Applied Spectroscopy

The applicability of confocal Raman microscopy for characterizing thin liquid-crystal (LC) filled polymer capsules obtained by photoenforced stratification is demonstrated. The investigated structure consists of an array of polymer capsules (typical size 500 × 500 × 20 μm) filled with LC material and is made by photopolymerization of a mixture of monomers and LC. Such an array can be used as the electro-optical component in liquid crystal displays. Confocal Raman microscopy does not require complex sample preparation, is non-invasive, and is shown to have adequate spatial and depth resolution. Although Raman spectroscopy is inherently insensitive, the use of data preprocessing and computational modeling makes it possible to quantify both the conversion of monomer to polymer and the compositions of both the polymer-rich and the LC-rich phase.

Fourier transform infrared (FT-IR) imaging was used to successfully explore several factors influencing the dissolution of poly(ethylene oxide). The effect of the degree of crystallinity on the rate of dissolution of mid-range molecular weight PEO was negligible over the temperature ranges studied. The influence of molecular weight on polymer dissolution was found to be much greater than the changes in morphology. An examination of the polymer and solvent images and absorbance profiles, compared with the results of the bulk polymer/solvent boundary movement, confirmed this relationship. An investigation of the bulk polymer/solvent boundary using a crystalline-sensitive polymer band showed the crystalline to amorphous phase change occurred over a short distance. Moreover, solvent diffusion ahead of the bulk polymer/solvent front was minimal, most likely a result of the required phase change, which in turn regulated the degree of solvent ingress. Modeling of the dissolution was performed using the Peppas (power law) model. Physical parameters of the dissolution process were obtained from fitting the release profiles to the power law (fraction released = k × tⁿ, where k is the dissolution rate constant and n is the release exponent). Results indicated the model worked well to describe dissolution at all molecular weights. By varying the number of data points input to the model and then comparing the generated graphs, it becomes clear that not only does the dissolution slow down over the course of the experiment, but an increase in molecular weight enhances this effect. The effect of different types of drug on the rate of polymer dissolution was also studied. The dissolution of neat polymer was compared to the dissolution of polymer containing 10% (by weight) of theophylline, etophylline, or testosterone. The general trend of all the dissolution curves was the same, with the addition of etophylline and testosterone tracing almost the same route in terms of movement of the bulk polymer/solvent front.

Nylons are an important class of synthetic polymers, from an industrial, as well as forensic, perspective. A spectroscopic method, such as Fourier transform infrared (FT-IR) spectroscopy, is necessary to determine the nylon subclasses (e.g., nylon 6 or nylon 6,6). Library searching using absolute difference and absolute derivative difference algorithms gives inconsistent results for identifying nylon subclasses. The objective of this study was to evaluate the usefulness of peak ratio analysis and multivariate statistics for the identification of nylon subclasses using attenuated total reflection (ATR) spectral data. Many nylon subclasses could not be distinguished by the peak ratio of the N–H vibrational stretch to the sp³ C–H₂ vibrational stretch intensities. Linear discriminant analysis, however, provided a graphical visualization of differences between nylon subclasses and was able to correctly classify a set of 270 spectra from eight different subclasses with 98.5% cross-validated accuracy.

External reflection Fourier transform infrared spectroscopy (ERFTIRS) has been used to obtain spectra of monolayers of the hydrocarbon surfactant octaethylene glycol monodecyl ether (C₁₀E₈) and the fluorocarbon surfactant ammonium perfluorononanoate (APFN) at the expanding liquid surface of an overflowing cylinder. The use of target factor analysis (TFA) to separate out the contributions of water, adsorbed surfactant, and dissolved surfactant is demonstrated. For both surfactants, there is a linear relationship between the component weight of the adsorbed surfactant, obtained by TFA, and the surface excess determined independently by ellipsometry or neutron reflection. This linear relationship suggests that the monolayers behave like isotropic films with a constant density. A sensitivity of less than 10% of a monolayer is demonstrated. The benefits of using a multivariate curve fitting procedure to analyze sets of ER-FTIR spectra are discussed and some potential pitfalls are identified. This technique is also applicable to static interfaces.

