In this work, we applied a hydrophilicity-enhanced solid substrate and an alternating laser-ablation data sampling (ALADS) scheme to improve laser-induced breakdown spectroscopy (LIBS) measurement precision and demonstrated the performance in analyzing K, Mg, Ca, and S contained in commercially available edible salt products. Five edible salt products from Australia, Bolivia, France, and South Korea were dissolved in water and a tiny volume of each solution was dropped on the solid substrate, that is, a miniaturized salt pond. After being dried, the residual salt crystals distributed still inhomogeneously, but the homogeneity could be significantly improved in comparison with that from typical drop-and-dry methods. The ALADS scheme was applied to extract three precise measurements from 9798 single-shot LIBS spectra covering the entire salt pond. The measurements obtained by ALADS were found to agree well with one another regardless of the inhomogeneous distribution of salt crystals. As a result, the measurement precision was proved remarkably. Limits of detection for K, Mg, Ca, and S were estimated to be 0.64, 1.7, 14, and 530 mg/kg, respectively, which are enough to analyze those elements contained in salts typically at the level of 100 parts per million (ppm) to ∼3 wt% for the purpose of salt quality assessment.

This work demonstrates the temperature (18-312 K) impact on Tm3+ up-conversion luminescence in core-shell structured NaYF4:Tm3+, Yb3+ nanoparticles excited at 976 nm. As the temperature decreases from room temperature to 18 K, Tm3+ up-conversion luminescence bands intensities greatly increase, an average of 60-fold, emitting intense blue and ultraviolet radiation. Tm3+ up-conversion luminescence spectra measurements at different temperatures reveal that three thermal quenching mechanisms are responsible for observed variations in Tm3+ up-conversion luminescence spectra. These three quenching mechanisms are related to the excitation radiation absorption, Stark sublevel population, and energy transfer from Yb3+ to Tm3+.

Spatial heterodyne Raman spectrometers (SHRSs) are modified forms of Michelson interferometers, except the mirrors in a Michelson interferometer are replaced with stationary diffraction gratings. This design removes the need for an entrance slit, as is the case in a dispersive spectrometer, and removes the need to scan the spectrum by using a moving mirror in a modern Michelson interferometer. In previous studies, various SHRS variants, such as free-standing two-grating SHRS, single-grating SHRS (1g-SHRS), monolithic SHRS (mSHRS), and single-grating mSHRS (1g-mSHRS), have been evaluated. However, the present study exclusively focuses on the 1g-mSHRS configuration. The 1g-mSHRS and 1g-SHRS increase the spectral range at fixed grating line density while trading off spectral resolution and resolving power. The mSHRS benefits from increased rigidity, lack of moving parts, and reduced footprint. In this study, we investigate how the choice of detector impacts the performance of the 1g-mSHRS system, with a specific focus on evaluating the performance of three types of cameras: charged-coupled device (CCD), intensified CCD (ICCD), and complementary metal-oxide-semiconductor (CMOS) cameras. These systems were evaluated using geological, organic, and inorganic samples using a 532 nm continuous wave laser for the CMOS and CCD cameras, and a 532 nm neodymium-doped yttrium aluminum garnet pulsed laser for the ICCD camera. The footprint of the 1g-mSHRS was 3.5 × 3.5 × 2.5 cm3 with a mass of 272 g or 80 g, depending on whether the monolith housing is included or not. We found that increasing the number of pixels utilized along the x-axis of the camera increases fringe visibility (FV) and optimizes the resolution (by capturing the entirety of the grating and magnifying the fringes). The number of pixels utilized in the y-axis, chip size, and dimensions, affect the signal-to-noise ratio of the systems. Additionally, we discuss the effect of pixel pitch on the recovery of Fizeau fringes, including the relationship between the Nyquist frequency, aliasing, and FV.

