Applied Spectroscopy

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High-throughput information extraction from large numbers of Raman spectra is becoming an increasingly taxing problem due to the proliferation of new applications enabled using advances in instrumentation. Fortunately, in many of these applications, the entire process can be automated, yielding reproducibly good results with significant time and cost savings. Information extraction consists of two stages, preprocessing and analysis. We focus here on the preprocessing stage, which typically involves several steps, such as calibration, background subtraction, baseline flattening, artifact removal, smoothing, and so on, before the resulting spectra can be further analyzed. Because the results of some of these steps can affect the performance of subsequent ones, attention must be given to the sequencing of steps, the compatibility of these sequences, and the propensity of each step to generate spectral distortions. We outline here important considerations to effect full automation of Raman spectral preprocessing: what is considered full automation; putative general principles to effect full automation; the proper sequencing of processing and analysis steps; conflicts and circularities arising from sequencing; and the need for, and approaches to, preprocessing quality control. These considerations are discussed and illustrated with biological and biomedical examples reflecting both successful and faulty preprocessing.

The technique of moving-window two-dimensional heterospectral (MW2DHetero) correlation spectroscopy is proposed. This computational method is based on the ideas of perturbation-correlation moving-window two-dimensional (PCMW2D) correlation spectroscopy and two-dimensional heterospectral correlation analysis. Not only small spectral variations, but also detailed bands assignments were captured using the analysis. This method was applied to near-infrared (NIR) spectra in the 10 000–4000 cm⁻¹ region and mid-infrared (mid-IR) spectra in the 5000–1200 cm⁻¹ region, which were simultaneously detected using a dual-region spectrometer. Near-infrared and mid-IR spectra collected during an alcoholic fermentation process using a solution containing glucose and fructose were reported. Slight time differences for the consumption of sugars compared with the production of ethanol were found between 50 and 150 min. It was concluded that these slight time differences are evidence for different consumption times between glucose and fructose during the fermentation process. The result proved a possibility of the selective monitoring of the simultaneous reaction processes between productive and consumptive components.

Ultraviolet–visible (UV-Vis) spectroscopy methodology was developed and utilized for the in situ nanoscale measurement of the size of mineral clay agglomerates in various liquid suspensions. The clays studied were organomodified and unmodified montmorillonite clays (I.44p, Cloisite 93a, and PGN). The methodology was compared and validated against dynamic light scattering (DLS) analysis. The method was able to measure clay agglomerates in solvents in situations where DLS analysis was unsuccessful due to the shapes, polydispersity, and high aspect ratios of the clay particles and the complexity of the aggregates, or dispersion medium. The measured clay agglomerates in suspension were found to be in the nanometer range in the more compatible solvents, and their sizes correlated with the Hansen solubility parameter space distance between the clay modifiers and the solvents. Mass detection limits for size determination were in the range from 1 to 9 mg/L. The methodology thus provides simple, rapid, and inexpensive characterization of clays or particles in the nano- or microsize range in low concentrations in various liquid media, including complex mixtures or highly viscous fluids that are difficult to analyze with DLS. In addition, by combining UV-VIS spectroscopy with DLS it was possible to discern flocculation behavior in liquids, which otherwise could result in false size measurements by DLS alone.