In this paper we describe the application and characterization of zinc oxide (ZnO) nanowires in an infrared (IR) chemical sensing system for the detection of volatile organic compounds (VOCs). Under suitable conditions, we grew ZnO nanowires on the surfaces of IR internal reflection elements (IREs) and obtained successful results for the detection of VOCs. ZnO nanowires offer a large surface area to effectively adsorb the examined species; the sensitivity of these IR sensing systems was increased by 3- to 15-fold after surface treatment with the ZnO nanowires. To explore the performance of this type of sensor, we correlated the morphologies of the ZnO nanowires grown on the surfaces of the IREs with the adsorption behavior observed during the sensing of the VOCs. To characterize the properties of the ZnO nanowires during the detection of VOCs having a range of functionalities, we classified the VOCs and examined their enrichment factors by comparing the IR signals detected in the presence and absence of the ZnO nanowires. Our results indicate that the ZnO nanowires exhibited better performance for the detection of aromatic-type VOCs than they did for non-aromatic compounds. For quantitative analyses, we examined several compounds for their responses toward varying quantities of injected VOCs. Our results indicate that the IREs treated with ZnO nanowires display acceptable linearity in their standard curves; the linear regression coefficients were higher than 0.995 for a range of volatile compounds.

Surface-enhanced micro-Raman spectroscopy (micro-SERS) was used to detect traces of the hazardous pollutant polycyclic aromatic hydrocarbons (PAHs) pyrene and benzo[c]phenanthrene deposited onto a calix[4]arene-functionalized Ag colloidal surface. High spectral reproducibility and very low molecular detection limits (10⁻⁸ M) were obtained by using 25,27-carboethoxy-26,28-hidroxy-p-tert-butylcalix[4]arene as host molecule. Films of immobilized aggregated Ag nanoparticles, obtained by chemical reduction with hydroxylamine, were prepared by direct adhesion on a glass surface. The influence of the aggregation degree of the initial Ag nanoparticles on the micro-SERS detection effectiveness was checked. Different relative concentrations of the host (calixarene receptor) and the guest (PAHs) were attempted in order to optimize detection of the pollutant. The obtained results indicated that the detection limit is much lower in the case of benzo[c]phenanthrene than in pyrene when exciting with the 785 nm line of a diode laser. A detailed interpretation of the Raman spectra was accomplished in order to obtain more information about the interaction mechanism of the host-guest complex, which could be useful in the future for the design of powerful detection systems.

A technique for distinguishing biological material based on surface-enhanced Raman scattering (SERS) is reported in this work. Of particular interest is biological material that can be airborne. Silver colloidal particles with diameters in the range 10 to 20 nm and with a characteristic ultraviolet–visible (UV-VIS) absorption band at 400 nm were used to obtain SERS spectra of Escherichia coli, Pseudomonas aeruginosa, and Salmonella typhimurium bacteria and a number of tree and grass pollens (Cupressus arizonica (cypress), Sequoia sempervirens (redwood), Populus deltoides (cottonwood), Poa pratensis (Kentucky bluegrass), and Anthoxanthum odoratum (sweet vernal grass)). While differences in the SERS spectra among the bacteria were small, we found that the pollen spectra we analyzed could readily be distinguished from the bacteria spectra, and there were significant differences between pollen from different families. In order to obtain reproducible results, we studied the parameters controlling the interaction between the analyte and the nanoscale metallic surface. Our results show that the volume ratio of analyte to colloidal particles must be within a narrow range of values to optimize the signal-to-noise ratio of the SERS spectra and minimize the fluorescence from the analyte. Also, we found that the time-dependent behavior of colloidal/bacterial suspensions (or adsorption rate of the silver colloid particles on the bacteria) is strongly dependent on pH, density of bacteria in solution, and even, to some extent, the type of bacteria.

