APPLIED SPECTROSCOPY应用光谱学
APPLIED SPECTROSCOPY(英文缩写 APPL SPECTROSC),ISSN 0003-7028,eISSN 1943-3530,中文译名:应用光谱学 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-09-27 至 2026-09-27，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 3.588 | Q1 |
| 2022 | 3.500 | Q1 |
| 2023 | 2.200 | Q2 |
| 2024 | 2.200 | Q2 |
| 2025 | 2.200 | Q2 |
APPLIED SPECTROSCOPY 最新收录文献
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1. Probing Keratin Fiber Aging with Terahertz Time-Domain Spectroscopy: Linking Disulfide Cleavage and Crystallinity Loss.
PMID:日期:2026-09-24Bio-based protein fibers such as cashmere are valued for low weight and thermal insulation but are vulnerable to environmental aging (UV, hygrothermal, alkaline), which undermines hierarchical structure and limits service life in high-demand applications. Rapid, non-destructive assays that bridge chemical fingerprints with crystalline and supramolecular readouts are therefore needed. This study integrates Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray diffraction (XRD), and terahertz time-domain spectroscopy (THz-TDS) to systematically characterize the multiscale aging of cashmere fibers under ultraviolet (UV) and alkaline conditions. Alkaline media preferentially and rapidly induce disulfide (S-S) bond scission, with the Raman I/I ratio dropping from ∼0.65 to 0.15 (≈77% decrease) after 72 h in NaOH, whereas UV irradiation-by virtue of deeper penetration-predominantly compromises interior crystalline domains, reducing the XRD Segal crystallinity index from 0.74 to 0.09 (≈88% decrease) after 600 h. Both pathways drive a common structural evolution characterized by decreased α-helical content, increased amide III disorder (I/I↑), and a net loss of relative crystallinity (alkaline: 0.74→0.52, ≈30% decrease). THz-TDS, via the 1.5 THz absorption, records a concomitant attenuation (from 26.74 to 5.02 under UV, ≈81% decrease; to 8.32 under alkali, ≈69% decrease), indicating that low-frequency collective modes are jointly governed by crystallinity, intermolecular coupling, and chain-segment constraints. These results show that THz-TDS effectively complements FTIR/Raman/XRD, which are less responsive to ensemble interactions, and is therefore well suited for rapid, non-destructive aging assessment and pathway discrimination. In this multimodal framework, THz-TDS serves as an ensemble-level probe that captures low-frequency collective vibrations and intermolecular coupling, thereby complementing the local chemical fingerprints from FTIR/Raman and the crystallinity information from XRD. The proposed multimodal framework provides a methodological basis for durability evaluation and potential online monitoring of protein fibers, and it lays the groundwork for future multimodal quantitative modeling.
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2. Rapid Authentication and Quality Assessment of Fish oil Using Near Infrared Spectroscopy.
PMID:日期:2026-09-24A near-infrared (NIR) spectroscopy-based framework was developed to efficiently evaluate fish oil quality. The workflow focuses on three main objectives: quantification of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), detection of adulteration, and classification of purity. For EPA/DHA quantification, spectra were preprocessed, and partial least squares regression (PLSR) was compared with support vector regression, where PLSR achieved higher accuracy and more stable performance. For adulteration quantification, pure fish oil was spiked with rapeseed, soybean, corn, and palm oils at concentrations ranging from 0% to 50% (w/w). Linear discriminant analysis of NIR spectra revealed distinct separation between pure and highly adulterated samples, with partial overlap at intermediate levels. PLSR models predicted adulterant percentages for all four oils with prediction R values ≥ 0.98 and low error. For purity classification, random forest models based on NIR spectra showed strong performance, and integration of selected gas chromatography variables through mid-level data fusion further improved accuracy to 91.7%. Overall, this NIR-based workflow provides a rapid, nondestructive, and reliable tool for label verification, supplier management, and routine quality assurance in fish oil products.
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3. Synchrotron-Based X-ray Fluorescence Profiling of Asphaltene Deposits: Overcoming Atmospheric and Scattering Interferences for Enhanced Elemental Characterization.
