Vibrational Spectroscopy最新文献

Study on liquid core optical fiber enhanced Raman scattering and micro detecting liquid-phase joint synovial fluid 液芯光纤增强拉曼散射及液相关节滑液微检测研究

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-12-10 DOI: 10.1016/j.vibspec.2025.103879

Jinjin Wu , Jiachun Dong , Shuang Xiong , Linwei Shang , Huijie Wang , Jianhua Yin

The low concentration and weak Raman activity of synovial fluid (SF) make it difficult to be detected in the liquid-phase by conventional Raman spectroscopy. Therefore, liquid-core optical fiber enhanced Raman scattering (LCOF-ERS, LERS) was introduced to detect liquid-phase SF since its obvious scattering enhancement. This study reveals that when the LCOF material (refraction index, RI) and length are determined to collect LERS spectra of ethanol solution, the LERS performance increases with decreasing both the objective lens magnification and the LCOF inner diameter (ID). It reaches optimum at 4 × objective and 200μm ID, which was set for LERS measurement of SF. It’s found that the SNR of the LERS (4 ×/200-ID) spectra of the liquid-phase SF is 15.3 times of the conventional Raman spectra, simultaneously avoiding the spectral distortion and molecular configuration change caused by the phase change of SF. Moreover, the enhancement factor of LERS increases from 6.5 to 25.6 by diluting 10 times with water, confirming that LERS is highly feasible and worth expecting for the practical detection of micro-SF with low-RI. The significant enhancements for LERS in intensity and Signal to Noise Ratio (SNR) are very helpful to facilitate the micro clinical detection, disease diagnosis and scientific research of SF and other bodily fluids in liquid.

滑液的低浓度和弱拉曼活性使得常规拉曼光谱难以在液相中检测到滑液。因此，由于液芯光纤增强拉曼散射（LCOF-ERS， LERS）具有明显的散射增强作用，因此引入了液芯光纤增强拉曼散射（LCOF-ERS）来检测液相SF。本研究表明，当确定LCOF材料（折射率，RI）和长度时，随着物镜倍率和LCOF内径（ID）的减小，LERS的性能增加。在4 × 物镜和200μm的孔径下达到最佳，该孔径为光谱线测量孔径。发现液相SF的LERS（4 ×/200-ID）光谱的信噪比是常规拉曼光谱的15.3倍，同时避免了SF相变引起的光谱畸变和分子构型改变。此外，经10倍水稀释后，LERS的增强因子从6.5增加到25.6，证实了LERS在低ri微sf的实际检测中是高度可行的，值得期待。LERS在强度和信噪比（SNR）方面的显著增强，对SF等体液在液体中的微观临床检测、疾病诊断和科学研究非常有帮助。

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引用次数: 0

Multivariable prediction of concentration and temperature pressure from absorption spectra using B-LSTM-transformer model 基于b - lstm变压器模型的吸收光谱多变量浓度和温度压力预测

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-11-29 DOI: 10.1016/j.vibspec.2025.103876

Hongda Chen

Direct absorption spectroscopy is extensively utilized in combustion diagnostics, offering valuable assistance in industrial production and aerospace applications. However, current approaches for processing substantial volumes of overlapped spectra encounter challenges related to slow processing speeds and inadequate precision. This research introduces a time series prediction model that integrates a Transformer self-attention mechanism with Long Short-Term Memory networks for spectroscopy and thermodynamic diagnostics, as well as spectral prediction in absorption spectroscopy. The proposed model proficiently adeptly captures spectral characteristics, including concentration, temperature, and pressure, from intricate unknown spectra. The model was verified in TDLAS. The prediction standard deviation for simulated spectra is less than 0.1, while the relative error for actual spectra is less than 1 %. Future advancements may involve the integration of spectral denoising and analysis techniques, along with few-shot learning methods, validation and optimization of the use of broadband spectrometers, to further optimize combustion gas detection solutions in industrial and aerospace domains.

