Journal of Applied Spectroscopy最新文献

Regularities of formation of the spatial-energy profile (SEP) of the visibility zone (VZ) of active-pulse vision systems (APVS) have been numerically studied, taking into account the ratio of the cross sections of the observation object A_ob and the laser illumination beam A_las in the plane of the object location. For this, the concepts of the boundary distance S_bd, at which A_ob = A_las and the multiplier w = A_ob/A_las, which is added to the well-known equation for the recorded APVS signal, are introduced. Taking into account the finite length of the VZ, the following cases can be distinguished. If S_bd ≥ S_end (end point of the VZ) within the VZ w =1. Previously known studies were performed for this case. When S_start (starting point of the VZ) ≤ S_bd < S_end within the VZ, there may first be a range of distances with a maximum value w₁ = 1, after which there is a range with a factor decreasing to a certain minimum value w₂ < 1. Finally, when S_bd < S_start within the limits of the VZ, w₁(S_del1) < 1 and w₂(S_del2) < 1 (in this case, w₂ is always less than w₁, and the delay distance S_del1 < S_del2). Taking into account the multiplier w < 1 leads, in the corresponding range, to a change in the shape of the SEP, maximum signal values, and other characteristics implemented within the visibility zone. A generalizing parameter that in practice characterizes the infl uence of the range of distances, where w < 1, is the maximum operating range (MOR) of the system S_MOR. For the parameters used in the calculations, taking into account the indicated influence led to a decrease in the S_MOR by 2.9–5.0 times. The main mechanisms for the influence of the relative position of S_bd and the VZ on the characteristics of MOR are given. The main results of numerical modeling are confirmed experimentally.

The carbon levels in low-alloy steel samples were measured using laser-induced breakdown spectroscopy (LIBS) and a random forest (RF) method. When employing the RF method, the root-mean-square error of cross-validation (RMSECV) criterion was first used to select the spectral range of the spectral variables for RF model input, to prevent over-fitting of the RF model when only a few relevant variables are accompanied by many other variables. Second, the out-of-bag (OOB) error criterion was used to optimize the numbers of decision trees (n_tree) and characteristic variables (m_try) in the RF model, which optimizes the RF structure. The availability of a large amount of relevant spectral information, coupled with the remarkable regression capacity of RF, greatly improved the carbon analytical accuracy. The results showed that the root-mean-square error of prediction (RMSEP) was 0.034 wt.% for the calibration curve method and 0.023 wt.% for the RF method; the reduction afforded by the latter method was 32.4%. Thus, the RF method improved the carbon analytical accuracy for low-alloy steels.

Terahertz (THz) single-pixel imaging has received major research attention because of the lack of a suitable high-resolution array detector for THz imaging applications. Improving both imaging speed and quality has become a research hotspot for this field in recent years. In this study, a terahertz single-pixel imaging system with Hadamard spatial encoding was constructed by using optically induced semiconductor materials to perform THz wave modulation. Sparse coding was added to the system’s reconstruction algorithm to enhance imaging quality. Numerous image patches were then collected from a natural image set to train an overcomplete dictionary and each patch in the measured image was reconstructed through sparse representation. To validate the effectiveness of the proposed algorithm, the reconstruction performances of different algorithms were compared under various conditions (i.e., with sampling rates varying from 5 to 100% and with noise levels within a signal-to-noise ratio range of 10–50 dB). The proposed algorithm, in combination with sparse representation of an overcomplete dictionary, showed a higher peak signal-to-noise ratio and a lower mean square error than both the inverse Hadamard transform (IHT) and TVAL3 algorithms. Finally, THz imaging experiments were performed to validate the algorithm’s reconstruction performance at sub-Nyquist sampling rates. The experimental and simulation results coincided closely, thus indicating that the use of the proposed algorithm enhances the signal-to-noise ratio of the reconstructed image, reduces its mean square error, and retains greater image detail. The proposed algorithm was demonstrated to be the preferred choice for THz single-pixel imaging applications.

Ivacaftor is a selective small molecule potentiator Transmembrane Conductance Regulator protein used for the treatment of cystic fibrosis. This report describes the validation of simple, rapid, sensitive and cost-effective zeroorder and first-order derivative spectrophotometric methods for the estimation of ivacaftor in bulk and in its marketed formulation. Preliminary spectrophotometric analysis of the drug was carried out in methanol and a total of 21 parametric variations were considered. Three selected method variants employing absorbance (zero-order), peak-peak- to-peak (first-order), and peak-to-zero (second order) techniques were assessed for their stability indicating potential in stress degraded solutions of the drug. The developed method was validated with respect to parameters including linearity, accuracy, precision, robustness, and solution stability. Excellent linearity was observed in the concentration range of 5.0–30.0 μg/mL with a correlation coefficient of 0.99 and above for the selected method variants. The limits of assay detection values ranged from 0.90–1.06 μg/mL, and quantitation limits ranged from 2.72–3.22 μg/mL for the proposed method variants. The proposed methods were used to quantify the drug in its marketed tablet formulation, and good recoveries ranging from 95.98 to 98.81% were obtained.

Laser-induced breakdown spectroscopy (LIBS) technology faces the challenge of redundant or irrelevant features when dealing with high-dimensional data of steel. To enhance the accuracy and interpretability of multivariate classification, this study introduces an innovative hybrid feature selection (FS) method that skillfully combines the filtering characteristics of the select percentile (SP) algorithm with the embedded advantages of the elastic net (EN) algorithm. Under this framework, the support vector machine (SVM) algorithm was applied for classification, demonstrating outstanding performance with an accuracy, precision, and F1 score of 0.9888, 0.9895, and 0.9889 on the test set, respectively. To address the ‘black box’ nature of the SVM algorithm, this paper further introduces the local interpretable model-agnostic explanations (LIME) method. LIME allows for the visualization of the importance of each variable, thereby enhancing the interpretability and credibility of the model. Overall, the model and methods proposed in this study show significant effectiveness in eliminating redundant or irrelevant features and in precise classification, effectively solving most of the challenges faced by LIBS in steel classification issues.