Degumming is an oil refinement process in which the naturally occurring phospholipids in crude vegetable oils are removed. Enzymatic degumming results in higher oil yield and more cost-efficient processing compared to traditional degumming processes using only water or acid. Phospholipase C hydrolyses phospholipids into diglycerides and phosphate groups during degumming. The diglyceride content can therefore be considered a good indicator of the state of the enzymatic reaction. This study investigates the use of near-infrared (NIR) spectroscopy and chemometrics to monitor the degumming process by quantifying diglycerides in soybean oil in both off-line and on-line settings. Fifteen enzymatic degumming lab scale batches originating from a definitive screening design (with varying water, acid, and enzyme dosages) were investigated with the aim to develop a NIR spectroscopy prediction method. By applying tailored preprocessing and variable selection methods, the diglyceride content can be predicted with a root mean square error of prediction of 0.06% (w/w) for the off-line set-up and 0.07% (w/w) for the on-line set-up. The results show that the diglyceride content is a good indicator of the enzyme performance and that NIR spectroscopy is a suitable analytical technique for robust real-time diglyceride quantification.

Microplastic pollution is a global issue for the environment and human health. The potential for human exposure to microplastic through drinking water, dust, food, and air raises concern, since experimental in vitro and in vivo toxicology studies suggest there is a level of hazard associated with high microplastic concentrations. However, to infer the likelihood of hazards manifesting in the human population, a robust understanding of exposure concentrations is needed. Infrared and near-infrared microspectroscopies have routinely been used to analyze microplastic in different exposure matrices (air, dust, food, and water), with technological advances coupling multivariate and machine learning algorithms to spectral data. This focal point article will highlight the application of infrared and Raman modes of spectroscopy to detect, characterize, and quantify microplastic particles, with a focus on human exposure to microplastic. Methodologies and state-of-the-art approaches will be reported and potential confounding variables and challenges in microplastic analysis discussed. The article provides an up-to-date review of the literature on microplastic exposure measurement using (near) infrared spectroscopies as an analytical tool, highlighting the recent advances in this rapidly advancing field.

The molecular basis of bone structure and strength is mineralized collagen fibrils at the submicron scale (∼500 nm). Recent advances in optical photothermal infrared (O-PTIR) spectroscopy allow the investigation of bone composition with unprecedented submicron spatial resolution, which may provide new insights into factors contributing to underlying bone function. Here, we investigated (i) whether O-PTIR-derived spectral parameters correlated to standard attenuated total reflection (ATR) Fourier transform infrared spectroscopy spectral data and (ii) whether O-PTIR-derived spectral parameters, including heterogeneity of tissue, contribute to the prediction of proximal femoral bone stiffness. Analysis of serially demineralized bone powders showed a significant correlation (r = 0.96) between mineral content quantified using ATR and O-PTIR spectroscopy, indicating the validity of this technique in assessing bone mineralization. Using femoral neck sections, the principal component analysis showed that differences between O-PTIR and ATR spectra were primarily attributable to the phosphate ion (PO4) absorbance band, which was typically shifter toward higher wavenumbers in O-PTIR spectra. Additionally, significant correlations were found between hydrogen phosphate (HPO4) content (r = 0.75) and carbon trioxide (CO3) content (r = 0.66) quantified using ATR and O-PTIR spectroscopy, strengthening the validity of this method to assess bone mineral composition. O-PTIR imaging of individual trabeculae at 500 nm pixel resolution illustrated differences in submicron composition in the femoral neck from bones with different stiffness. O-PTIR analysis showed a significant negative correlation (r = -0.71) between bone stiffness and mineral maturity, reflective of newly formed bone being an important contributor to bone function. Finally, partial least squares regression analysis showed that combining multiple O-PTIR parameters (HPO4 content and heterogeneity, collagen integrity, and CO3 content) could significantly predict proximal femoral stiffness (R2 = 0.74, error = 9.7%) more accurately than using ATR parameters. Additionally, we describe new findings in the effects of bone tissue orientation in the O-PTIR spectra. Overall, this study highlights a new application of O-PTIR spectroscopy that may provide new insights into molecular-level factors underlying bone mechanical competence.