直接吸收光谱法广泛应用于燃烧诊断，为工业生产和航空航天应用提供了宝贵的帮助。然而，目前处理大量重叠光谱的方法遇到了处理速度慢和精度不足的挑战。本文介绍了一种时间序列预测模型，该模型集成了变压器自关注机制和长短期记忆网络，用于光谱学和热力学诊断，以及吸收光谱学中的光谱预测。该模型能够从复杂的未知光谱中熟练地捕获光谱特征，包括浓度、温度和压力。在TDLAS中对模型进行了验证。模拟光谱的预测标准差小于0.1，实际光谱的相对误差小于1 %。未来的进展可能涉及光谱去噪和分析技术的集成，以及少量学习方法，验证和优化宽带光谱仪的使用，以进一步优化工业和航空航天领域的燃烧气体检测解决方案。

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引用次数: 0

Can we use visible-near infrared and mid infrared spectroscopy as a tool for wetland soil identification? 我们能否利用可见-近红外和中红外光谱作为湿地土壤识别的工具？

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-11-29 DOI: 10.1016/j.vibspec.2025.103875

Caleb R. Whatley , Nuwan K. Wijewardane , Chamika A. Silva , Mary Love Tagert , Raju Bheemanahalli , Prem Parajuli

The wetland delineation process is primarily based on the visual recognition of anaerobic soil indicators by trained individuals, and is a complex and subjective task that is prone to error. Therefore, an objective alternative is needed to identify wetland soil; however, no such method currently exists that is rapid and easy to deploy. Accordingly, the objective was to evaluate soil spectroscopic classification approach as a rapid, deployable alternative by testing its feasibility to differentiate wetland from non-wetland soils. This study used visible-near infrared and mid-infrared (MIR) ranges for this task. A total of 440 wetland and non-wetland soils were sampled across Mississippi followed by obtaining visible/near-infrared and MIR spectra under both fresh and dried conditions. Support Vector Classification (SVC) and Random Forest (RF) methods were then used to classify spectra based on wetland/non-wetland status with a 75 %/25 % calibration and validation split. This split was repeated for 50 iterations to obtain randomized calibration and validation sets for model calibration and achieve average model performance. The average classification accuracy across all models was ∼91 %, with the highest accuracy of 99.6 % achieved on MIR spectra. The accuracy, precision, and recall scores showed similar performances between SVC and RF ranging their values from ∼80 % - 100 %. This study showed the reliability and ease of wetland determinations using spectroscopy as an objective and rapid wetland recognition method, while reducing the need for an expert for determination.

湿地圈定过程主要基于训练有素的人员对厌氧土壤指标的视觉识别，这是一项复杂而主观的任务，容易出错。因此，需要一种客观的替代方法来识别湿地土壤；然而，目前还不存在这种快速且易于部署的方法。因此，我们的目标是通过测试土壤光谱分类方法区分湿地和非湿地土壤的可行性，来评估土壤光谱分类方法作为一种快速、可部署的替代方法。这项研究使用了可见-近红外和中红外（MIR）范围来完成这项任务。在美国密西西比州共采集了440个湿地和非湿地土壤样本，获得了新鲜和干燥条件下的可见光/近红外光谱和MIR光谱。然后使用支持向量分类（SVC）和随机森林（RF）方法对基于湿地/非湿地状态的光谱进行分类，校准和验证分割率为75% %/25 %。此分割重复50次迭代，以获得用于模型校准的随机校准和验证集，并获得平均模型性能。所有模型的平均分类准确率为~ 91 %，MIR光谱的最高准确率为99.6 %。准确度、精密度和召回率得分在SVC和RF之间表现出相似的性能，其值范围为~ 80 % - 100 %。本研究表明，光谱法作为一种客观、快速的湿地识别方法，具有可靠性和易用性，同时减少了对专家的测定需求。

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引用次数: 0

Fingerprint Raman spectroscopy for identification of hydration-dependent Brillouin shift variations in brain tumor tissue 指纹拉曼光谱识别脑肿瘤组织中水合依赖的布里渊位移变化