PMID:日期:2026-09-23Asphaltene deposition remains a significant operational challenge in the petroleum industry, requiring precise elemental characterization to understand formation mechanisms and develop mitigation strategies. This study utilizes Synchrotron Radiation X-ray Fluorescence (SR-XRF) at the SESAME facility to profile asphaltene deposits from four southwestern Iranian oil wells. To enhance technical soundness and data reliability, the experimental spectral window was optimized to overcome interferences inherent in long air-path measurements, specifically targeting the mitigation of low-energy atmospheric absorption and high-energy Rayleigh/Compton scattering. A critical spectroscopic evaluation was performed to resolve the spectral overlap between atmospheric Krypton (Kr) emission and the Strontium (Sr) line, enabling a definitive identification of inorganic mineral inclusions. The analysis revealed complex elemental profiles comprising transition metals (Fe, Ni, Cu, Zn) and the heteroatom bromine (Br). Variations in nickel (Ni) intensity across samples suggest its role as a sample-intrinsic component, while high iron (Fe) levels indicate a mix of natural porphyrin complexes and extrinsic mineral contamination. These findings demonstrate that by resolving specific spectral artifacts, SR-XRF serves as a robust, non-destructive analytical tool for the characterization and proactive management of asphaltene-related challenges in petroleum production.
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4. EXPRESS: Comparison of Linear and Nonlinear Regression Models for Dual ED-XRF Analysis of Trace Arsenic and Lead in Rice-Based Foods.
PMID:日期:2026-09-18Applications of energy dispersive X-ray fluorescence (ED-XRF) spectrometry for trace analysis of arsenic (As) and lead (Pb) in foods are limited by spectral interference around characteristic emission lines. To overcome this limitation, various chemometric data modeling approaches can be applied; however, dataset characteristics and model structure can significantly impact these approaches in their ability to accurately relate spectral features to analyte concentrations. This study compared linear and nonlinear multivariate regression models (partial least squares regression (PLSR) and artificial neural network (ANN), respectively) to model the spectral overlap and enable simultaneous analysis of trace As and Pb in rice-based foods. Calibration standards were developed through pelletization of powdered rice (4.0 ± 0.2 g) spiked with As and Pb (∼0-600 µg kg). Standards were analyzed via ED-XRF and resultant spectra were used to develop calibration models utilizing PLSR and ANN modeling. To assess method accuracy and applicability in real-world scenarios, a certified reference material of rice, 11 commercial rice-based products, and 12 Pb-spiked commercial foods were analyzed. PLSR yielded stronger calibration performance (R = 0.98, R = 0.93) compared to ANN; however, ANN modeling achieved lower quantification limits for As in samples containing detectable and non-detectable Pb content (53 µg kg and 54 µg kg, respectively). Both models achieved successful validation in the analysis of the certified reference material with errors of +12.7 % (PLSR) and -19.4 % (ANN) in the prediction of As. PLSR modeling demonstrated strong predictive capabilities in commercial rice-based samples containing non-detectable Pb content, obtaining a median absolute error of 10.7 % in As quantification and 8 of 11 samples yielding less than 20 % error. Conversely, in Pb-spiked commercial samples (76-417 µg kg Pb), the ANN outperformed PLSR, obtaining an average absolute error of 14.1 % with 8 of 12 samples yielding less than 20 % error in As determinations. PLSR modeling correctly identified low Pb content in samples containing non-detectable Pb content while also yielding 75 % accuracy in the classification of samples containing Pb levels above current regulatory limits, supporting its use as a tool for semi-quantitative screening of Pb content in rice/rice-based foods at levels aligning with current regulations. This study compared PLSR and ANN modeling in their ability to statistically model and overcome As/Pb spectral overlap in ED-XRF, highlighting their advantages and limitations in specific analytical scenarios and demonstrating their potential to enable trace As and Pb screening in rice-based foods.