Electrospun fibers of amorphous or low-crystallinity polymers typically exhibit a low molecular orientation that can hamper their properties and application. A key stage of the electrospinning process that could be harnessed to mitigate the loss of orientation is jet rigidification, which relates closely to the solvent evaporation rate. Here, we establish quantitative Raman methods to assess the molecular orientation and crystallinity of weakly crystalline poly(2,6-dimethyl-1,4-phenylene oxide) fibers with varying diameters. Our findings demonstrate that solvent volatility can be leveraged to modulate the orientation and crystallinity through its impact on the effective glass transition temperature (Tg,eff) of the polymer jet during the electrospinning process. Specifically, a highly volatile solvent yields a higher and more sustained orientation (median ⟨P2⟩ of 0.53 for diameters < 1.0 µm) because its fast evaporation rapidly increases Tg,eff above room temperature. This vitrification early along the jet path promotes the formation of an oriented amorphous phase and a moderate fraction of strain-induced crystals. Our data reveals that a high Tg is a crucial parameter for reaching high orientation in amorphous or low-crystallinity polymer systems.

In this research, an attempt was made to classify soil samples according to the different fractions of soil organic matter (SOM) using model systems in which the ratio of the fractions of SOM is chemically mimicked. A mixture of starch and nicotinamide was used for the labile organic matter model, while a standard of humic acid was used for the stabile organic matter. Changing the threshold value in the selected ranges after a permutation importance algorithm is conducted using train models and test data set, a list of selected important wavelengths and their importance scores were obtained. Three regions for the classification of soil fractions within the estimated probability density function are most prominent: 800-1200 cm-1, 0.48-0.55; 1800-2000 cm-1, 0.52-0.62; and 2500-3200 cm-1, 0.48-0.62, where the first component represents the spectral range while the second component covers the range of the importance score. Obtained wavelength ranges indicate the importance of the aliphatic stretching and bending vibration region, as well as the total soil reflectance (mineral content) for the characterization of organic matter fractions. A comparative evaluation with literature data found that the obtained wavelengths have a potential for application in methods of proximal and remote detection/calibration of existing and development of new sensors for Advanced Spaceborne Thermal Emission and Reflection Radiometer satellites, specifically in the shortwave infrared and thermal infrared ranges.

Infrared reflection absorption spectroscopy (IRRAS) is commonly used to study the structure and chemistry of molecules residing at surfaces, including water surfaces, which has far-reaching applications including atmospheric chemistry and food science. However, there is some debate regarding the surface-specificity of IRRAS when examining soluble surfactants on aqueous solutions, and there is some evidence that the surface-specificity may differ between IRRAS of ionic surfactants and soluble organic acids. This paper presents infrared reflection absorption (IRRA) spectra of soluble organic acids underneath monolayers of insoluble surfactants, where the contributions from the insoluble surfactants are subtracted from the spectra to capture "subsurface effects". These "subsurface" spectra demonstrate that IRRA spectra of soluble organic acids are surface specific, and this observation is supported by a simplified model for reflections from "subsurface" layers. Finally, the observations presented here are compared to literature observations regarding the surface-specificity of IRRAS when studying ionic surfactants. Overall, this work demonstrates the utility of IRRAS for studying the structures and chemistry of soluble organic acids at aqueous surfaces.

Near-infrared (NIR) spectroscopy is actually a well-established technique that demonstrates its performance in the frame of detection of poor-quality medicines. The use of low-cost handheld NIR spectrophotometers in low-resource contexts can allow an inexpensive and more rapid detection compared to laboratory methods. Considering these points, it was decided to develop, validate, and transfer methods for the quantification of ciprofloxacin and metronidazole tablet samples using a NIR handheld spectrophotometer in transmission mode (NIR-M-T1) coupled to chemometrics such as partial least squares regression (PLSR) algorithm. All of the models were validated with the total error approach using an accuracy profile as a decision tool, with ±10% specifications and a risk α set at 5%. Quantitative PLSR models were first validated in Belgium, which is a temperate oceanic climate zone. Second, they were transferred to Cameroon, a tropical climate zone, where issues regarding the prediction of new validation series with the initial models were highlighted. Two augmentation strategies were then envisaged to make the predictive models robust to environmental conditions, incorporating the potential variability linked to environmental effects in the initial calibration sets. The resulting models were then used for in-field analysis of ciprofloxacin and metronidazole tablet samples collected in three cities in Cameroon. The contents results obtained for each sample with the two strategies were close and not statistically different. Nevertheless, the first one is easier to implement and the second is the best regarding model diagnostic measures and accuracy profiles. Two samples were found to be noncompliant in terms of content, and these results were confirmed using high-performance liquid chromatography taken as the reference method.