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-11-01 DOI: 10.1016/j.vibspec.2025.103866

Jan Rix , Tina Leonidou , Achim Temme , Ortrud Uckermann , Roberta Galli

The Brillouin shift is a measure of the longitudinal elastic modulus, which is both sensitive to changes in water content and elasticity of the solid part of cells and tissues. Raman spectroscopy can be combined with Brillouin spectroscopy to provide biochemical information. In this study, the Raman signal intensity in the fingerprint region was evaluated to extract additional information about tissue hydration and relate it to the Brillouin shift. Simultaneous and colocalized confocal Brillouin and Raman spectroscopy was performed with laser excitation at 780 nm. Solutions of relevant biomolecules (albumin and sucrose) and gels (gelatin and agarose) with different concentrations up to 30 % as well as glioblastoma organoids and human brain tissue were probed, and the Raman intensity in the spectral region 800 – 1500 cm⁻¹ and Brillouin shift was investigated. A strong linear correlation was found between Raman signal intensity, mass concentration and Brillouin shift for all analyzed solutions and gels, while different mixtures with the same total concentrations had similar Raman intensities. Different degrees of correlation were found between Brillouin shift and Raman intensity on GBM organoids, human brain tissue (epileptic hippocampus) and brain tumor (meningioma), indicating different contributions of tissue hydration and biomechanics to the Brillouin shift. In conclusion, combining fingerprint Raman spectroscopy with Brillouin microscopy is not only useful for extracting biochemical information that highlights changes in Brillouin parameters, but may also provide insight into the effects of local hydration driving the changes of Brillouin shift.

布里渊位移是纵向弹性模量的量度，它对细胞和组织的固体部分的含水量和弹性的变化都很敏感。拉曼光谱可以与布里渊光谱相结合，提供生物化学信息。在这项研究中，评估指纹区域的拉曼信号强度，以提取有关组织水化的额外信息，并将其与布里布鲁因位移联系起来。在780 nm激光激发下进行同步共聚焦布里渊和拉曼光谱。对相关生物分子（白蛋白和蔗糖）、凝胶（明胶和琼脂糖）溶液（浓度高达30 %）以及胶质细胞瘤类器官和人脑组织进行探针，研究800 - 1500 cm⁻¹ 光谱区域的拉曼强度和布里温位移。在所有被分析的溶液和凝胶中，拉曼信号强度、质量浓度和布里渊位移之间存在很强的线性相关性，而不同的总浓度相同的混合物具有相似的拉曼强度。在GBM类器官、人脑组织（癫痫性海马）和脑肿瘤（脑膜瘤）上，布里渊位移与拉曼强度存在不同程度的相关性，表明组织水化和生物力学对布里渊位移的贡献不同。综上所述，将指纹拉曼光谱与布里渊显微镜相结合，不仅有助于提取布里渊参数变化的生化信息，而且可以深入了解局部水合作用对布里渊位移变化的影响。

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引用次数: 0

Influence of the computational methods in the conformational assignment of experimental infrared spectra 计算方法对实验红外光谱构象分配的影响

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-11-01 DOI: 10.1016/j.vibspec.2025.103863

