Applied Spectroscopy最新文献

We characterize the subsurface thermal degradation of an inert analog of high-explosive molecular crystals (Eu:Y(acac)₃(DPEPO)) (EYAD) embedded inside of a plastic bonded explosive simulant using feedback-assisted wavefront shaping-based fluorescence and Raman spectroscopies. This technique utilizes wavefront shaping to focus pump light inside a heterogeneous material onto a target particle, which significantly improves its spectroscopic signature. We find that embedding the EYAD crystals in the heterogeneous polymer results in improved thermal stability, relative to bare crystal measurements, with the crystal remaining fluorescent to >612 K inside of the heterogeneous material, while the bare crystal's fluorescence is fully quenched by 500 K. We hypothesize that this improvement is due to the polymer restricting the effects of EYAD melting, which occurs at 400 K and is the primary mechanism for spectroscopic changes in the temperature range explored.

This paper describes an approach based on the method of terahertz time-domain spectroscopy, which allows the analysis of dynamical hydration shells of proteins with a thickness of 1-2 nm. Using the example of bovine serum albumin in three conformations, it is shown that the hydration shells of the protein are characterized by increased binding of water molecules in the primary hydration layers, and in more distant areas of hydration, on the contrary, the water structure is somewhat destroyed. The fraction of free or weakly bound molecules, usually observed in the structure of liquid water in hydration shells, become more numerous but its average binding is greater than in undisturbed water. The energy distribution of hydrogen bonds in hydration shells is narrowed compared to undisturbed water. All these manifestations of hydration are most pronounced for the native conformation of the protein. Also, the hydration shells of the native protein are characterized by a smaller number of hydrogen bonds and a tendency to decrease their average energy compared to non-native conformations. The fact of a pronounced peculiarity of the hydration shells of the protein in the native conformation has been noted for different proteins before. However, the methodological approach used in this work for the first time allowed this peculiarity to be described by specific parameters of the intermolecular structure and dynamics of water.

Raman spectroscopy is among the top analytical techniques for ultra-low-dense organic matter, crucial to the search for life and analysis of celestial body surfaces in space exploration missions. Achieving the ultimate sensitivity of in-situ Raman spectroscopy necessitates a breakthrough in detecting inelastically scattered light. Single-photon detectors (SPDs) operating in photon counting mode, which can differentiate between Raman and luminescence responses, are promising candidates for the challenging scientific requirements. Since large SPD arrays are not yet commercially available, a dispersive element can be adapted to a single-pixel detector. By exploiting chromatic dispersion in optical fibers and picosecond-pulsed excitation, we delay the arrivals of different spectral components onto a single-pixel SPD. This method also separates weak Raman signals from stronger luminescence through correlated time-domain measurements. We study the impact of fiber properties and the excitation wavelength of a pulsed laser on the spectral resolution of the fiber-dispersive Raman spectrometer (FDRS). Additionally, we demonstrate the FDRS's potential for studying biomarkers and discuss its feasibility for analyzing inclusions in ice matrices.

Raman spectroscopy allows for the unambiguous identification of materials through the inelastic scattering of light. This technique has a great many uses in various aspects of society from academic, scientific, and industry. This paper explores a specific type of Raman spectrometer called a spatial heterodyne Raman spectrometer (SHRSy), which is a variation of an interferometric spectrometer. It utilizes a Michelson interferometer and replaces the mirrors with gratings that transform it from a time-domain spectrometer to a spatial-domain spectrometer, allowing for the entirety of the spectrum to be captured at once. This study specifically tests a half-inch two-grating monolithic SHRS (½-in. 2g-mSHRS), which has a weight of <60 g and a size of 2.2 × 2.2 × 1.3 cm. To do this we excite a variety of organic liquids with a 532 nm neodymium-doped yttrium aluminum garnet (Nd:YAG) pulsed laser, using an excitation energy of 6.5 mJ/pulse and distance of 3 m in conjunction with an intensified charge-coupled device camera. This is the first time that the SHRS has been used for investigating polarized Raman spectra of liquids. We discuss and contrast the instrumental properties such as resolution, spectral range, étendue, and field of view with previously tested mSHRS to give context to the instrument's performance.

The conditions for the smart colorimetric determination of cetylpyridinium chloride and sodium dodecyl sulfate by reaction with Coomassie brilliant blue G (CBBG) have been proposed. The nature of the absorption and fluorescence spectra of aqueous solutions of CBBG as a function of acidity has been investigated. A variety of reagent forms and associations with ionic surfactants have been demonstrated. The composition of the associates formed in the CBBG-cationic surfactant system has been established. The increase in the analytical signal of the cationic surfactant and the stabilization of the colloid-chemical state of the system during reactions in the organized medium of the nonionic surfactant Triton X-100 has been demonstrated. These effects are realized through association in premicellar solutions and as a result of the solubilization of components in Triton X-100 micellar solutions. The addition of long-chain cationic surfactants to the reagent occurs with the replacement of the heteroatom proton. The absorption of CBBG-cationic surfactant associates solutions increases with the length of the cationic surfactant hydrocarbon chain. Ethanol additives decrease the aggregation of CBBG. The technique of cationic surfactant determination has been tested in the analysis of the pharmaceutical. The results show that the simplicity of analytical signal registration with satisfactory correctness and acceptably high sensitivity of determination is an advantage of the developed technique.

