while at 457 nm, the fluorescence interference was the weakest, and the characteristic peaks (such as those at 1020 cm-1, 670 cm-1, and 3670 cm-1) exhibited high intensity. Overall, 457 nm is the optimal excitation wavelength for nephrite jade detection. This study attempts to establish a wavelength selection standard for Raman detection of nephrite jade, providing an experimental basis for improving the accuracy of jade identification, promoting the standardization of non-destructive detection, and advancing jade mineralogy research, and is expected to provide technical support for subsequent practical applications such as quantitative analysis and origin tracing of nephrite jade.
  • Research on Identification of the Seals on Chinese Painting and Calligraphy by Laser Raman Spectroscopy and X-ray Fluorescence Spectroscopy
    ZHAO Meihong,
    Chinese Journal of Light Scattering. 2026, 38(2): 499-504. https://doi.org/10.13883/j.issn1004-5929.202602021
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    To establish a rapid analytical method for identifying four serotypes of Streptococcus suis, surface-enhanced Raman spectroscopy (SERS) was employed for the detection and analysis of these serotypes. Based on the differences in Raman characteristic peaks among the samples, a recognition model was constructed using the random forest algorithm combined with data dimensionality reduction. The model performance was evaluated using multiple metrics. The experimental results demonstrated that the SERS substrate effectively enhanced the Raman signals of S. suis, and the feature extraction algorithm significantly improved the model performance, achieving an overall accuracy of 93%. Therefore, the combination of SERS and the random forest algorithm offers an effective approach for the rapid identification of Streptococcus suis.
  • Analysis of Corrosion Products on the Spring-and-Autumn Bronze Gui in the Collection of the Guangdong Museum
    GAN Xinxin
    Chinese Journal of Light Scattering. 2026, 38(2): 505-512. https://doi.org/10.13883/j.issn1004-5929.202602022
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    Microscopy, X-ray fuorescence spectroscopy (XRF), X-ray diffraction spectroscopy (XRD), Fourier-transform micro-infrared spectroscopy (FT-IR) and ion chromatography (IC) were used to examine the textile remnants, corrosion products and surface encrustations on a Spring-and-Autumn-period bronze gui, excavated in Sanmenxia, Henan, and now collected in the Guangdong Museum. The white spots “powdery corrosion” consist of PbCO3 and Pb3(CO3)2(OH)2 and contain a higher chlorine level than other areas.
  • X-ray Fluorescence and Raman Spectroscopy Analysis of the Xi Xia Thangka“Portrait of the Guru”
    WEI Yali, WANG Yanling, ZHANG Yuting, CAI Li, LIU Yanrong, MA Li
    Chinese Journal of Light Scattering. 2026, 38(2): 513-520. https://doi.org/10.13883/j.issn1004-5929.202602023
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    The Xi Xia Thangka 《Portrait of the Guru》 collected by the Ningxia Museum possesses significant historical, artistic, and scientific value, rendering it extremely precious. This study employed techniques such as Optical Microscopy (OM), X-ray Fluorescence Spectroscopy (XRF), and Raman Spectroscopy to conduct test and analysis on the pigment flaking or endangered areas of the painting. The results indicate that the core fabric of the thangka is cotton fiber with a plain weave structure, exhibiting local fiber deformation, fracture, and discoloration. Pigment analysis reveals that the red color on both the thangka core and the wooden scroll shafts is cinnabar (HgS); the golden part of the wooden shafts is composed of gold (Au) and cinnabar (HgS), with the craftsmanship involving first applying cinnabar on the wooden shafts and then gilding over it. The blue pigment on the thangka core is azurite (Cu(CO3)2(OH)2), while the green pigment is phthalocyanine green (C32H3Cl15CuN8). Investigations confirm that the green area was retouched during the restoration in the late 20th century due to limited technical conditions at that time. In addition, gold powder was extensively used in the decorative parts of the bottom wooden shafts, the skin tone of the guru in the center of the thangka core, and the two monks wearing lotus hats—this not only reflects the revered status of monks in the Xi Xia but also highlights the preciousness of this thangka. The findings of this study provide a scientific basis for the conservation and restoration of Portrait of the Guru and offer important references for the research on materials and craftsmanship of painted cultural relics from the same period.