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5. {"_":"EXPRESS: A Novel Er Doped SiO-AlO-NaO-CaO Glass Materials for Near-Infrared Photonic Applications: Unveiling the Structural, Optical Absorption, Optical Bandgap Energy, Photoluminescence, and Spectroscopic Properties.","sup":["3+"],"sub":["2","2","3","2"]}
PMID:日期:2026-09-18Although Er-doped glasses have been shown to be capable of producing an excellent combination of near-infrared and visible emissions; a number of conventional glass matrices are hampered by low levels of solubility for rare earths, concentration quenching, and poor structural uniformity which result in lower than desired optical quality. Furthermore, there is still a lack of systematic understanding regarding how modifications to the structure of aluminosilicate glasses influence their spectroscopic properties. Therefore, this investigation sought to develop and optimize a new series of Er doped AlO-SiO-CaO-NaO aluminosilicate glasses for use as advanced photonic materials, while investigating the relationships between the structure of the glass, the local environment of the rare earth ions within the glass matrix and the overall luminescent response. The glasses were produced via the traditional melt-quenching process and analyzed using Fourier Transform Infrared (FT-IR), optical absorption spectroscopy, Judd-Ofelt (J-O) analysis, and photoluminescence (PL) spectroscopy. Analysis via FT-IR indicated an improvement in the connectivity of the glass structure due to enhancement of both Al-O and O-Si-O vibrational bands present in the glass upon incorporation of Er. XRD confirmed the amorphous nature of the samples, while FT-IR analysis showed that increasing AlO enhances structural connectivity within interconnected AlO and SiO network units. Judd-Ofelt analysis demonstrated the parameter trend Ω > Ω > Ω with the A3 composition achieving the highest Ω value indicating elevated site asymmetry and stronger covalency around Erion. Upon 380 nm excitation, the photoluminescence spectra exhibited weak blue, intense green and orange emissions corresponding to the (H →I), (S →I1), and (F →I1) transitions, respectively, together with a prominent near-infrared emission around 1.55 μm assigned to the (I →I) transition. Additionally, the Judd-Ofelt analysis showed that the A3 glass composition possessed the largest Ω value among all compositions investigated, indicating that it had a greater degree of local structural asymmetry and a stronger level of covalency surrounding each Er ion. PL spectral data further demonstrated a strong intensity of green emission that corresponds to the S→I and I→I transitions. The radiative lifetime, quantum efficiency, and additional radiative parameters measured for the A3 glass composition also demonstrated that it possessed superior optical properties compared to the other compositions studied. The superior luminescence observed for the A3 glass composition was attributed to a higher degree of dispersion of the rare earth ions throughout the glass matrix, lessened effects of concentration quenching, and an optimal degree of modification of the aluminosilicate network. Overall, these results demonstrate that optimized Er doped aluminosilicate glasses provide good combinations of structural and spectroscopic properties and could therefore serve as suitable materials for use in the production of optical fiber and wave guide amplifiers, integrated photonic circuits, eye safe lasers, optical sensors, visible up conversion devices, and future generations of wide band optical communication systems. Hence, the optimized A3 sample exhibited superior radiative properties and enhanced luminescence performance confirming its potential for optical fiber amplifiers, planar waveguides, and photonic systems.
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6. A Low-Cost 3D-Printed Ocular Microspectrophotometer for Teaching Visible Spectroscopy.
PMID:日期:2026-09-16Visible microspectrophotometry enables the nondestructive acquisition of spectral information from microscopic regions and constitutes a valuable tool for the experimental teaching of spectroscopy, microscopy, and optical instrumentation. This work presents the design, fabrication, and evaluation of a low-cost ocular microspectrophotometer (OMP), developed using 3D printing and designed for integration with conventional optical microscopes. The device incorporates a diffraction grating, optical apertures, and a CMOS sensor to acquire continuous spectra over the 433-827 nm wavelength range from microscopic regions approximately 40 µm in diameter. In addition, a Python-based algorithm was developed to convert spectral images into transmittance vectors and calibrate the pixel-to-wavelength relationship. The system achieved a spectral resolution of approximately 0.84 nm/pixel and was validated using reference optical filters. Its educational potential was demonstrated through the spectral characterization of the RGB subpixels of a smartphone LCD screen and the analysis of the transmittance of a plant leaf. These activities provide an effective means of introducing concepts such as additive color synthesis, spatial resolution, light-matter interaction, and digital image processing. The OMP constitutes an accessible and reproducible platform that integrates additive manufacturing, digital image processing, and hands-on experimentation for teaching spectroscopy, microscopy, and the design of scientific instrumentation.
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7. EXPRESS: Detection of Food Contamination Using a Hybrid Raman and Laser-Induced Breakdown Spectroscopy (LIBS) System.
PMID:日期:2026-09-07Due to the prevalence of food fraud and its associated risks to human health, food safety and quality assurance systems must become more comprehensive, rapid, and accurate. Food fraud often involves contamination, which refers to the presence of harmful substances in food, including biological, chemical, and physical adulterants. Traditional detection methods, such as microbiological and chemical testing, are limited in sensitivity, are time-consuming, and often lack comprehensive analysis capabilities. This report presents the development of a hybrid Raman and laser-induced breakdown spectroscopy (LIBS) system, referred to as Hy-R-LIBS, for the quantitative analysis of food contaminants on fruit surfaces. In this work, the term denotes a system in which both spectroscopic modalities are co-housed within a single optical chassis, share a common optical path, and perform automated sequential acquisition on the same sample spot, enabling either independent or joint analysis of the resulting spectra. Raman spectroscopy provides molecular fingerprinting capability, while LIBS enables elemental analysis at low concentrations. The miniaturization of the combined system is feasible because Raman and LIBS share similar optical pathways. To overcome the inherently weak Raman scattering cross-section that limits sensitivity in portable systems, a surface-enhancement strategy based on silver nanoparticles (AgNPs) was employed, which improves both Raman scattering signals and LIBS plasma emission. The study demonstrated that AgNP-assisted surface enhancement improves both LIBS and Raman signals, as confirmed by the quantitative analysis of food contaminants on fruit peel. Pesticide and heavy -metal controls were used, and the limit of detection (LOD) for various contaminants was estimated. The results indicate the feasibility of the hybrid system and the enhancement achieved through surface-enhancement techniques. Overall, the Hy-R-LIBS system offers a promising approach for the quantitative analysis of food contaminants. The combination of these optical spectroscopic techniques enables comprehensive investigations of complex food matrices contaminated with both organic chemicals and metallic residues, providing valuable insights for food safety assurance and public health.