The aim of this work was the development and morphological/chemical, spectroscopic, and structural characterization of titanium dioxide, niobium pentoxide, and titanium:niobium (Ti:Nb) oxides, as well as materials modified with ruthenium (Ru) with the purpose of providing improvement in photoactivation capacity with visible sunlight radiation. The new materials synthesized using the sol-gel methodology were characterized using the following techniques: scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), photoacoustic spectroscopy (PAS), and X-ray diffraction (XRD). The SEM-EDS analyses showed the high purity of the bases, and the modified samples showed the adsorption of ruthenium on the surface with the crystals' formation and visible agglomerates for higher calcination temperature. The nondestructive characterization of PAS in the ultraviolet visible region suggested that increasing calcination temperature promoted changes in chemical structures and an apparent decrease in gap energy. The separation of superimposed absorption bands referring to charge transfers from the ligand to the metal and the nanodomains of the transition metals suggested the possible absorption centers present at the absorption threshold of the analyzed oxides. Through the XRD analysis, the formation of stable phases such as T-Nb_16.8O₄₂, o-Nb₁₂O₂₉, and rutile was observed at a lower temperature level, suggesting pore induction and an increase in surface area for the oxides studied, at a calcination temperature below that expected by the related literature. In addition, the synthesis with a higher temperature level altered the previously existing morphologies of the Ti:Nb, base and modified with Ru, forming the new mixed crystallographic phases Ti₂Nb₁₀O₂₉ and TiNb₂O₇, respectively. As several semiconductor oxide applications aim to reduce costs with photoexcitation under visible light, the modified Ti:Ru oxide calcined at a temperature of 800 °C and synthesized according to the sol-gel methodology used in this work is suggested as the optimum preparation point. This study presented the formation of a stable crystallographic phase (rutile), a significant decrease in gap energy (2.01 eV), and a visible absorption threshold (620 nm).

Carbonate minerals are globally distributed on the modern and ancient Earth and are abundant in terrestrial and marine depositional environments. Fluid inclusions hosted by calcite retain primary signatures of the source fluid geochemistry at the time of mineral formation (i.e., pCO₂) and can be used to reconstruct paleoenvironments. Confocal laser Raman spectroscopy provides a quick, nondestructive approach to measuring the constituents of fluid inclusions in carbonates and is a reliable method for qualitatively determining composition in both the aqueous and gas phases. Here, we demonstrate a method for accurately quantifying bicarbonate and carbonate ion concentrations (down to 20 mM) and pH (7-11) from calcite fluid inclusions using confocal Raman spectroscopy. Instrument calibrations for carbonate (CO₃^2-) and bicarbonate (HCO₃^-) concentrations and pH were performed using stock solutions. We show that the calcite host mineral does not affect the accurate quantification of carbonate solution concentrations and that these parameters can be used to estimate the pH and pCO₂ of a solution entrapped within a fluid inclusion. We apply the technique to Icelandic spar calcite and find a [CO₃^2-] = 0.11, [HCO₃^-] = 0.17, pH = 10.1, and CO₂ parts per million = 2217. The presence of gaseous Raman bands for CO₂, CH₄, and H₂S suggests that the mineral precipitated in a reducing environment.

A new optical diagnostic method that predicts the global fuel-air equivalence ratio of a swirl combustor using absorption spectra from only three optical paths is proposed here. Under normal operation, the global equivalence ratio and total flow rate determine the temperature and concentration fields of the combustor, which subsequently determine the absorption spectra of any combustion species. Therefore, spectra, as the fingerprint for a produced combustion field, were employed to predict the global equivalence ratio, one of the key operational parameters, in this study. Specifically, absorption spectra of water vapor at wavenumbers around 7444.36, 7185.6, and 6805.6 cm^-1 measured at three different downstream locations of the combustor were used to predict the global equivalence ratio. As it is difficult to find analytical relationships between the spectra and produced combustion fields, a predictive model was a data-driven acquisition. The absorption spectra as an input were first feature-extracted through stacked convolutional autoencoders and then a dense neural network was used for regression prediction between the feature scores and the global equivalence ratio. The model could predict the equivalence ratio with an absolute error of ±0.025 with a probability of 96%, and a gradient-weighted regression activation mapping analysis revealed that the model leverages not only the peak intensities but also the variations in the shape of absorption lines for its predictions.

Modern developments in autonomous chemometric machine learning technology strive to relinquish the need for human intervention. However, such algorithms developed and used in chemometric multivariate calibration and classification applications exclude crucial expert insight when difficult and safety-critical analysis situations arise, e.g., spectral-based medical decisions such as noninvasively determining if a biopsy is cancerous. The prediction accuracy and interpolation capabilities of autonomous methods for new samples depend on the quality and scope of their training (calibration) data. Specifically, analysis patterns within target data not captured by the training data will produce undesirable outcomes. Alternatively, using an immersive analytic approach allows insertion of human expert judgment at key machine learning algorithm junctures forming a sensemaking process performed in cooperation with a computer. The capacity of immersive virtual reality (IVR) environments to render human comprehensible three-dimensional space simulating real-world encounters, suggests its suitability as a hybrid immersive human-computer interface for data analysis tasks. Using IVR maximizes human senses to capitalize on our instinctual perception of the physical environment, thereby leveraging our innate ability to recognize patterns and visualize thresholds crucial to reducing erroneous outcomes. In this first use of IVR as an immersive analytic tool for spectral data, we examine an integrated IVR real-time model selection algorithm for a recent model updating method that adapts a model from the original calibration domain to predict samples from shifted target domains. Using near-infrared data, analyte prediction errors from IVR-selected models are reduced compared to errors using an established autonomous model selection approach. Results demonstrate the viability of IVR as a human data analysis interface for spectral data analysis including classification problems.