  • Scientific Research on Pigment Technology of Colored Terracotta Figurines Excavated from Han Nanling
    CAO Jingjing
    Chinese Journal of Light Scattering. 2026, 38(2): 521-527. https://doi.org/10.13883/j.issn1004-5929.202602024
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    This study employs super-depth-of-field optical microscopy, portable X-ray fluorescence spectroscopy, Raman spectroscopy, and polarizing microscopy to conduct the first comprehensive analysis of the pigment composition in the painted pottery figurines unearthed from the Hannan Mausoleum. The experiments revealed that the figurines were painted without a base layer, with pigments categorized into three types: single-layer, double-layer, and triple-layer. Specifically, the bright red pigment is cinnabar, the brown-red is iron red, the black pigment is carbon black, the brown-yellow is iron yellow, the green pigment consists of malachite green and calcium carbonate, and the pink pigment is a mixture of cinnabar, white clay, and iron red, or iron red combined with white clay or calcium carbonate. This research provides scientific guidance for the future conservation and restoration of these painted pottery figurines.
  • Near Infrared Spectroscopic Study on the O—H Structure of Cellulose ether Molecules
    ZHAO Xinyi, , DING Huining, Li Shuangfan, ZHANG Yong, YU Hongwei, CHANG Ming
    Chinese Journal of Light Scattering. 2026, 38(2): 528-536. https://doi.org/10.13883/j.issn1004-5929.202602025
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    The O—H structure of cellulose ether molecules was explored. The near-infrared (NIR) spectroscopy on the O—H structure of cellulose ether molecules (including one-dimensional NIR spectroscopy, in situ one-dimensional NIR spectroscopy and two-dimensional NIR spectroscopy) were studies. The experiment found that the absorption modes of the O—H structure of cellulose ether molecules mainly include: the first frequency doubling of the stretching vibration mode of the polymer O—H structure (ν1-NIR- 1D), the first frequency doubling of the stretching vibration mode of the polymer/dimer O—H structure (ν2-NIR- 1D), the first frequency doubling of the stretching vibration mode of the dimer O—H structure (ν3-NIR-1D), and the first frequency doubling of the stretching vibration mode of the free O—H structure (ν4-NIR- 1D). At room temperature, there are certain differences in the order of changes in the O—H structure of cellulose ether molecules. The order of change is 6665 cm-1 (ν1-B-NIR-2D) >6745 cm-1 (ν1-A-NIR-2D) >6605 cm-1 (ν1-C-NIR-2D) >6515 cm-1 (ν1-D-NIR-2D), 6955 cm-1 (ν2-B-NIR-2D) >6885 cm-1 (ν2-C-NIR-2D) >6975 cm-1 (ν2-A-NIR-2D) >6865 cm-1 (ν2-D-NIR-2D), 7175 cm-1 (ν3-A-NIR-2D) >7085 cm-1 (ν3-B-NIR-2D) >7025 cm-1 (ν3-C-NIR-2D), 7235 cm-1 (ν4-B-NIR-2D) >7225 cm-1 (ν4-C-NIR-2D) >7265 cm-1 (ν4-A-NIR-2D). NIR spectroscopy technology can quickly conduct research on the O—H structure of cellulose ether molecules.
