Search Results (186)

Near-infrared (NIR) spectroscopy is a rapid, non-destructive analytical tool widely used in the food and agricultural sectors. In this study, two NIR instruments were compared for classifying the addition of microplastics (MPs) to high-moisture-content samples such as vegetables and fruit. Polyethylene (PE), polypropylene (PP), and a mix of polymers (PE + PP) MP were added to mixtures of spinach and banana and scanned using benchtop (Bruker Tango) and portable (MicroNIR) instruments. Both principal component analysis (PCA) and partial least squares (PLS) were used to analyze and interpret the spectra of the samples. Quantitative models were developed to predict the addition of Mix, PP, or PE to spinach and banana samples using PLS regression. The R² _CV and the SECV obtained were 0.88 and 0.44 for the benchtop samples, and 0.54 and 0.67 for the portable instruments, respectively. Two wavenumber regions were also evaluated: 11,520–7500 cm⁻¹ (short to medium wavelengths), and 7500–4200 cm⁻¹ (long wavelengths). The R² _CV and the SECV obtained were 0.88 and 0.46, 0.86 and 0.49, respectively, for the prediction of addition in samples analyzed on the benchtop instrument using short and long wavenumbers, respectively. This study provides new insights into the comparison of two instruments for detecting the addition of MPs in high-moisture samples. The results of this study will ensure that NIR can be utilized not only to measure the quality of these samples but also to monitor MPs. Full article

Parasitic peaks are observed in the low wavenumber regions of Surface Waves Investigation and Monitoring (SWIM) wave height spectra. They can be attributed to random fluctuations in the wave spectra caused mainly by speckle noise, compromising the quality of SWIM wave spectra, or can be attributed to a lack of homogeneity over the SWIM footprint. Some recent studies have proposed methods to suppress parasitic peaks: unfortunately, they are intended only for one-dimensional wave spectra, or they lack validation of the quality of wave spectra. In this study, a specific parametric method is proposed to suppress parasitic peaks in two-dimensional wave spectra in order to solve these problems. The parametrized wave spectra are derived by integrating multiple empirical spectra with directional functions, and a cost function is formulated to identify the most suitable parametrized wave spectrum. Subsequently, the quality and wave parameters of the most suitable parametrized wave spectrum are derived. It should be pointed out that the parametric method relies on the wave products provided by SWIM for empirical spectral fitting, so it cannot solve the 180° ambiguity problem. The results show that the specific parametric method effectively suppresses parasitic peaks in the low wavenumber regions while preserving wave information in SWIM wave height spectra. Additionally, the specific parametric method enhances the accuracy of the wave parameters of SWIM data, including significant wave height, dominant wavelength, and dominant wave direction. Full article

Quality control of herbal medicinal products (HMPs) is challenging due to their multicomponent composition. For most HMPs, chemical reference standards (CRSs) required for traditional chromatographic and spectral analyses are unavailable. According to USP and Ph. Eur., an exception is valerian tincture, for which highly specific CRSs have been developed. The aim of this study was to use principal component analysis (PCA) and the novel two-dimensional diffuse laser scattering (2D-DLS) method to identify HMPs and their aqueous-ethanolic extracts according to their botanical genera without relying on specific marker compounds. Spectral data were compiled into an extensive library covering a wide wavelength range—from 0.02 nm to 15,000 nm. PCA of the spectral data (UV spectrophotometry, fluorimetry, FTIR spectroscopy, and X-ray diffraction) enabled clustering of samples by individual botanical genera. The most significant information for sample differentiation was provided by wavenumbers of 1400, 1180, and 931 cm⁻¹ in the IR spectra and wavelengths of 450 nm and 672 nm in the UV and fluorescence spectra, respectively. During model cross-validation, all “blind samples” were correctly classified by botanical genus, achieving a non-error rate (NER) of 100%. Furthermore, the unique 2D-DLS method was used to rapidly identify tinctures without opening the glass bottles. Full article