Glucose concentrations of in vitro human aqueous humor (HAH) samples from cataract patients were determined using 785 nm Raman spectra and partial least squares (PLS) calibration. PLS models were created from spectra of prepared calibration solutions rather than aqueous humor samples. Spectra were obtained with an excitation energy (100 mW for 150 s), which was higher than can be applied in vivo, to decrease the models' contribution to prediction uncertainty. The solutions contained experimentally designed levels of glucose, bicarbonate, lactate, urea, and ascorbate. Multiplicative signal correction of spectra helped compensate for the ±20% drift in laser power observed at the sample over six noncontiguous days of data collection. Seventeen HAH samples containing 38–775 mg/dL of glucose exhibited a root-mean-square error (RMSEP) of 22 mg/dL, coefficient of determination (r²) of 0.989, and bias of 6 mg/dL when predicted from lower energy (30 s) spectra collected contemporaneously with fifty calibration spectra. Similar results were obtained even when spectral data were gathered separately for human aqueous humor samples and calibration samples: 10 HAH samples, calibrated on 25 solutions measured 3.6 weeks earlier, exhibited an RMSEP of 23 mg/dL, r² of 0.992, and bias of 9 mg/dL. The results demonstrate progress toward the determination of glucose levels in patient-derived aqueous humor using laboratory-derived “artificial aqueous humor” calibration solutions.

Norfloxacin (NFX), a fluoroquinolone, was encapsulated in multi-lamellar liposomes (MLV) of soy-bean phosphatidylcholine at pH 7.0. The observed affinity of this class of drugs for hydrophobic environments, such as phospholipid bilayers, could lead to a better understanding of the mechanism of uptake in bacteria. The fluorescent properties of NFX were examined both free in solution and in MLV, using anisotropy and fluorescence quenching measurements. The latter data was treated with a chemometric method to deconvolute the overlapped spectra of zwitterionic and neutral species of NFX in equilibrium at this pH. The results show that NFX incorporates into the lipidic bilayers with two different distributions of species: the zwitterionic form in the lipid/aqueous interface, and the neutral one, more towards the center of the bilayer.

A method combining laser-induced fluorescence and principal component analysis to detect and discriminate between algal and fungal growth on insulator materials has been studied. Eight fungal cultures and four insulator materials have been analyzed. Multivariate classifications were utilized to characterize the insulator material, and fungal growth could readily be distinguished from a clean surface. The results of the principal component analyses make it possible to distinguish between algae infected, fungi infected, and clean silicone rubber materials. The experiments were performed in the laboratory using a fiber-optic fluorosensor that consisted of a nitrogen laser and an optical multi-channel analyzer system.

Fluorescence piezo-spectroscopy (PS) was applied to evaluate the residual stress fields stored in a multilayered Al₂O₃/3Y-TZP (3 mol % Y₂O₃-stabilized ZrO₂) composite using the chromophoric fluorescence spectra of Al₂O₃. The PS results were compared with a theoretical stress distribution in the laminate, calculated according to a repeating unit cell model. However, in practical fluorescence spectroscopy, each measurement point corresponded to a finite volume of material, within which the scattered light experienced fluorescence wavelengths characteristic of the local (weight-average) stress fields. Because of the finite volume of material probed in PS measurements, a comparison between the experimental and calculated values requires that the calculated stresses be convoluted according to the depth-response function of the probe. A pinhole aperture incorporated in the Raman microprobe was used to control the collection probe depth and to modulate the portion of the whole fluorescence emission reaching the detector. According to calibrations of the probe depth and probe response function, probe-convoluted stresses were obtained and a spatially resolved mapping of residual stresses could be obtained.

We propose a new scheme for a phase-modulation fluorometer (PMF) in which a photomultiplier tube (PMT) is used as a photo-detector whose gain is modulated sinusoidally with a burst signal of period T and duty ratio 0.5. The carrier wave of the burst modulation signal is synchronized with an incident fluorescence signal. In order to modulate the gain of the PMT, one of the dynodes in the PMT was deeply biased and the burst signal was superimposed. Because the fluorescence signal is converted to a direct current (dc) signal by the PMT internal modulation, we can make the value of the load resistance of the PMT relatively large under the condition τ ≤ T/2, where τ is a time constant of a low-pass filter attached to the output of the PMT. The proposed scheme brings about advantages in sensitivity and noise immunity in detecting weak fluorescence in comparison with those of the conventional PMF. The combined technique of the burst modulation of the gain of the PMT and the alternating current (ac) signal detection alleviates the influence of the background light.

