Rapid Identification of Atmospheric Gaseous Pollutants Using Fourier-Transform Infrared Spectroscopy Combined with Independent Component AnalysisRead the full article
Journal of Spectroscopy publishes research into the theory and application of spectroscopy across all disciplines, including biology, chemistry, engineering, earth sciences, medicine, materials science, physics, and space science.
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Sparse Representation for Different Animal Vertebra Classification along the Fixation Trajectory of Pedicle Screw
Pedicle screw (PS) implantation is an ideal method for the treatment of severe multilevel vertebral instability. The key problem is the accuracy of PS fixation. In this paper, the spectrum of different tissues along the fixation trajectory of PS is studied to tackle the accuracy problem. Fresh porcine vertebrae, bovine vertebrae, and ovine vertebrae were measured by using the near-infrared spectrum (NIRs) device to obtain the reflected spectrum from these vertebrae. Along the fixation trajectory of PS, the classification method based on the sparse representation-based classifier (SRC) was applied to different vertebral tissues (cortical bones and cancellous bones). Considering the large amount of spectral data, sparse preserving projection (SPP) was applied to improve the performance of SRC. The proposed method based on the SPP method for dimensionality reduction and the SRC method for tissue recognition was first used in vertebrae classification and showed superior performance compared with other classification methods, such as SVM and 1NN. The results gained from this project are vital significant to the development of hi-tech medical instruments with independent intellectual property rights.
Using PDMS Plasma Cavity SERS Substrate for the Detection of Aspartame
Surface-enhanced Raman spectroscopy (SERS) was used to simply and sensitively detect the artificial sweetener aspartame added to purified water. In this paper, a cavity formed spontaneously by silver ion droplets, and liquid polydimethylsiloxane (PDMS) is used as an SERS substrate to integrate plasma nanoparticles into optical devices. Firstly, Raman spectral characteristics of aspartame powder and aspartame aqueous solution were analyzed. Secondly, the effect of aspartame content in purified water on SERS intensity was investigated by using the prepared PDMS plasma cavity to test the samples. Thirdly, the SERS calibration curve was established by using the characteristic peak intensity of aspartame, and a good linearity relationship between the concentration of aspartame added in purified water and the characteristic peak intensity of 1588(±5) cm-1 was obtained. The linear regression equation and correlation coefficient (r) were y = 11412.73874 x + 107.36722 and 0.99593, respectively. The average recovery of aspartame in purified water was 101–106%, and the relative standard deviation (RSD) was 0.121–0.496%. The experimental results show that using this method can detect aspartame in purified water correctly, which is expected to be used in the identification and detection of sweeteners in purified water.
New Vibrational Information on Simple Amides in Solution: A Case Study on GaCl3-Formamide Complexes
IR and Raman measurements were carried out for GaCl3-formamide (FA) solutions, and comparisons with the Al3+ and Fe3+ chemistry are presented. Upshifts of both νCO and νCN modes of FA are observed, and analyses of the corresponding bands suggest different types of solvatocomplexes. The twisting mode (γHNH) of FA at 1190 cm−1, which is IR- and Raman-inactive, is activated only in the former upon coordination to high electrostatic potential ions. The spectral behavior exhibited in this region is shown for the first time in the literature and has helped in the understanding of the coordinated FA structure. The catalytic power of Ga3+ towards amide bond hydrolysis is also predicted for the first time using vibrational spectroscopy and may be useful for biological studies.
Development of UV Spectrophotometric Procedures for Determination of Amlodipine and Celecoxib in Formulation: Use of Scaling Factor to Improve the Sensitivity
FDA has recently approved a new fixed-dose combination of amlodipine besylate (AMD) and celecoxib (COX) for the treatment of hypertension and osteoarthritis. No analytical method has been reported for analysis of these two analytes so far. Hence, to monitor the quality and quantity in the formulation of AMD and COX a simple, accurate, precise, economical, and eco-friendly spectroscopic analytical method has been established. The first method involves the determination of AMD and COX by the first derivative UV spectroscopic method with scaling factor 10. However, the second method was based on the direct measurement of UV absorbance of AMD at 364.3 nm and ratio first derivative UV spectroscopic method for COX. Both methods showed good linearity in the range of 5 to 40 μg/ml for COX, whereas AMD showed linearity in the range of 0.5 to 10 μg/ml in first derivative method with scaling factor 10 and 1 to 10 μg/ml in the second method with good correlation coefficient (R2 > 0.998). Both the methods were validated for LOD, LOQ, accuracy, precision, recovery studies, and stability as per the ICH guidelines, and the validated results were well within the acceptable range. Both the methods were successfully utilized for the determination of AMD and COX in the presence of each other in the formulation, and statistically compared between the proposed methods. Therefore, the proposed procedures can be utilized for regular quality control studies.
Polystyrene Microsphere Optical Properties by Kubelka–Munk and Diffusion Approximation with a Single Integrating Sphere System: A Comparative Study
The optical properties of 1 μm polystyrene in the wavelength range of 500–750 nm were estimated by using a white light spectrophotometric transmittance spectroscopy and a single integrating sphere system. To retrieve the optical characteristics, two analytical methods, namely, diffusion approximation and Kubelka–Munk were used, and then their results were compared with Mie theory calculations. The correspondence of the Kubelka–Munk scattering coefficient with Mie was obvious, and relative errors varied between 6.73% and 2.66% whereas errors varied between 6.87% and 3.62% for diffusion theory. Both analytical methods demonstrated the absorption property of polystyrene over the abovementioned wavelength range. Although absorption coefficient turned out to be much lower than scattering, constructing a realistic optical phantom requires taking into account absorption property of polystyrene. Complex refractive index of polystyrene based on these two methods was determined. Inverse Mie algorithm with scattering coefficient was also used to retrieve the real part of refractive index and absorption coefficient for calculating the imaginary part of refractive index. The relative errors of the real part did not exceed 2.6%, and the imaginary part was in consistence with the prior works. Finally, the presented results confirm the validity of diffusion theory with a single integrating sphere system.
Prediction Model of the Key Components for Lodging Resistance in Rapeseed Stalk Using Near-Infrared Reflectance Spectroscopy (NIRS)
The chemical composition of rape stalk is the physiological basis for its lodging resistance. By taking the advantage of NIRS, we developed a rapid method to determine the content of six key composition without crushing the stalk. Rapeseed stalks in the mature stage of growth were collected from three cultivation modes over the course of 2 years. First, we used the near-infrared spectroscope to scan seven positions on the stalk samples and took their average to form the spectral data. The stalks were then crushed and sieved; then the ratio of carbon and nitrogen, ratio of acid-insoluble lignin and lignin, and the content of soluble sugar and cellulose were determined using the combustion method, weighing method, and colorimetric method, respectively. The partial least squares regression (PLSR) method was used to establish a prediction model between the spectral data and the chemical measurements, and all models were evaluated by an internal interaction verification and an external independent test set sample. To improve the accuracy of the model and reduce the computing time, some optimization methods have been applied. Some outliers were removed, and then the data were preprocessed to determine the best spectral information band and the optimal principal component number. The results showed that elimination of outliers effectively improved the precision of the prediction model and that no spectral pretreatment method exhibited the highest prediction accuracy. In summary, the NIRS-based prediction model could facilitate the rapid nondestructive detection in the key components of rapeseed stalk.