Raman spectroscopy has become an important tool for biomedical analysis due to its ability to provide label-free, non-destructive molecular fingerprints of biological samples. However, existing deep learning approaches for classifying biological Raman spectra often focus on specific datasets and lack generalizability and interpretability. In this study, BioRamanNet is presented, an interpretable and generalizable deep learning framework designed for classifying a wide range of biological Raman spectra. The model integrates adaptive one-dimensional convolutional layers and squeeze-and-excitation (SE) blocks within a residual network architecture to enhance feature extraction. BioRamanNet was evaluated using four representative Raman spectral datasets—breast cells, extracellular vesicles and particles (EVPs), viruses, and bacteria—achieving classification accuracies of 99.5%, 100%, 99.8%, and 85.3%, respectively. To improve model interpretability, a perturbation-based analysis using Voigt noise was introduced to identify key wavenumber regions influencing classification. These regions were found to correspond closely with known Raman biomarkers, validating their biological significance. The results of this work demonstrate that BioRamanNet is a powerful and interpretable tool for analyzing diverse biological Raman spectra and holds promise for advancing machine learning-assisted biomedical diagnostics. Full article

This work shows that inverse Judd–Ofelt (JO) analysis of relative absorption spectra, anchored by a single lifetime, provides JO parameters and radiative rates without absolute calibration. The method is applied to Er³⁺, Dy³⁺, and Sm³⁺ in a compositionally identical oxyfluoride glass. Three well-resolved ground-state 4f–4f absorption bands were selected. After baseline removal and wavenumber-domain integration, their normalized strengths S_rel,k (k = 1, 2, 3; k∈S) define a 3 × 3 system solved by non-negative least squares to obtain the anchor-independent ordering (Ω₂:Ω₄:Ω₆). Absolute scaling uses a single lifetime anchor. We report lifetime-scaled Ω_t and A_rad, and the normalized fractions p_k within the selected triplets; as imposed by the method, the anchor-independent ordering (Ω₂:Ω₄:Ω₆) is analyzed, while absolute A_rad and Ω_t scale with τ_ref. The extracted parameters fall within the expected ranges for oxyfluoride hosts and reveal clear ion-specific trends: Ω₂ follows Dy³⁺ > Er³⁺ > Sm³⁺ (site asymmetry/hypersensitive response), while the ordering Ω₄ > Ω₆ holds across all ions (oxide-rich networks). Er³⁺ exhibits the largest Ω₄ and the smallest Ω₆, indicative of pronounced medium-range “rigidity” with suppressed long-range polarizability; Sm³⁺ shows the lowest Ω₂ (more symmetric/less covalent coordination); and Dy³⁺ the highest Ω₂ (strong hypersensitive behavior). Uncertainty was quantified by Monte Carlo resampling of the preprocessing steps, yielding compact 95% confidence intervals; the resulting JO-parameter trends (Ω₂, Ω₄, Ω₆) and normalized f_k fractions reproduce the characteristic spectroscopic behavior known for each ion. This method enables quantitative JO outputs from uncalibrated spectra, allowing direct spectroscopic comparisons and quick screening when only relative absorption data are available. Full article

