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Latest:
Rapid Quantitative Method in the Determination of Total Flavonoids in Tibetan Medicine Meconopsis integrifolia (Maxim.) Franch. from Qinghai-Tibet Plateau by Near Infrared SpectroscopyThis study aimed to establish a fast, accurate method for quality evaluation of herbal medicine using NIR and chemometrics with ultraviolet-visible spectrophotometry (UV-vis) as a standard method to determine the total flavonoids content.
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Studying the Source of Raw Material and Glaze Formula of Sky Green “Ru-type Ware” and Ru Kuan Ware by EDXRFAs this study demonstrates, energy-dispersive X-ray fluorescence (EDXRF) and multivariate statistical analysis can be used to distinguish different classes of historical artifacts, such as ancient pottery—revealing insights about theirs origin and uses.
Latest:
A Genetic Algorithm–Optimized Extreme Learning Machine Model for Process Ethylene Analysis Robustness EnhancementTunable diode laser absorption spectroscopy (TDLAS) is combined with an extreme learning machine (ELM) model, tailored by genetic algorithm (GA) parameter searching, to produce a more robust analytical method for trace gas analysis of ethylene.
Latest:
Raman Spectroscopy as a Tool for Rapid Feedback of Perovskite Growth Crystallinity and CompositionPerovskites are known to be useful for fabrication of solar cells, and their crystalline structure plays an important role in their electronic properties. Here, we show how Raman analysis is able to confirm the presence of the required crystalline phase for solar cell production.
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Online ATR-FT-IR for Real-Time Monitoring of the Aspirin Esterification Process in an Acid-Mediated ReactionIn this study, the measured spectra of acetic anhydride, acetic acid, salicylic acid, and aspirin are used for in situ monitoring of the progression of aspirin synthesis in a reaction system. Traditional methods such as HPLC and titration ultraviolet (UV) absorption are not optimal for such real-time monitoring because of long analytical times and complicated procedures. ATR-FT-IR offers an alternative solution that overcomes the shortcomings of traditional techniques.
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Identification and Classification of Degradation-Indicator Grass Species in a Desertified Steppe Based on HSI-UAVUtilizing a low-altitude unmanned aerial vehicle (UAV), a hyperspectral remote-sensing system can identify key grass species indicating grassland degradation, developing an ASI index and classification rules and leveraging spectral differences and plant senescence reflectance to effectively monitor and evaluate grassland conditions and degradation.
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Whisky Analysis with Raman Spectroscopy in the Near-Infrared Spectral Range: Comparison of 785– and 1064–nm ExcitationWe compare the advantages and disadvantages of each laser wavelength.
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An X-ray Fluorescence (XRF) Analysis of a Molecular Layer Deposition (MLD) Method Used in Producing Cement from PhosphogypsumPhosphogypsum can be used as an intermediary material to produce cement clinker. To monitor the quality of phosphogypsum cement, a novel molecular layer deposition X-ray fluorescence (XRF) analysis method using a glass frit was developed.
Latest:
Identification and Classification of Degradation-Indicator Grass Species in a Desertified Steppe Based on HSI-UAVUtilizing a low-altitude unmanned aerial vehicle (UAV), a hyperspectral remote-sensing system can identify key grass species indicating grassland degradation, developing an ASI index and classification rules and leveraging spectral differences and plant senescence reflectance to effectively monitor and evaluate grassland conditions and degradation.
Latest:
Identifying Doxycycline Hydrochloride and Tylosin in Chicken Using Surface-Enhanced Raman SpectroscopyAn increasing number of antibiotic residue problems in food have emerged around the world. We examine how SERS is used to identify antibiotic residues in chicken, focusing on doxycycline hydrochloride and tylosin.
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Study on Estimating Total Nitrogen Content in Sugar Beet Leaves Under Drip Irrigation Based on Vis-NIR Hyperspectral Data and Chlorophyll ContentThe relationship between leaf nitrogen content (LNC) and hyperspectral remote sensing imagery (HYP) was determined to construct an estimation model of the LNC of drip-irrigated sugar beets, to enable real-time monitoring of sugar beet growth and nitrogen management in arid areas.
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Raman Spectroscopy as a Tool for the Quantitative Estimation of Chromium Aluminum Oxide Content in ChromiteRaman measurements of chromite minerals demonstrated that chromium content could be accurately determined, supporting a possible application of portable Raman devices on Earth or in space for mineral analysis of asteroids and planets.
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Raman Spectroscopy in Analyzing Fats and Oils in FoodsSeveral types of Raman spectroscopy, including Fourier transform (FT)–Raman and dispersive Raman, are well suited to examine and understand the fat compositional heterogeneity in solid foods, identify polymorph or crystallinity, and measure fatty acid saturation.