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8. Enhanced SVD for Signal-Noise Separation in Spectroscopic Data.
PMID:日期:2026-09-07Singular Value Decomposition (SVD) is a primary tool for exploratory analysis and for separating signal from noise and background in spectroscopic data, but it does not account for baseline variation. Standard SVD can assign to baseline features singular values comparable in magnitude to those of genuine chemical components, obscuring the boundary between signal and noise in the singular value spectrum and complicating determination of the chemical rank. This Note describes a preprocessing-enhanced SVD algorithm in which a Fourier-domain first-derivative transformation is combined with weights derived from the noise present in the data before the decomposition is performed, suppressing baseline contributions without loss of true signal components. The abstract spectra and time-traces are returned to the original spectral and temporal domains by inverse transformation, and a sign-ambiguity resolution procedure based on correlation coefficients is included. The algorithm is demonstrated on both synthetic and experimental time-dependent FTIR spectroscopic data. Relative to standard SVD, the enhanced decomposition yields a flat noise floor beyond the retained components, confining the baseline contribution to the discarded subspace rather than dispersing it through the low-rank subspace, and the recovered abstract spectral and temporal vectors carry less baseline contamination. Although demonstrated with time-dependent FTIR data, the algorithm applies to any variable-dependent spectroscopic measurement that can be organized as a two-way matrix. The implementation is released as open-source software.
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9. Advancements in NIR Spectroscopy: A Comparative Assessment of Portable and Benchtop NIR Devices for Analyzing Fermentation-Derived Foods.
PMID:日期:2026-09-07This study evaluates the performance of portable (P-NIR) and benchtop (B-NIR) NIR spectrometers in providing useful information for assessing key physicochemical parameters in fermentation-derived foods, including wines, beers, and vinegars. Using chemometric techniques such as PLS and PLS-DA, models were developed to predict and classify sample characteristics with high accuracy. The P-NIR device demonstrated comparable performance to the B-NIR spectrometer in specific applications, highlighting its potential for cost-effective on-site analyses without the need for sample preparation. Parameters such as acidity, pH, polyphenol content, and specific indicators like alcohol content and bitterness were effectively measured, while classification models successfully differentiated wine varieties, origins, and production methods. This study underscores the versatility and accessibility of P-NIR technology, paving the way for its broader adoption in quality control processes within the food industry.
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10. Time-Gated Raman Spectroscopic Characterization of Fluorescent Polyethylene Microplastics.
PMID:日期:2026-09-04Microplastics (MPs) have become increasingly common in nearly every natural environment. As their pervasiveness grows, so does the urgency to understand their abundance and origins. Raman spectroscopy has been used to identify MPs in natural environments. However, fluorescence from additives within MPs, other environmental matter, measurement substrates, or other factors can prevent MP identification. Polyethylene (PE) subtypes such as low-density, high-density, and ultra-high molecular weight polyethylene (LDPE, HDPE, and UHMWPE) have widely varying uses and origins ( residential, industrial). In this work, we demonstrate a technique using time-correlated single photon counting (TCSPC) Raman spectroscopy to isolate the Raman signal of microplastics from competing fluorescence. Fluorescence suppression reduces spectral noise and improves quantitative spectral analysis. Decomposing Raman spectra using Voigt profiles enables quantification of PE crystallinity and estimation of its density. In artificially fluorescent and environmental samples, TCSPC Raman spectroscopy improved visualization of weak spectral features and calculation of PE crystallinity compared with continuous-wave (CW) Raman spectroscopy. For an environmental PE MP sample, CW Raman-derived crystallinity estimates often exceeded 100%. These non-physical values were attributed to a significant fluorescence background and low signal-to-noise ratio. In contrast, TCSPC measurements produced crystallinity estimates of 55-70% and 65-80% at two sampled locations on the MP. These results show the potential to quantitatively characterize MPs with TCSPC Raman spectroscopy. The ability to identify the subtype of PE MPs could assist in identifying the sources of microplastic pollution to protect natural environments.