Applied Spectroscopy

Occupational exposure to airborne wood dust has been implicated in the development of several symptoms and diseases, including nasal carcinoma. However, the assessment of occupational wood dust exposure is usually performed by gravimetric analysis, which is non-specific. In this study, a mid-infrared (mid-IR) diffuse reflection method was adapted for direct on-filter determination of wood dust mass. The cup from the diffuse reflection unit was replaced with a horizontal translational stage and a filter with wood dust was set thereon. Diffuse reflection (DR) spectra were collected from filters with six different diameters in order to average the signal from the most filter surface. Two absorption bands around 1595 and 1510 cm⁻¹, attributed to lignin, were monitored for quantitative analysis. Calibration curves were constructed for standard extrathoracic red oak and yellow pine (aerodynamic particle diameters between 10 and 100 (μm). Calibration of DR intensity versus known wood dust mass on the filter using the Kubelka-Munk function showed a nonlinear dependence for mass of less than 10 mg of wood dust. The experimental data and small-thickness samples indicate that Kubelka-Munk conditions are not obeyed. Alternatively, the pseudo-absorption function log(1/R), for which R is the relative reflectance, while still giving nonlinear dependence against mass, is closer to a linear dependence and has been preferred by other researchers. Therefore, we consider the use of the log(1/R) function for mid-infrared DR analysis of neat, small-thickness wood dust samples. Furthermore, we suggest the use of a silver metal membrane filter for direct on-filter analysis of wood dust rather than the glass fiber filters that have been used previously.

Spectral fingerprinting, as a method of discriminating between plant cultivars and growing treatments for a common set of broccoli samples, was compared for six analytical instruments. Spectra were acquired for finely powdered solid samples using Fourier transform infrared (FT-IR) and Fourier transform near-infrared (NIR) spectrometry. Spectra were also acquired for unfractionated aqueous methanol extracts of the powders using molecular absorption in the ultraviolet (UV) and visible (VIS) regions and mass spectrometry with negative (MS-) and positive (MS+) ionization. The spectra were analyzed using nested one-way analysis of variance (ANOVA) and principal component analysis (PCA) to statistically evaluate the quality of discrimination. All six methods showed statistically significant differences between the cultivars and treatments. The significance of the statistical tests was improved by the judicious selection of spectral regions (IR and NIR), masses (MS+ and MS-), and derivatives (IR, NIR, UV, and VIS).

Terahertz time-domain spectroscopy (THz-TDS) and Fourier transform infrared (FT-IR) spectroscopy were used to generate far-infrared and low-frequency spectral measurements of monomeric lysozyme and lysozyme fibrils. The formation of lysozyme fibrils was verified by the Thioflavin T assay and transmission electron microscopy (TEM). It was evident in the FT-IR spectra that between 150 and 350 cm⁻¹ the two spectra diverge, with the lysozyme fibrils showing higher absorbance intensity than the monomeric form. The broad absorption phenomenon is likely due to light scattered from the fibrillar architecture of lysozyme fibrils as supported by simulation of Rayleigh light scattering. The lack of discrete phonon-like peaks suggest that far-infrared spectroscopy cannot detect vibrational modes between the highly ordered hydrogen-bonded beta-pleated sheets of the lysozyme subunit.

Inorganic phosphorus and nitrogen-phosphorus-potassium (NPK) fertilizers based on phosphates from thermochemically treated sewage sludge ash were analyzed using mid-infrared (mid-IR) and far-infrared (FIR) spectroscopy. The different compounds present in the fertilizers were qualitatively determined with the help of recorded reference spectra of pure substances. Differentiation between various phosphates and other compounds such as sulfates, nitrates, and oxides was possible using combined interpretation of the mid-IR and FIR spectra. The results are in agreement with previous X-ray diffraction (XRD) measurements of the same samples. The main phosphate phases detected were NH₄H₂PO₄, MgHPO₄-3H₂O, Mg₃(PO₄)₂, Ca₅(PO₄)_5Cl, CaHPO₄-2H₂O, Ca(H₂-PO₄)₂-H_2O, and AlPO₄. Furthermore, K₂SO₄, NH₄NO₃, Fe₂O₃, and SiO₂ were identified in the IR spectra. However, ammonium and sulfate compounds were only identified in the mid-IR region but were not detectable in the FIR region.