A procedure based on dispersive liquid-liquid microextraction (DLLME) for cadmium (Cd) quantification in an Iraqi environmental matrix by flame atomic absorption spectroscopy (FAAS) was applied in this work. A case study approach was chosen to obtain further in-depth information on the Cd levels and to evaluate the effectiveness of N-salicylideneaniline (SAN) as a complexing agent for preconcentration and extraction of Cd. Univariate strategy was utilized for achieving the optimum extraction conditions: 75.0 μL of carbon tetrachloride as the extraction solvent, 10 mL of a sample solution adjusted the pH at 8.50 containing 0.8% (w/v) SAN, and 1400 μL of methanol as the dispersive solvent, within 30 s complexation time. The estimated limits of detection (LOD) and quantification (LOQ) under optimum conditions were 0.26 and 0.87 μg/L, respectively. Enrichment factors were obtained in two manners, found to be 24.4 and 44.3. To evaluate the accuracy of the method, known amounts of analytes were spiked and compared with the results achieved using microwave digestion/graphite furnace atomic absorption spectrometer (MWD/GF-AAS) for solid samples, and direct graphite furnace atomic absorption spectrometer (GF-AAS) for water samples. Procedure was applied for analyzing eight environmental samples, the Cd levels for water samples ranged from 3.01 to 7.33 μg/L with a relative standard deviation (4.1–10.4 RSD%), while the concentration for the solid sample (Mentha piperita) was 2.71 μg/g (RSD% = 7.4). DLLME/FAAS proposed procedure is eff ective, simple, and has the benefi t of minimizing the organic solvent consumption, by a few microliters, which results in little waste.

Five types of plastics were classified based on NIR optical density spectra using multivariate cluster analysis in principal component space. An accuracy above 0.96 was obtained by ranking spectral variables by decreasing variance of measured optical density. Changes in polycarbonate VIS-NIR spectra during thermal degradation were modeled using a partial least squares method with searching combination moving windows of optimal width. A quantitative calibration of an aging time up to 11.5 years was obtained with a root mean square error of the estimate around 19 days and a residual predictive deviation of more than 45.

The atmospheric wind field in the troposphere and stratosphere notably impacts human production and life. The lidar is one of the most effective means of detecting the atmosphere in this region due to its high resolution and sensitivity. To meet this need, aerosol and molecular backscattering signals of different wavelengths were analyzed via lidar technology. The results showed that the 355-nm laser provides an advantage in detecting the atmosphere under clear weather conditions, and the 1064-nm laser achieves superior detection performance under severe haze weather conditions, while the detection performance of the 532-nm laser varies between those of the other lasers. The detection performance of the system was simulated using a 532-nm laser, and the maximum detection height reached 43 km under clear weather conditions and 28 km under polluted weather conditions. This analysis provides support for obtaining atmospheric wind fields in the troposphere and stratosphere under all weather conditions in the future.

The present work describes the development and validation of zero-order derivative and first-order derivative UV-Vis spectrophotometric methods for the quantitative determination of viloxazine hydrochloride. The spectrophotometric determination was performed within 200–400 nm and the first-order derivative spectrum was obtained by comparing absorbance to wavelength. The developed method was validated under ICH guidelines for linearity, precision, accuracy, limits of detection and quantification, and robustness. The correlation coefficient value of the methods was 0.9989 (method A) and 0.9979 (method B) with a limit of detection of 3 μg/mL and a limit of quantification of 9 μg/mL. The precision of the methods was confirmed by calculating the %relative standard deviation, which is acceptable as per guidelines. The accuracy of the methods was calculated and represented in terms of % mean recovery. Moreover, the greenness profiles of the developed UV method were assessed using the green analytical procedure index (GAPI) and the AGREE evaluation method. The results revealed adherence of the described method to the green analytical chemistry principles. We successfully developed and validated the UV method according to ICH guidelines. The method was proved for the analysis of marketed formulations.

Folic acid (FA) is an important nutrient for several physiological functions, including DNA synthesis, amino acid homeostasis, and normal blood production. With the increased circulation of counterfeit and substandard drugs worldwide, it is vital to ensure the quality of the FA tablets using a simple and validated analytical method that can be applied for routine QC of FA tablets in developing countries or worldwide. We developed two validated spectrophotometric methods for the quantitation of FA in tablet dosage forms. The developed methods were applied to bulk and FA powdered tablets dissolved in alkaline media using a 0.1 N NaHCO₃ solution (method 1) and a 0.1 N NaHCO₃/0.1N HCl solution (method 2). The established wave lengths λ_max were found to be at 256, 283, and 366 nm (method 1) and at 295 nm (method 2). Method validation parameters included linearity, accuracy, precision, LOD, and LOQ. The accuracy and precision (RSD%) of the methods were tested by direct sample/standard comparison (n = 5) and found to be simple, selective, and robust. Good linearity was achieved, with correlation coefficients ≥0.9923 and limits of detection and quantification ranging from 1.46 to 2.44 μg/mL and from 4.45 to 7.38 μg/mL at 256, 283, and 366 nm (method 1). Likewise, the LOD and LOQ values of method 2 were 1.53 and 4.66 μg/mL, respectively. The assay results for FA tablets were 102–107% for method 1, with RSD% between 3.73 and 7.75%. For method 2, the assay results for FA tablets were 106.54 ± 2.34% with a linearity of 0.9998. These developed methods provide a simple alternative to the important published methods for assaying of FA in tablet formulations.