  • Rapid Detection of Authenticity of Rose Seed Oil Using Raman Spectroscopy Based on Dual Model Collaboration
    ZHANG Dongpo
    Chinese Journal of Light Scattering. 2026, 38(2): 537. https://doi.org/10.13883/j.issn1004-5929.202602026
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    Rose seed oil is highly favored in the high-end cosmetics and health products market due to its excellent nutritional value and skincare benefits. It is expensive, but adulteration is common in the market. Traditional detection methods such as gas chromatography-mass spectrometry (GC-MS) are accurate, time-consuming, labor-intensive, and expensive, making it difficult to meet the needs of rapid on-site screening. This study innovatively proposes a fast and non-destructive detection method for the authenticity of rose seed oil based on Raman spectroscopy combined with dual model collaboration. The experiment collected Raman spectra (excitation wavelength 532 nm) of pure rose seed oil and samples mixed with different proportions of common inexpensive vegetable oils (such as soybean oil and sunflower seed oil). After adaptive spectral preprocessing of the original spectrum, principal component analysis (PCA) was used for feature extraction and dimensionality reduction, and a support vector machine classification model (SVC) was constructed to identify pure vegetable oil and adulterated rose seed oil. Then, the XGBoost regression optimization model was used to predict the adulteration ratio. The research results indicate that Raman spectroscopy can effectively capture the characteristic fingerprint information of rose seed oil and its adulterated substances, especially the key spectral peaks of fatty acid composition differences (such as C=C stretching vibration, C—H deformation vibration, etc.). Under the dual model collaborative architecture of PCA-SVC and XGBoost regression, the classification accuracy of pure vegetable oil and adulterated rose seed oil in the test set is as high as 98.18%, and the adulteration ratio can be effectively quantified and predicted (test set determination coefficient R2>0.92, root mean square error RMSE<6.2%). In the detection process, a single spectral acquisition only takes tens of seconds and does not require complex sample pretreatment. This study successfully verified the efficiency and reliability of Raman spectroscopy technology, combined with a dual model collaboration, in the identification of authenticity and quantitative analysis of adulteration in rose seed oil. It provides strong technical support for the development of portable on-site rapid detection equipment, ensuring market fairness and consumer rights, and strengthening oil quality supervision. It has significant practical application value and promotion prospects.
  • FTIR Spectral Response Analysis of Major Components in Tartary Buckwheat under Different Soaking Treatments
    LIU Yan, WANG Jianqiu, WANG Dongdong, XIE Daotong, CHEN Xiaoyan
    Chinese Journal of Light Scattering. 2026, 38(2): 547-561. https://doi.org/10.13883/j.issn1004-5929.202602027
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    This study employed Fourier Transform Infrared Spectroscopy (FTIR) to investigate the structural responses and dissolution behaviors of major functional components—phenolic acids, flavonoids, and proteins—in Tartary buckwheat during different soaking durations. The analytical process followed a systematic spectral loop, including: standard compound construction→original spectral identification→ differential spectral analysis→derivative spectral enhancement→extraction of quantitative variation rates→integrated modeling of composite peaks→multivariate verification. Gallic acid, quercetin, and bovine serum albumin (BSA) were selected as representative compounds to build a “3 major + 2 auxiliary” composite peak model for functional group recognition and peak assignment. The peak intensity (A) and integrated area (S) of each composite peak were extracted, and their average variation rates (ΔAmean, ΔSmean) were calculated to quantify component responses and dissolution tendencies. Two typical functional spectral regions (800~1300 cm-1 and 1600~1800 cm-1) were selected for Principal Component Analysis (PCA) to verify the compositional separation and structural response features at various soaking durations. Results showed that gallic acid exhibited a continuous release pattern, with a ΔAmean of 24.30% and ΔSmean of 8.64% at 60 minutes; quercetin displayed an associative release pattern, with ΔAmean increasing to 24.46% and a consistently negative ΔSmean; BSA demonstrated a rapid release with unchanged conformation, reaching its peak ΔAmean of 19.51% at 10 minutes, while ΔSmean remained within +9% to +15%. The 3D PCA score plots further revealed a temporal spatial evolution pattern characterized by “intense initial migration-mid-term aggregation stability-late-stage slight redistribution,” which confirmed the dissolution mechanisms inferred from the quantitative composite peak model. This study establishes a framework combining composite peak-based average variation rate modeling with spectral region PCA validation, enabling a multidimensional and systematic analysis of dynamic structural responses, release patterns, and spectral migration pathways of complex components in Tartary buckwheat during the infusion process. It provides theoretical reference and technical support for spectroscopic tracking of active ingredients in multi-component systems such as beverages and herbal medicines.