Roel van de Ven, Herma M. Cuppen, Daria R. Galimberti

Recent advancements in experimental techniques have provided spectra for single conformers for relatively large flexible molecules, creating an ideal environment to benchmark computational methods on their ability to identify the conformers responsible for the experimentally measured spectra. Here, we performed benchmarks of different functionals and basis sets using three molecules: diphenylalanine, delta-9-tetrahydrocannabinol, and the 3-O-Acetyl-2,4,6-tri-O-methyl-gluco-D-pyranosyl cation. For this task, a new type of spectral similarity score was introduced, the Logarithmic Convoluted Cosine Similarity (LCCS), which is able to quantify spectral differences in terms of both frequency and intensity mismatches. Our results show that, as long as hybrid functionals are selected, the most crucial factor for the correct conformer assignment is the basis set. In particular, polarization functions were found to play a crucial role. We analyzed three additional aspects of the problem: the scan of the potential energy surface to find candidate conformers, pre-optimization of candidate conformers, and the selection from the pool of conformers based on the energy. Our data indicate that for scanning the potential energy surface, the DFTB3 semi-empirical method is a good compromise between accuracy and low computational cost. For the pre-optimization, we found that GGA functionals and a small basis set with a polarization functional already achieve sufficient accuracy. Instead, in the pre-selection based on energy, hybrid functionals should be preferred, and in any case, an energy window of at least 15 kJ/mol should be employed for the conformer selection.

实验技术的最新进展为相对较大的柔性分子提供了单一构象的光谱，创造了一个理想的环境，以基准计算方法识别实验测量光谱的构象的能力。在这里，我们使用三种分子：二苯丙氨酸、德尔塔-9-四氢大麻酚和3- o-乙酰基-2,4,6-三- o-甲基-葡萄糖- d -吡喃基阳离子，对不同的功能和基集进行了基准测试。为此，引入了一种新的频谱相似度评分，即对数卷积余弦相似度（LCCS），它能够从频率和强度两方面量化频谱差异。结果表明，在选择混合泛函的情况下，基集是决定正确赋形体的最关键因素。特别是发现极化函数起着至关重要的作用。我们还分析了该问题的另外三个方面：扫描势能面寻找候选构象，候选构象的预优化以及基于能量的构象池选择。我们的数据表明，对于扫描势能面，DFTB3半经验方法在精度和低计算成本之间取得了很好的折衷。对于预优化，我们发现GGA泛函和一个带有极化泛函的小基集已经达到了足够的精度。相反，在基于能量的预选择中，应优先选择混合官能团，并且在任何情况下，应使用至少15 kJ/mol的能量窗口来选择构象。

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引用次数: 0

Research on quantitative analysis of single-component hydrocarbon gases based on optimized SVR with double-local strategy 基于双局部优化SVR策略的单组分烃类气体定量分析研究

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-11-01 DOI: 10.1016/j.vibspec.2025.103865

Gang Liu , Peng Han , Hai Yang , Yilin Yao , Haibo Liang

Accurate measurement of gas concentrations in drilling fluids is essential for effective gas logging in drilling engineering, as both accuracy and speed significantly influence real-time monitoring and decision-making. To address the limitations of on-site infrared spectroscopy for single-component gas measurements—such as model mismatches, redundant wavenumbers across broad spectral ranges, and substantial concentration fluctuations that lead to slow processing and large errors, which fail to meet gas logging needs—this study introduces an optimized solution. The approach involves modifying the measurement model, utilizing local characteristic wavenumbers to eliminate redundant spectral information, and dividing local calibration sets to reduce the effects of concentration fluctuations. A novel modeling technique is developed by enhancing Competitive Adaptive Reweighted Sampling (CARS) with Interval Random Frog (IRF) and combining it with the Beetle Antennae Search (BAS) algorithm to optimize Support Vector Regression (SVR). Experimental results demonstrate that the proposed IRF-CARS-BAS-SVR method significantly outperforms traditional techniques in the quantitative analysis of single-component hydrocarbons, achieving an average prediction accuracy exceeding 98 %. This method improves both the speed and precision of infrared-based quantification of single-component gases and has been successfully deployed at various drilling sites, meeting operational requirements for gas logging.