Potential mushroom (Agaricus bisporus) yield of phase II compost is determined by interactions of key quality parameters including dry matter, nitrogen dry matter, ammonia, pH, conductivity, thermophilic microorganisms, C: N ratio, fiber fractions, ash, and certain minerals. This study was aimed at generating robust visible and near-infrared (Vis-NIR) calibrations for predicting potential yield, using spectra from fresh phase II compost. Four compost comparative trials were carried out during the winter and summer months of 2001–2003, under controlled experimental conditions employing six commercially prepared composts, with eight replicate (8 bag) plots per treatment (48 × 8 = 384). The substrates were prepared by windrow or bunker phase I, followed by phase II production. The fresh samples were scanned for Vis-NIR (400–2498 nm) spectra, averaged, transformed, and regressed against the recorded yield by employing a modified partial least squares algorithm. The best calibration model generated from the database explained 84% of yield variation within the data set with a standard error of calibration of 13.75 kg/tonne of fresh compost. The model was successfully tested for robustness with yield results obtained from a validation trial, carried out under similar experimental conditions in early 2004, and the standard error of prediction was 18.21 kg/tonne, which was slightly higher than the mean experimental error (17.94 kg/tonne) of the trial. The accuracy of the model is acceptable for estimating potential yield by classifying phase II substrate as poor (180–220 kg), medium (220–260 kg), and high (260–300 kg) yielding compost. The yield prediction model is being transferred to a new instrument based at Loughgall for routine evaluation of commercial phase II samples.

Surface characterization and catalysis can significantly benefit from the application of generalized two-dimensional (2D) correlation analysis. This two-dimensional approach allows a better resolution of overlapping peaks, can reveal new features not readily observable in the raw spectra, gives clear evidence for spectral intensities that change as an effect of a perturbation applied to the system, and allows the establishment of time sequences for the changes occurring in different spectral features of interest for determining reaction intermediates and/or mechanisms. The interpretation of the synchronous and asynchronous plots was observed to lead to erroneous time sequences when spectral features change in a nonmonotonic way, such as a biphasic or oscillatory behavior, under the influence of a perturbation. We propose a new approach to the 2D correlation analysis to avoid misinterpretation of the results calculated in the asynchronous plot. Progressive correlation analysis (ProCorA) calculates the synchronous plot from the first two spectra of the data matrix and one spectrum is added at every step of the analysis. The sequence of changes can be set up from the progressive evolution of peaks in both the synchronous and asynchronous plots.

An improved method for qualitative and quantitative sampling of bacterial endospores using Fourier transform infrared (FT-IR) microscopy on gold-coated porous alumina membranes is presented. Bacillus subtilis endospores were filtered onto gold-coated alumina membranes serving as substrates. Studies in the mid-infrared (MIR) region revealed the characteristic bacterial absorption spectrum at low surface concentration, while scanning electron microscopy (SEM) images of the same samples provided precise calculation of the surface concentration of the bacterial endospores. Under the conditions of study, the average concentration of endospores was determined to be 1356 ± 35 spores in a 100 × 100 μm² area, with a relative standard deviation of 0.0260. Examination of ten random spots on multiple substrates with FT-IR microscopy apertured to the same area gave an average relative standard deviation of 0.0482 in the signal strength of the amide A band at 3278 cm⁻¹. An extinction cross-section in reflection of σ_ext = (7.8 ± 0.6) × 10⁻⁹ cm²/endospore was calculated for the amide A band at the frequency of its peak absorbance, 3278 cm⁻¹. The absorption cross-section of the amide A band in reflection is estimated to be σ_abs ≈ (2.10 ± 0.12) × 10⁻⁹ cm²/endospore.