The current study aims to determine lipid profiles in terms of the content and structure of skeletal muscle and adipose tissues to better understand the characteristics of juvenile-onset spontaneous obesity without high fat diet induction. For the purposes of this study, muscle (longissimus, quadriceps) and adipose (inguinal, gonadal) tissues of 10-week-old male DBA/2J and Berlin fat mouse inbred (BFMI) lines (BFMI856, BFMI860, BFMI861) fed with a standard breeding diet were used. Biomolecular structure and composition was determined using attenuated total reflection Fourier transform (ATR FT-IR) spectroscopy, and muscle triglyceride content was further quantifed using high-performance liquid chromatography (HPLC) coupled with an evaporative light scattering detector (ELSD). The results revealed a loss of unsaturation in BFMI860 and BFMI861 lines in both muscles and inguinal adipose tissue, together with a decrease in the hydrocarbon chain length of lipids, especially in the BFMI860 line in muscles, suggesting an increased lipid peroxidation. There was an increase in saturated lipid and triglyceride content in all tissues of BFMI lines, more profoundly in longissimus muscle, where the increased triglyceride content was quantitatively confrmed by HPLC-ELSD. Moreover, an increase in the metabolic turnover of carbohydrates in muscles of the BFMI860 line was observed. The results demonstrated that subcutaneous (inguinal) fat also displayed considerable obesity-induced alterations. Taken together, the results revealed differences in lipid structure and content of BFMI lines, which may originate from different insulin sensitivity levels of the lines, making them promising animal models for spontaneous obesity. The results will contribute to the understanding of the generation of insulin resistance in obesity without high fat diet induction.

To better understand the effect of mechanical stress during the spinning of silk, the protein orientation and conformation of Bombyx mori regenerated silk fibroin (RSF) films have been studied as a function of deformation in a static mode or in real time by tensile-Raman experiments and polarization modulation infrared linear dichroism (PM-IRLD), respectively. The data show that either for step-by-step or continuous stretching, elongation induces the progressive formation of β-sheets that align along the drawing axis, in particular above a draw ratio of 2. The formation of β-sheets begins before their alignment during a continuous drawing. Unordered chains were, however, never found to be oriented, which explains the very low level of orientation of the amorphous phase of the natural fiber. Stress-perturbed unordered chains readily convert into β-sheets, the strain-induced transformation following a two-state process. The final level of orientation and β-sheet content are lower than those found in the native fiber, indicating that various parameters have to be optimized in order to implement a spinning process as efficient as the natural one. Finally, during the stress relaxation period in a step-by-step drawing, there is essentially no change of the content and orientation of the β-sheets, suggesting that only unordered structures tend to reorganize.

It was found that cadmium telluride (CdTe) quantum dots (QDs) with different sizes can have a great sensitizing effect on chemiluminescence (CL) emission from luminal–potassium periodate (KIO₄) system. Levodopa, a widely prescribed drug in the treatment of Parkinson's disease, could inhibit luminal–KIO₄–CdTe QDs CL reaction in alkaline solution. The inhibited CL intensity was proportional to the concentration of levodopa in the range from 8.0 nM to 10.0 μM. The detection limit was 3.8 nM. This method has been successfully applied to determine levodopa in pharmaceutical preparation and human urine and plasma samples with recoveries of 94.1–105.4%. This was the first work for inhibition effect determination of levodopa using a QD-based CL method.

A tunable diode laser (TDL) was used to measure hydrogen chloride (HCl) spectra at 5747 cm⁻¹ (1.74 μm) and temperatures of 25–950 °C in a quartz cell. The purpose was to evaluate the capability of monitoring HCl concentration under pyrohydrolysis conditions using a near-infrared (NIR) laser. These conditions are characterized by 20–40% HCl, 2–40% H₂O, and the presence of metal chloride vapors at temperatures of 600–1000 °C. Spectral peak area measurements of HCl–N₂ mixtures at atmospheric pressure and a path length of 8.1 cm showed linear absorption behavior between concentrations of 5–95% and temperatures of 25–950 °C. Results from the addition of 2–40% water (H₂O) indicate that the HCl peak area relationships are not affected for temperatures of 350–950 °C. Evaporating NiCl₂ within the cell did not show spectral interference effects with HCl between 650 and 850 °C. The results from this work indicate that a near-infrared optical sensor is capable of measuring high HCl concentrations at high temperatures in the presence of high H₂O content during pyrohydrolysis process conditions.

