Applied Spectroscopy最新文献

The continuous evolution of deep learning has garnered significant attention in spectroscopy. This study focuses on identifying wheat flour, presenting a more efficient and accurate method by combining two-dimensional correlation spectroscopy (2D-COS) and deep learning techniques. A data set of 316 near-infrared (NIR) spectral samples of four types of wheat flour was collected. By applying three disparate 2D-COS techniques, i.e., synchronous, asynchronous, and integrated, we crafted 948 2D-COS images. These images, obtained by transforming the original one-dimensional spectra into 2D representations, offer richer information for deep learning analysis. The study introduced an 18-layer residual network incorporating a convolutional attention mechanism, specifically tailored for the 2D-COS analysis of wheat flour, aimed at enhancing the model's discriminative capabilities by refining the residual neural network's structure. Achieving an unprecedented recognition accuracy of 100% through methodical optimization and rigorous training on the synchronous 2D-COS data set of wheat flour, the proposed model is a testament to the efficacy of deep learning in spectroscopic analysis. To further exhibit the confluence of 2D-COS with deep learning, t-distributed stochastic neighbor embedding was employed to visualize the distinctive 2D-COS features within the deep learning architecture. Additionally, the model's performance was juxtaposed with prevailing NIR spectral recognition methods, including random forest, gradient boosting decision tree, and artificial neural network. This comparison cemented the proposed approach's superiority in wheat flour categorization. The findings of this study not only introduce a novel and efficient solution for wheat flour quality analysis but also underscore the significant potential of deep learning techniques in spectroscopy applications.

We propose a new way of deriving the effective thickness in attenuated total reflection (ATR) spectroscopy, initially introduced by Hansen and Harrick in 1965. While following Hansen's approach, our derivation is more straightforward and includes an intermediate approximation that more closely aligns with results derived from Fresnel's equations, particularly for organic and biological materials. Using this intermediate approximation, we present improved estimations for the effective thicknesses with s- and p-polarized light. These estimations enabled us to enhance a recently developed ATR correction scheme that relies on effective thickness. Additionally, we examined the wavelength dependence of the product of wavenumber and effective thickness, observing that it bears a resemblance to the refractive index function of the sample. This similarity increases with the angle of incidence and the refractive index of the ATR crystal. Based on this observation, we introduce a simple correction scheme using the Kramers-Kronig transformed absorbance. This correction has the potential to address spectral shifts, facilitating applications in pattern recognition and spectra identification.

Oyster fossils are some of the most common bivalve mollusk fossils found all over the world, they are different from other fossils because the oyster is still alive in the present day, and the body structure of modern oyster is almost the same as that of ancient one. Therefore, we designed a control experiment comparing the Raman spectra of minerals from both modern oysters and fossil oysters to explore the mechanism of oyster's fossilization process, which is considered to be helpful for investigating biological evolution or paleoenvironment. The oyster fossil sample was found in Nagi-Cho, Okayama Prefecture, Japan. We focused on the variations of band position and full width half-maximum of ν₁ Raman band (symmetric stretching mode) of calcite (CaCO₃) from modern and fossil oysters and the mineral conversion between calcite and aragonite (CaCO₃) around the adductor muscle inside the oyster. Compared to modern oysters, the ν1 band at around 1086 cm^-1 of calcite from oyster fossils shifted to a high wavenumber region, and the possible reason for this phenomenon is considered an elemental substitution between Ca²⁺ and Mg²⁺. As for aragonite around adductor muscle in fossil oysters, it has been found by Raman spectra that most of the aragonite has been converted into calcite because calcite has a relatively more stable structure.

The insufficient capabilities of current surface-enhanced Raman scattering (SERS) substrates in enriching dilute analytes from complex media severely restrict detection sensitivity, hampering practical applications. To meet this demand, in this study, a novel super hydrophobic membrane that can be directly prepared on a large scale based on the silver nanoparticles (AgNPs) functioning with perfluorodecanethiol (PFDT) is fabricated and evaluated as an SERS substrate. Firstly, polyester (PET) films modified with sodium chloride were proven to be capable of loading AgNPs, and the sizes of AgNPs were investigated. In addition, the PFDT concentration and reaction time for functionalizing the surface of AgNPs have been optimized. The relationship between the hydrophobic properties of the film and its SERS performance was then studied. The PET@Ag-PFDT film demonstrates two orders of magnitude superior SERS performance than the unmodified PET@Ag substrate, with a detection limit of folic acid approaching 5 × 10^-10 M.

The increasing use of light-based treatments requires a better understanding of the light tissue interaction for pigmented skin. To enhance comprehension in this area, this study proposes the use of pigmented-mimicking skin phantoms to assess the optical properties based on their tone, represented by the Individual Typology Angle (ITA) color scale. In this study, an epoxy resin matrix alongside compact facial powder and titanium dioxide was used to mimic the absorption, scattering, and shade properties of human skins. Eight phantoms covering the skin tones, light (ITA = 45.2°), tan (ITA = 23.3°), brown (ITA = 6.9°, -5.7°, and -16.9°), and dark (ITA = -34.6°, -41.6°, and -48.6°), were crafted. The absorption and reduced scattering coefficients were obtained using integrating spheres and calibrated spectrometers in the 500-900 nm range, and tones were measured using a commercial colorimeter. The experimental fitting proposed in this study could estimate the optical properties as a function of the skin tones through ITA values, by using an exponential function with a second-order polynomial exponent. This investigation aligns with prior studies involving human skin samples, and these findings hold promise for future clinical and diagnostic applications, particularly in the realm of light-based treatments to individual dermatological corrections in pigmented skin.