在钻井工程中，准确测量钻井液中的气体浓度对有效的气体测井至关重要，因为准确性和速度对实时监测和决策具有重要影响。为了解决现场红外光谱用于单组分气体测量的局限性，例如模型不匹配，宽光谱范围内的冗余波数，以及导致处理缓慢和误差大的浓度波动，这些都不能满足气体测井的需求，本研究引入了一种优化的解决方案。该方法包括修改测量模型，利用局部特征波数消除冗余的光谱信息，划分局部校准集以减少浓度波动的影响。提出了一种基于区间随机蛙（IRF）的竞争自适应重加权抽样（CARS）算法，并结合甲虫天线搜索（BAS）算法优化支持向量回归（SVR）的建模方法。实验结果表明，所提出的IRF-CARS-BAS-SVR方法在单组分烃定量分析方面明显优于传统技术，平均预测精度超过98 %。该方法提高了基于红外的单组分气体定量的速度和精度，并已成功应用于多个钻井现场，满足了气测井的作业要求。

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引用次数: 0

A PCA-UVE based feature selection strategy for nutritional component quantification in milk powder using Raman spectroscopy 基于PCA-UVE的拉曼光谱定量奶粉营养成分特征选择策略

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-11-01 DOI: 10.1016/j.vibspec.2025.103867

Xiangchu Li , Yu Ding , Jianan Xu , Yihua He , Qiang Tan , Maoyuan Pang , Weiye Yu , Jinyi Li , Guang Yang , Xinxin Liu

Ensuring the rapid and accurate assessment of nutritional components in milk powder is essential for quality control in the dairy industry. In this study, a Raman spectroscopy-based analytical framework is proposed, integrating principal component analysis (PCA) and uninformative variable elimination (UVE) for feature selection, to optimize spectral modeling and enhance detection performance. A portable Raman system was employed to acquire spectra from 40 commercial milk powder samples, including skimmed, low-fat, and full-fat variants. PCA was initially used to reduce dimensionality and identify informative spectral regions, which were further refined using UVE to eliminate redundant features. The optimized spectral subset was utilized to construct partial least squares regression (PLSR) models for fat and protein prediction, achieving R² values of 0.9865 and 0.9751, respectively, with substantial reductions in RMSE_P and computational cost. Compared to full-spectrum models, the proposed approach reduced processing time by over 70 %, while maintaining high prediction accuracy. This study demonstrates the potential of integrating advanced chemometric methods with Raman spectroscopy for efficient, real-time nutritional analysis in milk powder quality monitoring.

确保奶粉营养成分的快速准确评估是乳品行业质量控制的关键。本文提出了一种基于拉曼光谱的分析框架，结合主成分分析（PCA）和无信息变量消除（UVE）进行特征选择，以优化光谱建模，提高检测性能。采用便携式拉曼系统采集40种商业奶粉样品的光谱，包括脱脂、低脂和全脂变体。该方法首先利用主成分分析（PCA）降维并识别信息丰富的光谱区域，然后利用UVE对光谱区域进行进一步细化以消除冗余特征。利用优化后的谱子集构建脂肪和蛋白质预测的偏最小二乘回归（PLSR）模型，R²值分别为0.9865和0.9751，RMSEP和计算成本大幅降低。与全谱模型相比，该方法在保持较高预测精度的同时，减少了70%以上 %的处理时间。本研究展示了将先进的化学计量方法与拉曼光谱相结合，在奶粉质量监测中进行高效、实时营养分析的潜力。

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引用次数: 0

In-situ SERS monitoring of light-gated reaction switching on magnetic-plasmonic CoFe2O4@TiO2@Ag nanorods 磁等离子体CoFe2O4@TiO2@Ag纳米棒上光门控反应开关的原位SERS监测

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-11-01 DOI: 10.1016/j.vibspec.2025.103864