Silver (Ag) films of varying thickness were simultaneously deposited using physical vapor deposition (PVD) onto six infrared (IR) substrates (BaF₂, CaF₂, Ge, AMTIR, KRS-5, and ZnSe) in order to correlate the morphology of the deposited film with optimal SEIRA response and spectral band symmetry and quality. Significant differences were observed in the surface morphology of the deposited silver films, the degree of enhancement provided, and the spectral appearance of para-nitrobenzoic acid (PNBA) cast films for each silver-coated substrate. These differences were attributed to each substrate's chemical properties, which dictate the morphology of the Ag film and ultimately determine the spectral appearance of the adsorbed analyte and the magnitude of SEIRA enhancement. Routine SEIRA enhancement factors (EFs) for all substrates were between 5 and 150. For single-step Ag depositions, the following ranking identifies the greatest SEIRA enhancement factor and the maximum absorption of the 1345 cm⁻¹ spectral marker of PNBA at the optimal silver thickness for each substrate: BaF₂ (EF = 85 ± 19, 0.059 A, 10 nm Ag) > CaF₂ (EF = 75 ± 30, 0.052 A, 10 nm Ag) > Ge (EF = 45 ± 8, 0.019 A, 5 nm Ag) > AMTIR (EF = 38 ± 8, 0.024 A, 15 nm Ag) > KRS-5 (EF = 24 ± 1, 0.015 A, 12 nm Ag) > ZnSe (EF = 9 ± 5, 0.008 A, 8 nm Ag). A two-step deposition provides 59% larger EFs than single-step depositions of Ag on CaF₂. A maximum EF of 147 was calculated for a cast film of PNBA (surface coverage = 341 ng/cm²) on a 10 nm two-step Ag film on CaF₂ (0.102 A, 1345 cm⁻¹ symmetric NO₂ stretching band). The morphology of the two-step Ag film has smaller particles and greater particle density than the single-step Ag film.

Dynamic oscillatory experiments and front-face synchronous fluorescence spectroscopy and mid-infrared (mid-IR) spectroscopy have been used to investigate structure evolution, at the macroscopic and molecular levels, during milk acidification kinetics. The studies were performed using skim milk, at two different temperatures (30°C and 40°C), to which was added glucono-δ-lactone (GDL) to generate different structural changes in casein micelles and gels. Synchronous fluorescence spectra were recorded in the 250–500 nm excitation wavelength range using an offset of 80 nm between the excitation and emission monochromators for each system during the 300 min acidification kinetics. The change in the fluorescence intensity at 281 nm reflects the pH-induced physicochemical changes of casein micelles and, in particular, structural changes in the micelles in the pH range 5.5–5.0. Regarding mid-infrared spectroscopy, the region located between 1700 and 1500 cm⁻¹, corresponding to the amide I and II bands, and the 1500–900 cm⁻¹ region, called the fingerprint region, were considered for the characterization of milk coagulation kinetics. Changes in the absorbance at 1063 cm⁻¹ as a function of pH for kinetics recorded at 30°C and 40°C reflected pH-induced phosphate dissolution in the pH range 5.5–5.0. Compared to rheometry, which reveals microstructure changes only in the gel state, spectroscopic methods make it possible to monitor molecular structure changes in micelles throughout the acidification processes.