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A Novel Fluorescence Sensor Based on the Tetrakis (4-Carboxyphenyl) Porphyrin (TCPP)-Hg2+ System for Glutathione (GSH) DetectionGlutathione (GSH) is an intracellular thiol that plays a major role in biological systems. Therefore, the development of effective probes that can detect GSH elicits significant attention.
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Nondestructive Spectroscopic Techniques for Detection of Fungal and Mycotoxin Infections in Food Products: A ReviewFungal infections and mycotoxin contamination in food products pose a major threat to the world population. Mycotoxins contaminate approximately 25% of the world’s food products and cause severe health problems through the utilization of affected food products. The major mycotoxins in different foods are aflatoxins, ochratoxins, fumonisins, zearalenone, trichothecenes, and deoxynivalenol. Today, various conventional and nondestructive techniques are available for the detection of mycotoxins across multiple food products. Conventional methods are time-consuming, require chemical reagents, and include many laborious steps. Therefore, nondestructive techniques like near-infrared (NIR) spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, hyperspectral imaging, and the electronic nose are a priority for online detection of fungal and mycotoxin problems in different food products. In this article, we discuss recent improvements and utilization of different nondestructive techniques for the early detection of fungal and mycotoxin infections in various food products.
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Raman Spectroscopy as a Tool for the Quantitative Estimation of Chromium Aluminum Oxide Content in ChromiteRaman measurements of chromite minerals demonstrated that chromium content could be accurately determined, supporting a possible application of portable Raman devices on Earth or in space for mineral analysis of asteroids and planets.
Latest:
Identifying Doxycycline Hydrochloride and Tylosin in Chicken Using Surface-Enhanced Raman SpectroscopyAn increasing number of antibiotic residue problems in food have emerged around the world. We examine how SERS is used to identify antibiotic residues in chicken, focusing on doxycycline hydrochloride and tylosin.
Latest:
Spectroscopic Analysis of the Effects of Alkaline Extractants on Humic Acids Isolated from Herbaceous PeatTo study the effect of various extractants on the structure of peat humic acid, peat humic acid was extracted using NH3·H2O, Na2CO3, NaHCO3, and Na2SO3 via alkali-extraction and acid-precipitation methods.
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EDX and LIBS Studies on Gallstones Using Partial Least Squares Discriminant Analysis (PLS-DA)Understanding gallstone formation requires examining their elemental composition. Here, EDS and LIBS were used with PLS-DA to quantify elements found in human gallstones.
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Influence of Bulk Density on Near-Infrared Spectrum Detection of Cement Raw Materials and Compensation MethodsThis study provides theoretical and technical support for implementing online detection of cement raw meal components using near-infrared (NIR) spectroscopy.
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Raman Spectroscopy Analysis of Minerals Based on Feature VisualizationThe advantages of machine-learning methods have been widely explored in Raman spectroscopy analysis. In this study, a lightweight network model for mineral analysis based on Raman spectral feature visualization is proposed. The model, called the fire module convolutional neural network (FMCNN), was based on a convolutional neural network, and a fire-module was introduced to increase the width of the network, while also ensuring fewer trainable parameters in the network and reducing the model’s computational complexity. The visualization process is based on a deconvolution network, which maps the features of the middle layer back to the feature space. While fully exploring the features of the Raman spectral data, it also transparently displays the neural network feature extraction results. Experiments show that the classification accuracy of the model reaches 0.988. This method can accurately classify Raman spectra of minerals with less reliance on human participation. Combined with the analysis of the results of feature visualization, our method has high reliability and good application prospects in mineral classification.
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Comparative Study of Heavy Metals Analysis in Mongolian Medicines Based on High Sensitivity X-ray Fluorescence Spectroscopy and ICP-MSIn this study, X-ray fluorescence (XRF) spectroscopy was used to analyze heavy metals in five traditional Mongolian medicines, and the results were compared to those obtained using ICP-MS.
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Technological Analysis of Glazed Tiles Unearthed from Bao’ensi in NanjingUV-Vis-NIR can be used to understand how ancient buildings were constructed. Here, a UV-Vis-NIR and EDXRF spectrophotometer were used to analyze glazed tiles that comprised a historical site built in Ancient China.
Latest:
Raman Spectroscopy as a Tool for the Quantitative Estimation of Chromium Aluminum Oxide Content in ChromiteRaman measurements of chromite minerals demonstrated that chromium content could be accurately determined, supporting a possible application of portable Raman devices on Earth or in space for mineral analysis of asteroids and planets.
Latest:
A Genetic Algorithm–Optimized Extreme Learning Machine Model for Process Ethylene Analysis Robustness EnhancementTunable diode laser absorption spectroscopy (TDLAS) is combined with an extreme learning machine (ELM) model, tailored by genetic algorithm (GA) parameter searching, to produce a more robust analytical method for trace gas analysis of ethylene.