Shuang Wang , Zian Li , Wei Lv , Guolin Zhang , Xiaoqi Fu , Juan Yang

Here, we fabricate magnetically recyclable CoFe₂O₄@TiO₂@Ag nanorods (NRs) for in-situ surface-enhanced Raman scattering (SERS) monitoring of light-gated catalytic pathways. The hierarchical structure, comprising a magnetic CoFe₂O₄ NR core, a TiO₂ interlayer, and Ag nanoparticles (NPs) shell, enables the SERS detection of rhodamine 6 G (R6G) at a low concentration of 10⁻⁸ mol L⁻¹ with excellent signal reproducibility. In-situ SERS reveals distinct reduction mechanisms for 4-nitrothiophenol (4-NTP) governed by the excitation wavelength. Under 532 nm visible laser irradiation, plasmon-induced hot electrons from Ag NPs drive the selective conversion of 4-NTP to trans-dimercaptoazobenzene (DMAB) with a rate constant of 0.118 min⁻¹. In contrast, under 365 nm UV light, TiO₂-mediated electron transfer promotes the formation of cis-DMAB at a rate constant of 0.034 min⁻¹. Reversible cis-trans isomerization is achieved by alternating the light sources. This work establishes CoFe₂O₄/TiO₂/Ag NRs as a versatile platform for monitoring light-gated catalysis in real time, with promising applications in energy conversion, environmental remediation, and selective chemical transformations.

在这里，我们制造了磁性可回收的CoFe2O4@TiO2@Ag纳米棒（nr），用于光门控催化途径的原位表面增强拉曼散射（SERS）监测。由磁性CoFe2O4 NR核、TiO2中间层和Ag纳米颗粒（NPs）壳组成的分层结构，使罗丹明6 G （R6G）在低浓度（10−8 mol L−1）下的SERS检测具有良好的信号再现性。原位SERS揭示了4-硝基苯酚（4-NTP）在不同激发波长下的不同还原机制。在532 nm可见激光照射下，Ag纳米粒子的等离子体诱导热电子驱动4-NTP选择性转化为反式二巯基偶氮苯（DMAB），速率常数为0.118 min−1。相反，在365 nm紫外光下，tio2介导的电子转移促进顺式dmab的形成，速率常数为0.034 min−1。可逆顺反异构化是通过交替光源实现的。这项工作建立了CoFe2O4/TiO2/Ag NRs作为实时监测光门控催化的多功能平台，在能量转换，环境修复和选择性化学转化方面具有广阔的应用前景。

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引用次数: 0

Standardized protocol for unstimulated saliva analysis by ATR-FTIR spectroscopy ATR-FTIR光谱分析非刺激唾液的标准化方案

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-10-22 DOI: 10.1016/j.vibspec.2025.103862

Maricela Toro-Alzate , Ana Isabel Cañas-Gutierrez , Monica Tatiana Parada-Sanchez

Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy has gained relevance as a non-invasive technique for analyzing the biochemical composition of biofluids such as saliva, with increasing interest in clinical diagnostics. However, spectral quality and repeatability are strongly influenced by sample preparation, saliva type, and drying method. This study aimed to standardize a protocol for the collection, processing, and spectroscopic acquisition of unstimulated saliva. Spectra were obtained from liquid, lyophilized, and air-dried samples of both whole and clarified saliva.

Liquid samples exhibited strong water absorption, masking characteristic biomolecular bands. Lyophilization produced macroscopically heterogeneous residues, resulting in variable band intensity and poor repeatability. In contrast, air-drying at room temperature yielded uniform and reproducible spectra, with 3 µL identified as the optimal sample volume. Clarified saliva, obtained by centrifugation, produced spectra with sharper and more consistent biomolecular bands, particularly in the Amide II region, by reducing biological noise from cells and particulate matter. Although signal intensity and SNR values were lower, these changes reflected reduced scattering rather than molecular loss. The Wilcoxon test confirmed significant differences between sample types only for the Amide II region (p < 0.05).

Overall, air-dried clarified saliva provides a clean, stable, and reproducible spectral matrix, supporting its suitability for reliable biochemical and diagnostic ATR-FTIR applications.