Onboard the MetOp satellite series, Infrared Atmospheric Sounding Interferometer (IASI) is a Fourier Transform spectrometer based on the Michelson interferometer. IASI acquires interferograms, which are processed to provide high-resolution atmospheric emission spectra. These spectra enable the derivation of temperature and humidity profiles, among other parameters, with exceptional spectral resolution. In this study, we evaluate a novel, rapid retrieval approach in the interferogram domain, aiming for near-real-time (NRT) analysis of large spectral datasets anticipated from next-generation tropospheric sounders, such as MTG-IRS. The Partially Sampled Interferogram (PSI) method, applied to trace gas retrievals from IASI, has been sparsely explored. However, previous studies suggest its potential for high-accuracy retrievals of specific gases, including CO, CO₂, CH₄, and N₂O at the resolution of a single IASI footprint. This article presents the results of a study based on retrieval in the interferogram domain. Furthermore, the optical pathway differences sensitive to the parameters of interest are studied. Interferograms are generated using a fast Fourier transform on synthetic IASI spectra. Finally, the relationship to the total column of carbon monoxide is explored using three different algorithms—from the most intuitive to a complex neural network approach. These algorithms serve as a proof of concept for interferogram classification and rapid predictions of surface temperature, as well as the abundances of H₂O and CO. IASI spectra simulations were performed using the LATMOS Atmospheric Retrieval Algorithm (LARA), a robust and validated radiative transfer model based on least squares estimation. The climatological library TIGR was employed to generate IASI interferograms from LARA spectra. TIGR includes 2311 atmospheric scenarios, each characterized by temperature, water vapor, and ozone concentration profiles across a pressure grid from the surface to the top of the atmosphere. Our study focuses on CO, a critical trace gas for understanding air quality and climate forcing, which displays a characteristic absorption pattern in the 2050–2350 ${\mathrm{cm}}^{-1}$ wavenumber range. Additionally, the study explores the potential of correlating interferogram characteristics with surface temperature and H₂O content, aiming to enhance the accuracy of CO column retrievals. Starting with intuitive retrieval algorithms, we progressively increased complexity, culminating in a neural network-based algorithm. The results of the NN study demonstrate the feasibility of fast interferogram-domain retrievals, paving the way for operational applications. Full article

The acid number evaluates the degree of deterioration of lubricating oil. Existing methods for evaluating the performance degradation of lubricating oils are mostly based on the detection of traditional physical and chemical indicators, which often only reflect a single dimension of the degradation process, thus affecting the accuracy and repeatability of the results. Integrating multi-dimensional information can more comprehensively reflect the essence of degradation, which can improve the accuracy and reliability of the evaluation results. Mid-infrared spectroscopy is an effective means of monitoring the acid number. In this study, a combination of infrared spectroscopy quantitative analysis and chemometrics was used. The oil sample data was divided into training set and validation set by the Kennard–Stone method. In the experiment, a Fourier transform infrared spectrometer equipped with an attenuated total reflection accessory (ATR-FTIR) was used to collect spectral data of the samples in the wavenumber range of 1750–1700 cm⁻¹ (this range corresponds to the characteristic absorption of carboxyl groups and is directly related to the acid number). Meanwhile, a G20S automatic potentiometric titrator was used to determine the acid number as a reference value in accordance with GB/T 7304. The study compared various preprocessing methods. A regression prediction model between the spectra and acid number was established using partial least squares regression (PLSR) within the selected wavenumber range, with the root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP), and coefficient of determination (R) as evaluation indicators. The experimental results showed that the PLSR model established after preprocessing with second derivative combined with seven-point smoothing exhibited the optimal performance, with an RMSECV of 0.00505, an RMSEP of 0.14%, and an R of 0.9820. Compared with the traditional titration method, this prediction method is more suitable for real-time monitoring of production lines or rapid on-site screening of equipment. It can in a timely manner warn of the deterioration trend of lubricating oil, reduce the risk of equipment wear caused by oil failure, and provide efficient technical support for lubricating oil life management. Full article

Background/Objectives: This study investigates the chemical structure and molecular interactions in 3D-printed dental resins reinforced with varying concentrations of Yttria-Stabilized Zirconia (YSZ) nanoparticles, using Fourier-Transform Infrared Spectroscopy (FTIR) to assess the compatibility and bonding behavior at the molecular level. Methods: Three groups of 3D-printed methacrylate-based resin discs were fabricated: a control (0% YSZ), and experimental groups reinforced with 1% and 3% YSZ nanoparticles. Samples were produced using Digital Light Processing (DLP) technology and post-processed under standardized conditions. FTIR spectra were collected via ATR mode over a wavenumber range of 4000–600 cm⁻¹. Spectral differences at key wavenumbers (1721.16, 1237.11, and 929.62 cm⁻¹) were statistically analyzed using one-way ANOVA and Tukey’s post hoc test. Results: FTIR spectra showed no significant shifts in the ester carbonyl band at 1721.16 cm⁻¹, suggesting the preservation of the core resin matrix. However, a statistically significant increase in absorbance at 1237.11 cm⁻¹ was observed in the 1% YSZ group (p = 0.034), indicating dipolar interaction. A distinct new peak at 929.62 cm⁻¹, corresponding to Zr–O vibrations, emerged in the 3% YSZ group (p = 0.002), confirming successful nanoparticle integration. Conclusions: YSZ nanoparticles enhance specific molecular interactions within methacrylate-based dental resins without compromising structural integrity. These findings support the potential application of YSZ-reinforced 3D-printed resins in durable, biocompatible permanent dental restorations. Full article