Data from total synchronous fluorescence spectroscopy (TSFS) measurements of normal and malignant breast tissue samples are introduced in supervised self-organizing maps, a type of artificial neural network (ANN), to obtain diagnosis. Three spectral regions in both TSFS patterns and first-derivative TSFS patterns exhibited clear differences between normal and malignant tissue groups, and intensities measured from these regions served as inputs to neural networks. Histology findings are used as the gold standard to train self-organizing maps in a supervised way. Diagnostic accuracy of this procedure is evaluated with sample test groups for two cases, when the neural network uses TSFS data and when the neural network uses data from first-derivative TSFS. In the first case diagnostic sensitivity of 87.1% and specificity of 91.7% are found, while in the second case sensitivity of 100% and specificity of 94.4% are achieved.

This study focuses on the spectrofluorimetric behavior of the camptothecin derivative 7-ethyl-10-hydroxycamptothecin (SN-38) alone and in the presence of organized media and also on its potential analytical applications. SN-38 displays native fluorescence in both lactone and carboxylate form, which has been the base for development of two spectrofluorimetric methods, one for the lactone form (acidic media) and another for the carboxylate form (basic media). In an attempt to improve the understanding of SN-38, its interaction with several cyclodextrins and surfactants has been studied using spectrofluorimetry. Consequently, the optimal working conditions for the determination of SN-38 have been established in both the presence and the absence of organized media. The proposed methods were applied to human urine, using liquid–liquid extraction for clean-up of the samples, with satisfactory recoveries. No interference of the urine matrix was observed.

A combination of laser-induced breakdown spectroscopy (LIBS) and artificial neural networks (ANNs) has been used for the identification of polymer materials, including polypropylene (PP), polyvinyl chloride (PVC), polytetrafluoroethylene (PTFE), polyoxymethylene (POM), polyethylene (PE), polyamide or nylon (PA), polycarbonate (PC) and poly(methyl methacrylate) (PMMA). After optimization of the experimental setup and the spectrum acquisition protocol, successful identification rates between 81 and 100% were achieved using spectral features gathered from single spectra without averaging (1 second acquisition time) over a wide spectral range (240–820 nm). Furthermore, ten different materials based on PVC were tested using the identification procedure. Correct identifications were obtained as well. Sorting of the materials into sub-categories of PVC materials according to their charges (concentration in trace elements such as Ca) was performed. The demonstrated capacities fit, in practice, the needs of plastic-waste sorting and of producing high-grade recycled plastic materials.

The basic principles and the application of hydride-generation multichannel atomic fluorescence spectrometry (HG-MC-AFS) in soil analysis are described. It is generally understood that only one or two elements can be simultaneously detected by commonly used one- or two-channel HG-AFS. In this work, a new sample-sensitive and effective method for the analysis of arsenic, bismuth, tellurium, and selenium in soil samples by simultaneous detection using HG-MC-AFS was developed. The method detection limits for arsenic, bismuth, tellurium, and selenium are 0.19 μ/g, 0.10 μg/g, 0.11 μg/g, and 0.08 μg/g, respectively. This method was successfully applied to the simultaneous determination of arsenic, bismuth, tellurium, and selenium in soil samples.

We studied the surface reactions of a LiCoO₂/Li cell under high-voltage conditions using X-ray photoelectron spectroscopy (XPS), X-ray absorption spectroscopy (XAS), and two-dimensional correlation spectroscopy (2D-COS). 2D XPS correlation spectra show that Li₂CO₃ is formed first by decomposition of the organic solvents, and then polycarbonate, which is formed by polymerization of the electrolytes, is produced on the cathode surface of the LiCoO₂/Li system under high-voltage conditions. XAS measurements also confirm that the solid electrolyte interface (SEI) layer is formed on the LiCoO₂ electrode by decomposition of the organic solvents. The thickness of the SEI layer is less than 100 Å.