衰减全反射傅里叶变换红外光谱（ATR-FTIR）作为一种非侵入性技术，在分析唾液等生物流体的生化成分方面已经获得了相关性，在临床诊断方面的兴趣越来越大。然而，光谱质量和可重复性受到样品制备、唾液类型和干燥方法的强烈影响。本研究旨在标准化非刺激唾液的采集、处理和光谱采集方案。光谱从液体、冻干和风干的整个唾液和澄清唾液样品中获得。液体样品表现出很强的吸水性，掩盖了特征的生物分子带。冻干产生宏观上不均匀的残基，导致条带强度变化，重复性差。相比之下，室温风干得到均匀且可重现的光谱，确定3 µL为最佳进样量。通过离心获得的澄清唾液，通过减少来自细胞和颗粒物质的生物噪声，产生了具有更清晰和更一致的生物分子带的光谱，特别是在酰胺II区。虽然信号强度和信噪比值较低，但这些变化反映的是散射减少，而不是分子损失。Wilcoxon检验证实，样品类型之间仅在Amide II区域存在显著差异（p <； 0.05）。总的来说，风干澄清唾液提供了一个干净，稳定，可重复的光谱矩阵，支持其适用于可靠的生化和诊断ATR-FTIR应用。

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引用次数: 0

Throughput-enhanced grating spectrometers for fiber-optic Raman detection with deep learning-based spectral recovery 基于深度学习光谱恢复的光纤拉曼检测吞吐量增强光栅光谱仪

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-10-20 DOI: 10.1016/j.vibspec.2025.103860

Huijie Wang, Xu Liu, Zichun Yang, Lang Huang, Xinhang Lou, Jianbo Zhu, Linwei Shang, Jianhua Yin

Grating spectrometers are widely utilized to perform the single-shot spectral measurement with relatively high performance, while inherently suffering from a conflict between optical throughput and spectral resolution. As a key component, the entrance slit is required to be narrow for high spectral resolution, inevitably limiting the optical throughput and typically hindering the ultra-weak Raman detection. In this work, the deep learning-based spectral recovery has been proposed and preliminarily explored to numerically eliminate the spectral broadening along with a wider slit in a rapid and accurate way, without demand for complicated physical modification and time-consuming iterative calculation. Given the possible influence of spectral complexity on the spectral recovery, spectral reconstruction is performed in parallel with a set of generative adversarial networks (GANs), following the spectral segmentation and classification in terms of peak number with a convolutional neural network (CNN). For instance, the spectral recovery has been performed on the fiber-optic Raman detection of common drugs, where all the core diameters of excitation and collection fibers are

200 μ m

and far larger than the detector pixel width of

15 μ m

. Through the combination of CNN classification and GAN reconstruction, low-resolution spectra of the 200-

μ

m-width slit with

\sim

7 times higher throughput can be recovered to coincide well with those of the 15-

μ

m-width slit, achieving the optimal spectral resolution. Moreover, the signal-to-noise ratio can be improved by

\sim

3 times on average, promoting more efficient weak-light detection with the flexible fiber-optic probes.

光栅光谱仪被广泛应用于单次光谱测量，具有较高的性能，但其固有的缺点是光学吞吐量和光谱分辨率之间存在冲突。入口狭缝作为关键器件，为了实现高光谱分辨率，需要窄的狭缝，这不可避免地限制了光吞吐量，通常会阻碍超弱拉曼检测。本文提出并初步探索了基于深度学习的光谱恢复方法，在数值上快速准确地消除随狭缝变宽而产生的光谱展宽，不需要进行复杂的物理修正和耗时的迭代计算。考虑到光谱复杂性对光谱恢复的可能影响，在使用卷积神经网络（CNN）对光谱进行峰数分割和分类之后，使用一组生成式对抗网络（gan）并行进行光谱重建。例如，对常见药物的光纤拉曼检测进行了光谱恢复，其中激发和收集光纤的芯直径均为200μm，远大于检测器的像元宽度15μm。通过CNN分类和GAN重构相结合的方法，恢复了吞吐量提高约7倍的200 μm宽狭缝的低分辨率光谱，使其与15 μm宽狭缝的低分辨率光谱吻合良好，达到了最佳的光谱分辨率。此外，信噪比可以平均提高约3倍，从而促进柔性光纤探头更有效地检测弱光。

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引用次数: 0