Diffuse reflectance ultraviolet-visible-near-infrared (UV-Vis-NIR) spectroscopy is applied as a means of differentiating various types of writing, office, and photocopy papers (collected from stationery shops in India) on the basis of reflectance and absorbance spectra that otherwise seem to be almost alike in different illumination conditions. In order to minimize bias, spectra from both sides of paper were obtained. In addition, three spectra from three different locations (from one side) were recorded covering the upper, middle, and bottom portions of the paper sample, and the mean average reflectivity of both the sides was calculated. A significant difference was observed in mean average reflectivity of Side A and Side B of the paper using Student's pair t-test. Three different approaches were used for discrimination: (1) qualitative features of the whole set of samples, (2) principal component analysis, and (3) a combination of both approaches. On the basis of the first approach, i.e., qualitative features, 96.49% discriminating power (DP) was observed, which shows highly significant results with the UV-Vis-NIR technique. In the second approach the discriminating power is further enhanced by incorporating the principal component analysis (PCA) statistical method, where this method describes each UV-Vis spectrum in a group through numerical loading values connected to the first few principal components. All components described 100% variance of the samples, but only the first three PCs are good enough to explain the variance (PC1 = 51.64%, PC2 = 47.52%, and PC3 = 0.54%) of the samples; i.e., the first three PCs described 99.70% of the data, whereas in the third approach, the four samples, C, G, K, and N, out of a total 19 samples, which were not differentiated using qualitative features (approach no. 1), were therefore subjected to PCA. The first two PCs described 99.37% of the spectral features. The discrimination was achieved by using a loading plot between PC1 and PC2. It is therefore concluded that maximum discrimination of writing, office, and photocopy paper could be achieved on the basis of the second approach. Hence, the present inexpensive analytical method can be appropriate for application to routine questioned document examination work in forensic laboratories because it provides nondestructive, quantitative, reliable, and repeatable results.

Spectroscopy is often applied when a rapid quantitative analysis is required, but one challenge is the translation of raw spectra into a final analysis. Derivative spectra are often used as a preliminary preprocessing step to resolve overlapping signals, enhance signal properties, and suppress unwanted spectral features that arise due to non-ideal instrument and sample properties. In this study, to improve quantitative analysis of near-infrared spectra, derivatives of noisy raw spectral data need to be estimated with high accuracy. A new spectral estimator based on singular perturbation technique, called the singular perturbation spectra estimator (SPSE), is presented, and the stability analysis of the estimator is given. Theoretical analysis and simulation experimental results confirm that the derivatives can be estimated with high accuracy using this estimator. Furthermore, the effectiveness of the estimator for processing noisy infrared spectra is evaluated using the analysis of beer spectra. The derivative spectra of the beer and the marzipan are used to build the calibration model using partial least squares (PLS) modeling. The results show that the PLS based on the new estimator can achieve better performance compared with the Savitzky–Golay algorithm and can serve as an alternative choice for quantitative analytical applications.

Derivatives are common preprocessing tools, typically implemented as Savitzky–Golay (SG) smoothing derivatives. This work discusses the implementation and optimization of fourth-order gap derivatives (GDs) as an alternative to SG derivatives for processing infrared spectra before multivariate calibration. Gap derivatives approximate the analytical derivative by calculating finite differences of spectra without curve fitting. Gap derivatives offer an advantage of tunability for spectral data as the distance (gap) over which this finite difference is calculated can be varied. Gap selection is a compromise between signal attenuation, noise amplification, and spectral resolution. A method and discussion of the importance of fourth derivative gap selections are presented as well as a comparison to SG preprocessing and lower-order GDs in the context of multivariate calibration. In most cases, we found that optimized GDs led to calibration models performing comparably to or better than SG derivatives, and that optimized fourth-order GDs behaved similarly to matched filters.

