Applied Spectroscopy最新文献

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.

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.

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).

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.

Osteomyelitis (OM) and periprosthetic joint infections (PJIs) are major public health concerns in Western countries due to increased life expectancy. Infections usually occur due to bacterial spread through fractures, implants, or blood-borne transmission. The pathogens trigger an inflammatory response that hinders bone tissue regeneration. Treatment requires surgical intervention, which involves the precise removal of infected tissue, wound cleansing, and local and systemic antibiotic administration. Staphylococcus aureus (SA) is one of the most common pathogens causing infection-induced OM and PJIs. It forms antimicrobial-resistant biofilms and is frequently found in healthcare settings. In this proof-of-concept, we present an approach based on multiple spectroscopic techniques aimed at investigating the effects of SA infection on bone tissue, as well as identifying specific markers useful to detect early bacterial colonization on the tissue surface. A cross-section of a human femoral diaphysis, with negative-culture results, was divided into three parts, and the cortical and trabecular regions were separated from each other. Two portions of each bone tissue type were infected with SA for one and seven days, respectively. Multiple techniques were used to investigate the impact of the infection on bone tissue, Brillouin-Raman microspectroscopy and attenuated total reflection Fourier transform infrared spectroscopy were employed to assess and develop a new noninvasive diagnostic method to detect SA by targeting the bone of the host. The results indicate that exposure to SA infection significantly alters the bone structure, especially in the case of the trabecular type, even after just one day. Moreover, Raman spectral markers of the tissue damage were identified, indicating that this technique can detect the effect of the pathogens' presence in bone biopsies and pave the way for potential application during surgery, due to its nondestructive and contactless nature.

The reduction of greenhouse gas emissions and the effort of carbon neutrality require the improvement of spark-ignition engines in terms of efficiency and capability to operate on renewable fuels. The electrode wear of spark plugs, used for ignition of novel fuels and lean mixtures, emerges as a significant challenge in this transition. Understanding the physical mechanism and influence of spark operation parameters of the wear process is thus important. Compared to the conventional methodology of performing long-term wear tests, laser-based optical diagnostics methods are capable of assessing electrode wear during one single or a few spark discharges. In this work, the necessary initial steps required for performing optical investigations using laser-induced fluorescence (LIF) are presented. Several excitation pathways of nickel atoms were investigated, and 336.96 nm was identified as the optimal one. This excitation approach yielded emissions between 338.75 and 353.58 nm, effectively avoiding the major interference from N₂ plasma emission in spark discharges. Additionally, a linear relationship in fluorescence signal intensity with excitation energy up to 400 µJ was observed. These findings indicate the potential of LIF for in situ diagnostics of electrode wear, contributing to engine development in both efficiency and compatibility with sustainable fuels.

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.

A combination of a highly efficient 213 nm Rayleigh rejection filter (RRF) and a miniaturized 213 nm neodymium-doped vanadate laser enables portable deep ultraviolet (UV) Raman spectrometers. We demonstrate the high efficiency of 213 nm RRF manufactured by Green Optics Co., Ltd by utilizing our compact 213 nm vanadate laser to measure high signal-to-noise ratio UV Raman spectra of Teflon and UV resonance Raman (UVRR) spectra of solid ammonium nitrate. We also demonstrate UVRR detection of trace amounts of ammonia formed during ammonium nitrate UV photolysis. We roughly estimate the ammonia UVRR detection limit of ∼10 ng under our experimental conditions.

A multimodal spectroscopic approach is proposed to correlate the mechanical and chemical properties of plastic materials in art and design objects, at both surface and subsurface levels, to obtain information about their conservation state and to monitor their degradation. The approach was used to investigate the photo-oxidation of acrylonitrile butadiene styrene (ABS), a plastic commonly found in many artistic and design applications, using ABS-based LEGO bricks as model samples. The modifications of the chemical and viscoelastic properties of ABS during photoaging were monitored by correlative Brillouin and Raman microspectroscopy (BRaMS), combined with portable and noninvasive broad-range external reflection infrared (IR) spectroscopy and nuclear magnetic resonance (NMR) relaxometry, directly applicable in museums. BRaMS enabled combined measurements of Brillouin light scattering and Raman spectroscopy in a microspectroscopic setup, providing for the coincident probe of the chemical and mechanical changes of ABS at the sample surface. NMR relaxometry allowed for noninvasive measurements of relaxation times and depth profiles which are directly related to the molecular mobility of the material. Complementary chemical information was acquired by external reflection IR spectroscopy. The simultaneous probe of the chemical and mechanical properties by this multimodal spectroscopic approach enabled us to define a decay model of ABS in terms of compositional changes and variation of stiffness and rigidity occurring with photodegradation. The knowledge acquired on LEGO samples has been used to rate the conservation state of ABS design objects noninvasively investigated by external reflection Fourier transform IR spectroscopy and NMR relaxometry offered by the MObile LABoratory (MOLAB) platform of the European Research Infrastructure of Heritage Science.

The perceived color of human skin is the result of the interaction of environmental lighting with the skin. Only by resorting to human skin spectral reflectance, it is possible to obtain physical outcomes of this interaction. The purpose of this work was to provide a cured and validated database of hyperspectral images of human faces, useful for several applications, such as psychophysics-based research, object recognition, and material modeling. The hyperspectral imaging data from 29 human faces with different skin tones and sexes, under constant lighting and controlled movements, were described and characterized. Each hyperspectral image, which comprised spectral reflectance of the whole face from 400 to 720 nm in 10 nm steps at each pixel, was analyzed between and within nine facial positions located at different areas of the face. Simultaneously, spectral measurements at the same nine facial positions using conventional local point and/or contact devices were used to ascertain the data. It was found that the spectral reflectance profile changed between skin tones, subjects, and facial locations. Important local variations of the spectral reflectance profile showed that extra care is needed when considering average values from conventional devices at the same area of measurement.