Journal of Applied Spectroscopy最新文献

Current challenges in the field of luminescent materials are concerned with designing efficient material to meet the rapidly rising demands of industry. Luminescent material excitation and emission are highly complex phenomena driven by the combination of atomic-level properties such as valence electron, inter-atomic radius, ionic radius, etc., and physical properties such as crystal structure, symmetry, etc. The current research paper focuses on the development of a machine-learning algorithm based on simple luminescent materials to predict the excitation to the closest possible accuracy using easily accessible key attributes by the CatBoost regressor, multiple linear regression (MLR), and an artificial neural network (ANN) approach. These selected features likely correlate with the excitation of the material. In comparison, the ANN and MLR algorithms have higher mean absolute error values in both the training and test datasets. The CatBoost algorithm outperforms the other algorithms in terms of mean of the absolute percentage difference, achieving a value of 0.302136% in the training dataset. The CatBoost algorithm exhibits the lowest root mean squared error value of 1.680768 nm in the training dataset, indicating that its predictions have a smaller average deviation from the actual values. The style for studying the material property has the potential to reduce the cost and time involved in an Edisonian approach to the lengthy laboratory experiment to identify excitation.

This work was aimed at creating a new, fast, and accurate UV spectrophotometric method for quantifying prazosin hydrochloride in pure and tablet dosage forms. A phosphate buffer solution of pH 6 was used as a diluent. The highest absorbance of prazosin hydrochloride was measured at 247 nm, and the linearity ranged from 2 to 8 μg/mL. The regression equation for prazosin hydrochloride was y= 0.087x + 0.236, with a correlation value 0.987. The percentage of recovery ranged from 99.6 to 101%. The relative standard deviation for intraday precision and interday precision was determined to be less than 2. The LOD and LOQ of prazosin hydrochloride were determined to be 0.0375 and 0.113 μg/mL, respectively. International Council for Harmonisation criteria validated the spectrometric technique and was suitable for routine quantitative measurement of prazosin hydrochloride in pure and tablet dosage forms.

Idelalisib is a phosphatidylinositol 3-kinase delta inhibitor approved by the FDA and the EMA for the treatment of lympholytic lymphoma, B cell non-Hodgkin lymphoma, and lymphocytic lymphoma. The present report describes the validation of a simple, rapid, sensitive, and cost-effective zero-order and first-order derivative spectrophotometric method for the estimation of idelalisib in bulk and in its marketed formulation. Preliminary spectrophotometric analysis of the drug was carried out in methanol and a total of 12 parametric variations were considered. Three selected method variants employing peak-zero and peak-peak techniques were assessed for their stability indicating potential in stress degraded solutions of the drug. The developed method was validated with respect to linearity, accuracy, precision, and robustness. Excellent linearity was observed within the concentration range 1.0–60.0 μg/mL with a correlation coefficient of 0.9997. The limits of assay detection values were found for the range 0.42–3.11 μg/mL, and quantitation limits ranged from 1.29 to 9.42 μg/mL for the proposed method variants. The proposed method was used to quantify the drug in its marketed tablet formulation, and good recoveries ranging from 95.98 to 98.81% were obtained.

The kinetics of oxidation/reduction of the primary donor of photosystem 1 (PS1) P700, plastocyanin (PC), and ferredoxin (Fd) in the first leaves of barley seedlings under exposure to high-intensity light (2000 μmol∙quanta∙m^–2·s^–1, 30 min) and elevated temperature (40°C, 3 h) were studied using differential absorption photometry. Exposure to high-intensity light increased the accumulation of the oxidized form of PS1 reaction center P700⁺, oxidized PC, and reduced Fd. Reduced Fd was not reoxidized under the same conditions on exposure to red and far-red light. The accumulation of P700⁺, PC⁺, and Fd ^– increased in barley seedlings exposed to elevated temperatures. Also, reoxidation of leaf Fd accelerated under red light. Oxidized Fd did not accumulate under far-red light. It was concluded that photo-independent electron flow through Fd under light stress and alternative electron flows involving the plastoquinone pool under heat stress were activated.

Rapid detection of trace heavy metal ions in water is of great relevance to the environment and human health in the future. With pyrimidine as the parent structure, the water-soluble thiourea group is skillfully introduced to form a symmetric framework, thus firmly capturing the heavy metal ions in the water. The responsiveness of heavy metal ions in water was observed by UV-fluorescence spectroscopy. Especially with Co(NO₃)₂, Cu(NO₃)₂, Ni(NO₃)₂, and Zn(NO₃)₂, the response changes are most significant. The rapid response changes between them and trace heavy metal ions in water were intuitively observed under sunlight and fluorescence irradiation environment.