The ever-increasing use of fluorescent nanomaterials and micrometersized beads in the life and material sciences requires reliable procedures for the measurement of the key performance parameter fluorescence quantum yield (φ_f) of scattering particle dispersions and reference systems to evaluate the performance of such measurements. This encouraged us to systematically study, both theoretically and experimentally, the optical determination of photoluminescent quantum yield as a function of the scattering and absorption properties of the sample and the illumination geometry with an integrating sphere method. The latter included measurements with a direct and an indirect illumination. As a representative and easyto-prepare reference system, we used ethanolic dispersions of 250 nm sized silica particles and the dye rhodamine 101 and systematically varied the concentration of the dye and particles within the typical ranges of spectroscopic and (bio)analytical applications of fluorescent nanomaterials. Based on our measurements, we recommend indirect sample illumination geometry for the accurate measurement of φ_f of samples with low or unknown absorption and high scattering coefficients such as dispersions of luminescent particles or fluorescent reporters in biological matrices. This finding is of utmost relevance for all (bio)analytical applications of fluorescent nanomaterials ranging from particle labels and probes over assay platforms to safety barcodes.

The development of biopharmaceutical manufacturing processes presents critical constraints, with the major constraint being that living cells synthesize these molecules, presenting inherent behavior variability due to their high sensitivity to small fluctuations in the cultivation environment. To speed up the development process and to control this critical manufacturing step, it is relevant to develop high-throughput and in situ monitoring techniques, respectively. Here, high-throughput mid-infrared (MIR) spectral analysis of dehydrated cell pellets and in situ near-infrared (NIR) spectral analysis of the whole culture broth were compared to monitor plasmid production in recombinant Escherichia coli cultures. Good partial least squares (PLS) regression models were built, either based on MIR or NIR spectral data, yielding high coefficients of determination (R²) and low predictive errors (root mean square error, or RMSE) to estimate host cell growth, plasmid production, carbon source consumption (glucose and glycerol), and by-product acetate production and consumption. The predictive errors for biomass, plasmid, glucose, glycerol, and acetate based on MIR data were 0.7 g/L, 9 mg/L, 0.3 g/L, 0.4 g/L, and 0.4 g/L, respectively, whereas for NIR data the predictive errors obtained were 0.4 g/L, 8 mg/L, 0.3 g/L, 0.2 g/L, and 0.4 g/L, respectively. The models obtained are robust as they are valid for cultivations conducted with different media compositions and with different cultivation strategies (batch and fed-batch). Besides being conducted in situ with a sterilized fiber optic probe, NIR spectroscopy allows building PLS models for estimating plasmid, glucose, and acetate that are as accurate as those obtained from the high-throughput MIR setup, and better models for estimating biomass and glycerol, yielding a decrease in 57 and 50% of the RMSE, respectively, compared to the MIR setup. However, MIR spectroscopy could be a valid alternative in the case of optimization protocols, due to possible space constraints or high costs associated with the use of multi-fiber optic probes for multi-bioreactors. In this case, MIR could be conducted in a high-throughput manner, analyzing hundreds of culture samples in a rapid and automatic mode.

A hyperspectral imaging instrument analyzing fibers between crossed polarizers spectrometrically is presented. The principle of operation is introduced and illustrated briefly by the theory of polarization and birefingence and calculations based on Stokes parameters and Müller matrices. Afterward, the developed instrumentation and results are detailed. Results obtained by the calculations and developed instrumentation indicate that the retardance of birefringent materials can be calculated over a high range and with a high accuracy. In addition, the spatial resolution of the instrument suffices to analyze different regions within a fiber individually. This allows the selection of a region at the center of an analyzed fiber that is shown to provide an optimal signal. The developed software enables analysis of the polarization color and the “normal”, i.e., absorptive color of the sample individually. These features make possible a preliminary identification of fibers, without isolation of the fiber from a microscope slide. The instrument forms a powerful new approach to automated analyses in forensic fiber evidence, as it can establish analyses of morphology, color, and identity of a set of samples in a high-throughput, automated, and objective way.