The functional properties of proteins are closely related to their structure and conformation. The effects of glycosylation and pH on the structural and conformational changes in whey protein isolate (WPI) were investigated using multispectral technology. More and higher-molecular-weight molecules of WPI–dextran conjugates (WDCs) with increased degrees of glycosylation (DGs) in SDS-PAGE occurred at the expense of band intensities of α-lactalbumin, β-lactoglobulin, and bovine serum albumin. The higher wavenumber shift in FTIR peaks of WPI after glycosylation in the Amide I, II, and III regions and the decrease in its intensity occurred. The maximum absorption wavelength (λ_max) of UV-Vis spectra of WPI before and after glycosylation in the range of 260–290 nm showed no significant difference in a pH range of 2.0–10.0. Moreover, the UV-Vis absorption intensities of WDCs at λ_max around 278 nm were highly and positively correlated with their DGs. The λ_max and intensities of total intrinsic fluorescence spectra of Tyr and Trp residues in WDCs with an increase in DGs had an obvious redshift and decrease, respectively. Although the intensities of synchronous fluorescence spectra of individual Tyr or Trp residues in WDCs with an increase in DGs also gradually decreased, the λ_max of the former and latter had a blueshift and redshift, respectively. UV-Vis absorption and fluorescence spectroscopies indicated that the changes in the λ_max and intensity of WPI were closely related to the protonation states of carbonyl groups and free amino groups and the degree of glycosylation. This work may be beneficial for understanding the structural and conformational changes in proteins by measuring the microenvironment around Tyr and/or Trp residues in proteins using UV-Vis absorption and synchronous fluorescence spectroscopies, providing a promising technique for quantitatively monitoring the degree of glycosylation (DG) in a rapid and practical way without any chemical reagents using UV-Vis absorption spectroscopy. Full article

Chrysomya nigripes Aubertin, 1932, is a species of Calliphoridae widely distributed in Southeast Asia, with studies and case reports confirming the value of this species in estimating the minimum postmortem interval (PMI_min). However, data on the growth and development of this species’ intra-puparial age are not yet complete. Here, we investigated the intra-puparial morphological changes of C. nigripes at seven temperatures, ranging from 16 °C to 34 °C. We also investigated the potential value of Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) coupled with chemometric methods for the intra-puparial age estimation of C. nigripes at 19 °C, 25 °C, and 31 °C. The spectral data within the wavenumber range of 1800–900 cm⁻¹, collected from the second thoracic segment of all puparia, were processed. Through this procedure, the mean values of ATR-FTIR spectra of C. nigripes of puparia at each intra-puparial age under various constant temperature conditions were obtained. The results showed that at 16 °C, C. nigripes could not complete its developmental process, while it could do so at the remaining six constant temperatures. With an increase in temperature, the average duration of the intra-puparial period was reduced from the longest at 19 °C of 192 ± 0 h to 77.3 ± 4.6 h at 34 °C. The intra-puparial morphological changes were divided into 12 sub-stages, and the development of the compound eyes, mouthparts, antennae, thorax, legs, wings, and abdomen were divided into 6–8 sub-stages. The Partial Least Squares Discriminant Analysis (PLS-DA) classification model predicted better results compared to the Random Forest (RF) classification model, with an accuracy of 58.3%, 77.8%, and 100% at 19 °C, 25 °C, and 31 °C, respectively. In this study, each sub-stage of the C. nigripes pupa and the time range of structure emergence were recorded, and it was concluded that the spectral trends were time-dependent. Thus, ATR-FTIR combined with chemometrics could also be used as a tool to assist in estimating the intra-puparial stage of C. nigripes and provide a reference value for PMI_min. Full article