The current–voltage and capacitance–voltage characteristics of InGaAs/InP heterostructure p-i-n photodiodes fabricated by mesa technology have been studied. Photodiodes of circular configuration differ in active region diameter from 0.05 to 2.5 mm. All measurements are performed in the dark at room temperature using the probe method on a wafer with ready-made devices. Data are obtained on dark currents (leakage currents), I_dark, which are interpreted in terms of the surface and bulk currents in p–i–n photodiodes of various sizes. In the absorbing layer of the InGaAs/InP photodiode heterostructures, the concentration profiles N_D(x) are assessed for the first time by the nondestructive CV method and are compared with the electrochemical profiling data. It is shown that for the most part of the heterostructure i-layer the two methods are complementary.

A new phosphor Sr₅(BO₃)₃Cl:Ce³⁺,Yb³⁺, which enables near-infrared (NIR) quantum cutting, was prepared using traditional solid-state reaction methods. Its properties were examined using X-ray diffraction, photoluminescence emission, excitation spectra, and measurements of fluorescence decay. Upon excitation of Ce³⁺ with an ultraviolent (UV) photon at 350 nm, broadband emission at 415 nm and an intense NIR emission at 982 nm were observed. Emission at 415 nm corresponds to 5d→4f transition of Ce³⁺ ions, whereas the NIR emission at 982 nm is ascribed to the characteristic ²F_5/2 → ²F_7/2 transition of Yb³⁺ ions. Thorough investigation delved into how the concentration of Ce³⁺ affects visible and NIR emissions, decay lifetime, and energy transfer efficiency (η_ETE). Detailed analysis of photoluminescence excitation, emission spectra, and fluorescence decay measurements revealed a proficient energy transfer from Ce³⁺ to Yb³⁺ ions. This transfer was demonstrated as a cooperative energy transfer (CET) process, showcasing a CET efficiency of 71.2% and a total theoretical quantum efficiency of 171.2%.

Different concentrations of B₂O₃ in zinc–aluminum–sodium–phosphate (ZANP) glasses were synthesized by the conventional melt-quenching method and analyzed using X-ray diffraction (XRD), optical absorption, excitation, visible luminescence, decay lifetime, and chromaticity methods. The amorphous nature of the glasses was confirmed by the absence of sharp diffraction peaks in the XRD profile. In the visible emission spectra blue, yellow, and red bands were observed and the intensity of the yellow band was superior. Furthermore, the samples show a luminescence quenching beyond 20 mol.% of B₂O₃ concentration. The decay lifetime of ⁴F_9/2 of Dy³⁺ ions was found to be maximal in ZANP Dy0.5:20B₂O₃ glass.

Empagliflozin, an inhibitor of SGLT-2, a sodium glucose co-transporter is found mainly in the proximal tubules of the nephronic components of the kidney. The assay of empagliflozin in its tablet form has been created using a unique, secure, and sensitive UV-spectrophotometric approach. During the development and validation of the method for the assay of empagliflozin, methanol was employed as the solvent. The maximum absorbance wavelength of the solution was determined by scanning in a UV spectrophotometer. At the specified wavelength; absorbance was measured using a variety of calibration standards. The linearity and range of the calibration curve of concentration vs. absorbance were computed. The accuracy, precision, limit of detection, limit of quantitation, and ruggedness of the analytical approach were among the metrics that were determined. A correlation coefficient of 0.999 indicated linearity within the concentration range 2–10 μg/mL. The maximum absorbance of empagliflozin in methanol was determined to be 238.5 nm. Recovery was estimated as per International Conference on Harmonization guidelines and was found to be as per the acceptance limits: 93.25%. The developed UV method was found to be precise with relative standard deviation less than 2%. The assessment of empagliflozin in its tablet formulation using a UV-spectrophotometric technique was determined to be both safe and helpful. The uniqueness of this research is based on a cost-efficient, time-saving, safe, easy, and successful approach for validating empagliflozin.

Owing to variation of moisture content, the larch wood basic density near-infrared (NIR) prediction model shows reduced accuracy and robustness, or even model failure. To solve this technical problem, a multi-verse-algorithm-optimized BP neural network (MVO-BPNN) prediction model is proposed to improve the accuracy of the model. The preprocessing effects of the Savitzky–Golay smoothing, detrending, and 15-point moving average smoothing method were compared. The synergy interval partial least squares was used to extract the feature bands of the NIR spectra. Results showed that the prediction model based on MVO-BPNN was better than those based on BPNN and the genetic algorithm-optimized BPNN. It indicated that the NIR model based on the MVO-BPNN could effectively predict the basic density of wood with different moisture contents.