  • Effects of Heat Treatment and Soaking on the Structural Characteristics of Major Components in Cassia Seeds: A Fourier Transform Infrared Spectroscopy (FTIR) Study
    YIN Dedu, WANG Dongdong, ZHANG Yiyang, LI Ziyang, LIU Yan
    Chinese Journal of Light Scattering. 2026, 38(2): 562-576. https://doi.org/10.13883/j.issn1004-5929.202602028
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    This study employed Fourier transform infrared spectroscopy (FTIR) to systematically investigate the effects of heat treatment and hot-water soaking on the molecular structure and functional group vibrations of key bioactive compounds (emodin, quercetin, and gallic acid) in Cassia obtusifolia L. seeds. Reference peak assignment was performed using authentic standards, and spectral analysis included raw FTIR spectra evaluation, difference spectroscopy, and second-derivative spectroscopy, with quantitative assessment based on peak intensity variations and peak area changes. The results demonstrated that heat treatment caused significant reductions in characteristic absorption bands, including a 36.41% decrease in O—H stretching peak area, 31.99% reduction in C=O stretching, and 31.37% reduction in C=C aromatic vibrations, indicating disruption of hydrogen bonding networks and degradation of conjugated systems. In contrast, hot-water soaking progressively enhanced vibrational signals, with C=O groups showing up to 79.67% recovery and C=C bonds exhibiting a 183.3% increase, suggesting hydration-induced structural reorganization. Time-dependent effects were observed, with 10 min soaking achieving 41.46% overall recovery and 30 min soaking reaching 67.39% recovery, while repeated soaking demonstrated cumulative restorative effects. These findings indicate that heat treatment primarily causes structural degradation, while hydration through soaking facilitates molecular rearrangement and partial structural recovery, possibly through reformation of hydrogen bonds. The study confirms FTIR as a sensitive analytical tool for monitoring structural modifications in herbal processing, revealing opposing effects of heat treatment and hydration on molecular structure. These results provide spectroscopic evidence for processing optimization and molecular-level understanding of traditional preparation methods, establishing FTIR-based protocols for quality control in herbal medicine and offering scientific foundation for optimizing traditional preparation techniques.
  • Vertical Characteristics and Evolution of Dust Aerosols over the Taklimakan Desert during 2007-2022: From the Perspective of CALIPSO
    TAN Yahe, ZHANG Haodong, TANG Kun, MA Baodong, GONG Yican, YOU Bowen
    Chinese Journal of Light Scattering. 2026, 38(2): 577-588. https://doi.org/10.13883/j.issn1004-5929.202602029
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    To address the gap in long-term observational data on the vertical characteristics of dust aerosols over the Taklimakan Desert and the limitations of passive remote sensing, this study employs CALIPSO satellite Level 1B and Level 2L data from 2007 to 2022 to investigate the spatiotemporal variation characteristics of dust aerosols. The results indicate that: 1) The backscatter coefficient is highest in spring 0.00198~0.00207 km-1sr-1 and lowest in summer 0.00182~0.00191 km-1sr-1, with interannual changes characterized by fluctuating growth during 2007~2012, stable peak values during 2013~2016, and a return to initial levels during 2017~2022; 2) The extinction coefficient profile exhibits significant vertical differentiation, with high-value areas concentrated at 0~4 km in spring and enriched at 4~6 km in summer, and its interannual variation shows a trend of first increasing and then continuously decreasing, with the contribution ratio of the upper layer (4 km above) dropping to 8%~12% during 2018~2022; 3) The backscatter coefficient and extinction coefficient display segmental correlation under the same spatiotemporal conditions, reflecting the optical property of dust aerosols dominated by scattering; 4) The PM2.5 concentration shows a bimodal pattern in spring and winter and a single trough in summer, exhibiting a moderate correlation with ground observations. This study provides support for the assessment of dust pollution and research on climate effects in arid regions, and multi-source data can be integrated to optimize inversion models in future studies.
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