A visible-attenuated total reflection (visible-ATR) device was designed to provide a method for directly determining the relative tint strength in high-strength inks. This device showed good reproducibility and the spectra could be correlated to known values of relative tint strength in viscous, highly pigmented inks well within the industry-acceptable error (±5% tint strength). The results of the visible-ATR measurements were compared to those from mid-infrared (mid-IR) and near-infrared (NIR) spectroscopy and the capabilities of those techniques for determining ink strength. Mid-IR analysis was able to directly quantify relative tint strengths, as well as correlating to known values, and to qualify ink products by spectral matching. NIR analysis was able to quantify the tint strength based on the vehicle concentrations in the NIR region. The visible region of the NIR spectrometer was not able to be used for quantification. The vis-ATR and mid-IR spectra showed changes over the time scale of minutes, indicating self-stratification of the pigment and varnish.

The transfer of a multivariate calibration model for quantitative determination of diethylene glycol (DEG) contaminant in pharmaceutical-grade glycerin between five portable Raman spectrometers was accomplished using piecewise direct standardization (PDS). The calibration set was developed using a multi-range ternary mixture design with successively reduced impurity concentration ranges. It was found that optimal selection of calibration transfer standards using the Kennard–Stone algorithm also required application of the algorithm to multiple successively reduced impurity concentration ranges. Partial least squares (PLS) calibration models were developed using the calibration set measured independently on each of the five spectrometers. The performance of the models was evaluated based on the root mean square error of prediction (RMSEP), calculated using independent validation samples. An F-test showed that no statistical differences in the variances were observed between models developed on different instruments. Direct cross-instrument prediction without standardization was performed between a single primary instrument and each of the four secondary instruments to evaluate the robustness of the primary instrument calibration model. Significant increases in the RMSEP values for the secondary instruments were observed due to instrument variability. Application of piecewise direct standardization using the optimal calibration transfer subset resulted in the lowest values of RMSEP for the secondary instruments. Using the optimal calibration transfer subset, an optimized calibration model was developed using a subset of the original calibration set, resulting in a DEG detection limit of 0.32% across all five instruments.

The data obtained in confocal Raman microscopy (CRM) depth profiling experiments with dry optics are subjected to significant distortions, including an artificial compression of the depth scale, due to the combined influence of diffraction, refraction, and instrumental effects that operate on the measurement. This work explores the use of (1) regularized deconvolution and (2) the application of simple rescaling of the depth scale as methodologies to obtain an improved, more precise, confocal response. The deconvolution scheme is based on a simple predictive model for depth resolution and the use of regularization techniques to minimize the dramatic oscillations in the recovered response typical of problem inversion. That scheme is first evaluated using computer simulations on situations that reproduce smooth and sharp sample transitions between two materials and finally it is applied to correct genuine experimental data, obtained in this case from a sharp transition (planar interface) between two polymeric materials. It is shown that the methodology recovers very well most of the lost profile features in all the analyzed situations. The use of simple rescaling appears to be only useful for correcting smooth transitions, particularly those extended over distances larger than those spanned by the operative depth resolution, which limits the strategy to the study of profiles near the sample surface. However, through computer simulations, it is shown that the use of water immersion objectives may help to reduce optical distortions and to expand the application window of this simple methodology, which could be useful, for instance, to safely monitor Fickean sorption/desorption of penetrants in polymer films/coatings in a nearly noninvasive way.

When resolving mixture data sets using self-modeling mixture analysis techniques, there are generally a range of possible solutions. There are cases, however, in which a unique solution is possible. For example, variables may be present (e.g., m/z values in mass spectrometry) that are characteristic for each of the components (pure variables), in which case the pure variables are proportional to the actual concentrations of the components. Similarly, the presence of pure spectra in a data set leads to a unique solution. This paper will show that these solutions can be obtained by applying angle constraints in combination with non-negativity to the solution vectors (resolved spectra and resolved concentrations). As will be shown, the technique goes beyond resolving data sets with pure variables and pure spectra by enabling the analyst to selectively enhance contrast in either the spectral or concentration domain. Examples will be given of Fourier transform infrared (FT-IR) microscopy of a polymer laminate, secondary ion mass spectrometry (SIMS) images of a two-component mixture, and energy dispersive spectrometry (EDS) of alloys.