In recent years, domestic research on the ion substitution behavior and chromaticity of the mineral composition of “Ya’an Green” remains insufficient, while there is almost no relevant research on “Ya’an Green” abroad. In this study, X-ray powder diffraction (XRD), electron probe microanalysis (EPMA), infrared spectroscopy (IR), ultraviolet–visible spectroscopy (UV-Vis), and colorimetry were employed. The results indicate that the green and yellow matrices of “Ya’an Green” are primarily composed of muscovite, with rutile also present in the yellow matrix. In contrast, the white–green samples are mainly composed of quartz, with muscovite as a secondary mineral. Additionally, it was observed that the (004) crystal plane of muscovite exhibits a peak shift to lower 2θ angles, attributed to the substitution of Al³⁺ by ions with larger radii, such as Ba²⁺, Cr³⁺, and Fe²⁺, leading to an increase in unit cell parameters and a consequent shift in the peak to lower wavenumbers. The main elements of “Ya’an Green” are Al, Si, and K, with minor elements including Na, Fe, and Cr. Furthermore, Mg²⁺, Ca²⁺, Ti⁴⁺, Cr³⁺, and Fe²⁺ in the samples can substitute for Al³⁺ through isomorphic substitution. The infrared spectrum of muscovite in the ‘Ya’an Green’ sample shows three typical absorption peaks, 422 cm⁻¹ and 513 cm⁻¹ caused by Si-O bending vibration, 697 cm⁻¹ and 837 cm⁻¹ caused by Si-O-Al vibration, 948 cm⁻¹ caused by O-H bending vibration, and 3647 cm⁻¹ caused by O-H stretching vibration. The peak at 837 cm⁻¹ exhibits varying degrees of shift due to the substitution of Al³⁺ by ions with larger radii. The ultraviolet–visible spectra display two broad absorption bands at 422 nm and 615 nm, which are caused by Cr³⁺ transition, indicating that Cr is the chromogenic element responsible for the green color. A correlation was observed between the Cr³⁺ content and the hue angle h in “Ya’an Green” samples: the higher the Cr³⁺ content, the closer the hue angle is to 136^°, resulting in a darker green color, while lower Cr³⁺ content leads to a deviation from the dark green hue. This study establishes for the first time the correlation between the mineral composition of ‘Ya’an Green’ and its chromatic parameters and explores the linear relationship between its color and the number of color-causing elements and elemental substitution, which provide data support and theoretical models for the study of the color of seal stones. Full article

Because of the involvement of π-electron cyclic constituents in their side chains, the so-called aromatic residues give rise to a number of strong, narrow, and well-resolved lines spread over the middle wavenumber (1800–600 cm⁻¹) region of the Raman spectra of peptides and proteins. The number of characteristic aromatic markers increases with the structural complexity (Phe → Tyr → Trp), herein referred to as (F_i = 1, …, 6) in Phe, (Y_i = 1, …, 7) in Tyr, and (W_i = 1, …, 8) in Trp. Herein, we undertake an overview of these markers through the analysis of a representative data base gathered from the most structurally simple tripeptides, Gly-Xxx-Gly (where Xxx = Phe, Tyr, Trp). In this framework, off-resonance Raman spectra obtained from the aqueous samples of these tripeptides were jointly used with the structural and vibrational data collected from the density functional theory (DFT) calculations using the M062X hybrid functional and 6-311++G(d,p) atomic basis set. The conformation dependence of aromatic Raman markers was explored upon a representative set of 75 conformers, having five different backbone secondary structures (i.e., β-strand, polyproline-II, helix, classic, and inverse γ-turn), and plausible side chain rotamers. The hydration effects were considered upon using both implicit (polarizable solvent continuum) and explicit (minimal number of 5–7 water molecules) models. Raman spectra were calculated through a multiconformational approach based on the thermal (Boltzmann) average of the spectra arising from all calculated conformers. A subsequent discussion highlights the conformational landscape of conformers and the wavenumber dispersion of aromatic Raman markers. In particular, a new interpretation was proposed for the characteristic Raman doublets arising from Tyr (~850–830 cm⁻¹) and Trp (~1360–1340 cm⁻¹), definitely excluding the previously suggested Fermi-resonance-based assignment of these markers through the consideration of the interactions between the aromatic side chain and its adjacent peptide bonds. Full article