Raman spectroscopy has great potential for quantitative analysis of natural gas. Helium is one of the components of natural gas and has a wide range of applications. It was believed that noble gases could not be detected using this technique due to the absence of their vibrational spectra. In this study, we demonstrated an approach to extracting the content of helium from the Raman spectrum of methane and carried out test measurements for the first time. The approach is based on the determination of changes in the ν₁ band of methane caused by the influence of helium and other components. The necessary spectroscopic parameters characterizing the effect of methane (CH₄), helium (He), nitrogen (N₂), carbon dioxide (CO₂), and ethane (C₂H₆) on the ν₁ band of methane at a resolution of 0.35 cm^-1 were obtained. The validation of the approach showed that the helium content in natural gas can be measured with an uncertainty of 1 mol% at a sample pressure of 50 bar. The measurement precision can be increased to 0.01 mol% by using a high-resolution spectrometer. The described method does not claim to replace helium detectors, but it can be considered a valuable addition to Raman gas analysis of natural gas in developing an all-in-one device. The possibilities for further improvement of the approach are also discussed.

We have specified and obtained a ZnSe prism with an unconventional face angle cut to 30°. This prism, with internal incidence angles ranging from 30° to 48°, allows users to record internal reflection spectra below the critical angle and attenuated total reflection (ATR) spectra above the critical angle without the need to change optics or move or replace the sample. We demonstrate its capabilities using 102 spectra of benzyl benzoate taken with s- and p-polarization at different angles of incidence. The subcritical spectra were analyzed to obtain n_∞, a key parameter for correcting the ATR spectra. These corrected spectra were subsequently used to determine the complex refractive index for all ATR measurements. The averaged complex refractive index function shows excellent agreement with that obtained through ATR spectroscopic ellipsometry.

The Perseverance rover landed at Jezero crater, Mars, on 18 February 2021, with a payload of scientific instruments to examine Mars' past habitability, look for signs of past life, and process samples for future return to Earth. The instrument payload includes the Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) deep ultraviolet Raman and fluorescence imaging spectrometer designed to detect, characterize, and map the presence of organics and minerals on the Martian surface. Operation and engineering constraints sometimes result in the acquisition of spectra with features near the detection limit. It is therefore important to separate instrumental (background) spectral components and spectral components inherent to Martian surface materials. For SHERLOC, the instrumental background is assessed by collecting spectra in the stowed-arm configuration where the instrument is pointed at the Martian nighttime sky with no surface sample present in its optical path. These measurements reveal weak Raman and fluorescence background spectral signatures as well as charged-coupled device pixels prone to erroneous intensity spikes separate from cosmic rays. We quantitatively describe these features and provide a subtraction procedure to remove the spectral background from surface spectra. By identifying and accounting for the SHERLOC Raman background features within the median Raman spectra of Martian target scans, we find that the undefined silicate spectral feature interpreted to be either amorphous silicate or plagioclase feldspar is ubiquitously found in every Mars target Raman scan collected through Sol 751.

This article provides a detailed discussion of the evidence available to date on the application of laser-induced breakdown spectroscopy (LIBS) and supervised classification methods for the individual reassignment of commingled bone remains. Specialized bone chemistry studies have demonstrated the suitability of bone elemental composition as a distinct individual identifier. Given the widely documented ability of the LIBS technique to provide elemental emission spectra that are considered elemental fingerprints of the samples analyzed, the analytical potential of this technique has been assessed for the investigation of the contexts of commingled bone remains for their individual reassignment. The LIBS bone analysis consists of the direct ablation of micrometric portions of bone samples, either on their surface or within their internal structure. To produce reliable, accurate, and robust bone classifications, however, the available evidence suggests that LIBS spectral information must be processed by appropriate methods. When comparing the performance of seven different supervised classification methods using spectrochemical LIBS data for individual reassociation, those employing artificial intelligence-based algorithms produce analytically conclusive results, concretely individual reassociations with 100% accuracy, sensitivity, and robustness. Compared to LIBS, other techniques used for the purpose of interest exhibit limited performance in terms of robustness, sensitivity, and accuracy, as well as variations in these results depending on the type of bones used in the classification. The available literature supports the suitability of the LIBS technique for reliable individual reassociation of bone remains in a fast, simple, and cost-effective manner without the need for complicated sample processing.

We report the standoff/remote identification of post-consumer plastic waste by utilizing a low-cost and compact standoff laser-induced breakdown spectroscopy (ST-LIBS) detection system. A single plano-convex lens is used for collecting the optical emissions from the plasma at a standoff distance of 6.5 m. A compact non-gated Czerny-Turner charge-coupled device (CCD) spectrometer (CT-CCD) is utilized to analyze the optical response. The single lens and CT-CCD combination not only reduces the cost of the detection system by tenfold, but also decreases the collection system size and weight compared to heavy telescopic-based intensified CCD systems. All the samples investigated in this study were collected from a local recycling plant. All the measurements were performed with only a single laser shot which enables rapid identification while probing a large number of samples in real time. Furthermore, principal component analysis has shown excellent separation among the samples and an artificial neural network analysis has revealed that plastic waste can be identified within ∼10 ms only (testing time) with accuracies up to ∼99%. Finally, these results have the potential to build a compact and low-cost ST-LIBS detection system for the rapid identification of plastic waste for real-time waste management applications.