This research aimed to assay the impact of convective drying (CD) or infrared–convective (IR–CD) drying methods on the physical and techno-functional properties, FTIR spectra, and mathematical modeling of adsorption kinetics of black soldier fly larvae powders. By using convective drying, insect powder exhibited higher water content and water activity but lower hygroscopicity than powder dried with the infrared–convective method. After drying with the convective method, the powder exhibited a significantly lower loose and tapped bulk density and oil holding capacity (OHC). Furthermore, this powder was lighter and more yellow. The FTIR spectrum of the CD-dried powder showed lower absorption at key wavenumbers for the protein (1625 and 1350–1200 cm⁻¹), indicating lower denaturation and less ability to bind water and water vapor. The mathematical modeling of the water vapor adsorption kinetics of insect powders via the second Fick’s law for transient diffusion showed that this equation is suitable for adjusting the experimental data based on the high coefficient of determination (0.997–0.999) and the low root mean square (2.50–3.34%). This study revealed that the drying method influences insect powder properties, and the IR–CD method seems better in terms of obtaining better techno-functional properties. Full article

Cortisol, known as the “stress hormone”, is vital for stress response, metabolism regulation, and immune function, and salivary cortisone reflects serum cortisol levels. The measurement of salivary cortisone levels has been proposed as an effective alternative method for estimating serum cortisol levels. Objective: This study aimed to evaluate the use of Fourier Transform Infrared Spectroscopy (FTIR) for salivary cortisone identification and quantification and to assess the impact of adding the surfactant TWEEN 80 to the analysis. Methods: Initially, cortisone was diluted in chloroform and methanol (5,000,000 µg/dL). FTIR spectra were obtained, and absorbance characteristics and peaks were identified. The spectrum of this initial dilution was processed using the Savitzky-Golay filter to evaluate peak heights at 1655 cm⁻¹ and 1700 cm⁻¹, and the effect of signal processing on these peaks was assessed. Additionally, two series of dilutions were performed by adding the surfactant TWEEN 80 at two different concentrations, and the effect of the surfactant on the cortisone spectra was evaluated to reduce noise and enhance the signal. Results: The spectra obtained from the cortisone solution were similar to those found in the literature for solid samples. The peak corresponding to the wavenumber range of 1600–1680 cm⁻¹, related to the stretching bands of C=C, was found to be reliable for use in cortisone quantification studies. The standard deviation between the spectra of the same sample was less than 0.01. It was not possible to detect cortisone when TWEEN 80 was added; however, with signal processing, TWEEN 80 could be detected in quantities as low as 0.0033% of the solution. Conclusions: FTIR demonstrates potential as a non-invasive method for cortisone analysis. While Tween 80 aids in the dilution of cortisone in water, it obscures its spectrum. Full article

The interaction between terahertz (THz) photons and phonons of materials is crucial for the development of THz photonics. In this work, typical two-dimensional (2D) van der Waals (vdW) transition metal chalcogenide (TMD) layers and heterostructures are used in THz time-domain spectroscopy (TDS) measurements, low-wavenumber Raman spectroscopy measurements, calculation of 2D materials’ phonon spectra, and theoretical analysis of thermal responses. The TDS results reveal strong absorption of THz photons in the frequency range of 2.5–10 THz. The low-wavenumber Raman spectra show the phonon vibration characteristics and are used to establish phonon energy bands. We also set up a computational simulation model for thermal responses. The temperature increases and distributions in the individual layers and their heterostructures are calculated, showing that THz photon absorption results in significant increases in temperature and differences in the heterostructures. These give rise to interesting photothermal effects, including the Seebeck effect, resulting in voltages across the heterostructures. These findings provide valuable guidance for the potential optoelectronic application of the 2D vdW heterostructures. Full article