Applied Spectroscopy

It has been shown that an increase in sensitivity and selectivity of detection of an analyte can be achieved by tuning the ablation laser wavelength to match that of a resonant gas-phase transition of that analyte. This has been termed resonant laser ablation (RLA). For a pulsed tunable nanosecond laser, the data presented here illustrate the resonant enhancement effect in pure copper and aluminum samples, chromium oxide thin films, and for trace molybdenum in stainless steel samples, and indicate two main characteristics of the RLA phenomenon. The first is that there is an increase in the number of atoms ablated from the surface. The second is that the bandwidth of the wavelength dependence of the ablation is on the order of 1 nm. The effect was found to be virtually identical whether the atoms were detected by use of a microwave-induced plasma with atomic emission detection, by an inductively coupled plasma with mass spectrometric detection, or by observation of the number of laser pulses required to penetrate through thin films. The data indicate that a distinct ablation laser wavelength dependence exists, probably initiated via resonant radiation trapping, and accompanied by collisional broadening. Desorption contributions through radiation trapping are substantiated by changes in crater morphology as a function of wavelength and by the relatively broad linewidth of the ablation laser wavelength scans, compared to gas-phase excitation spectra. Also, other experiments with thin films demonstrate the existence of a distinct laser–material interaction and suggest that a combination of desorption induced by electronic transition (DIET) with resonant radiation trapping could assist in the enhancement of desorption yields. These results were obtained by a detailed inspection of the effect of the wavelength of the ablation laser over a narrow range of energy densities that lie between the threshold of laser-induced desorption of species and the usual analytical ablation regime. Normal ablation employs high-power lasers in an attempt to create a vapor plume without selective vaporization, and with a stoichiometry that accurately represents the stoichiometry of species in the solid sample. RLA, as a method of selective vaporization, appears to provide an opportunity to exploit selective vaporization in new ways.

At Naval Base Point Loma in San Diego, California, a canyon had been filled with construction debris and automotive scrap residue (ASR), the latter of which included lead acid batteries. A magnetic survey and induced potential (IP)/DC resistivity survey showed the presence of anomalies at the western end of the site where historic records indicated that the ASR had been placed. Lead concentration depth profiles were obtained in situ and in real time at the site using a direct push fiber-optic laser-induced breakdown spectroscopy (FO-LIBS) sensor probe. Lead, along with strontium and titanium, was detected at depths of 7 to 8 m bgs. These results provided confirmation that the magnetic/IP anomalies at the site are due to ASR.

In this work, a simple method for experimentally obtaining the value of the damping parameter or a-parameter of the spectral lines emitted by an argon plasma generated at atmospheric pressure is presented. The value of this coefficient indicates the proportion existing between the Lorentzian and Doppler components of the total line profile, which can be approximated to a Voigt function for our experimental conditions. The a-parameter values found were within the value interval recorded in the literature. The results obtained showed that the damping coefficient of the lines next to the fundamental level remains practically constant along the plasma column, whereas for the spectral lines involving high-lying levels, the a-parameter is sensitive to the changes in the electron density in the plasma. In this work it is also proved that the self-absorption phenomenon induces errors in the calculation of a, due to an increase in the broadening of the line profile produced by this phenomenon.

A new commercial energy dispersive X-ray fluorescence spectrometer (EDXRF), applying a three-dimensional geometry and high-energy excitation, was optimized for the quantitative analysis of aerosols deposited on filters. The preliminary results are presented here. First-order calibration curves were obtained for 20 elements deposited on the filters. The accuracy of the applied method and of the obtained calibration curves was checked by the measurement of a standard reference material from NIST. The precision of the analysis for the majority of the analytes was better than 10%. Due to the obtained low detection limits, it is possible to determine the analytes usually present at very low concentrations in ambient air, such as, e.g., Cd, Sb, Cr, and V. It is also possible to decrease significantly the time of analysis or the time of the sampling.

The optical scheme of a near-field dual-beam mode-mismatched thermal-lens detector for capillary electrophoresis with a crossed-beam configuration employing a multimode HeCd laser (325 nm) as an excitation source was optimized. It is shown that a multimode laser can be successfully used as an excitation source in thermal lensing with minimal deviations in thermal responses from Gaussian excitation sources. An equation for diffraction thermal-lens theory for near-field measurements is deduced, and the experimental results agree with the deduced equation. The temperature rise in the capillary was estimated, and the exponential decrease of the signal with time for static conditions and low flow velocities was explained. The optimum configuration of the detector from the viewpoint of the maximum sensitivity and beam sizes was found. The detector provides a significant improvement in the detection limits for model compounds absorbing at 325 nm (nitrophenols) compared to the results obtained with a commercial absorbance detector operating at the same wavelength.

Optical sensing of glucose would allow more frequent monitoring and tighter glucose control for people with diabetes. The key to a successful optical noninvasive measurement of glucose is the collection of an optical spectrum with a very high signal-to-noise ratio in a spectral region with significant glucose absorption. Unfortunately, the optical throughput of skin is low due to absorption and scattering. To overcome these difficulties, we have developed a high-brightness tunable laser system for measurements in the 2.0–2.5 μm wavelength range. The system is based on a 2.3 μm wavelength, strained quantum-well laser diode incorporating GaInAsSb wells and AlGaAsSb barrier and cladding layers. Wavelength control is provided by coupling the laser diode to an external cavity that includes an acousto-optic tunable filter. Tuning ranges of greater than 110 nm have been obtained. Because the tunable filter has no moving parts, scans can be completed very quickly, typically in less than 10 ms. We describe the performance of the present laser system and avenues for extending the tuning range beyond 400 nm.

We present the first elementary model predicting how Raman intensities vary for a range of experimental variables for spatially offset Raman spectroscopy (SORS), a recently proposed technique for the effective retrieval of Raman spectra of subsurface layers in diffusely scattering media. The model was able to reproduce the key observations made from the first SORS experiments, namely the dependence of Raman signal intensities on the spatial offset between the illumination and collection points and the relative contributions to the overall spectrum from the top layer and sub-layer. The application of the SORS concept to a three-layer system is also discussed. The model also clearly indicates that an annular geometry, rather than a point-collection geometry, which was used in the earlier experiments, would yield much improved data.

Measurement of illicit drugs on paper currency is of interest for evidentiary purposes in legal cases involving the drug trade. Current methods, primarily based on mass spectrometry, are destructive and prevent re-analysis of the evidence. This article details a method based on Raman microspectroscopy that is able to collect spectra from individual crystals on the surface of paper currency. Mixtures of isoxsuprine and norephedrine, which are non-pharmacologically active drug surrogates, as well as lidocaine and benzocaine, common excipients in street drugs, were doped in small quantities onto US currency. Significant fluorescence interference resulted from the underlying dollar bill. This work presents two methods for reducing the fluorescence background, photobleaching and background subtraction, which both worked well. Finally, a method for determining the percent composition of individual components in heterogeneous mixtures was developed by systematically sampling the surface of the dollar bill. Results were accurate within a few percent, although the method was quite time consuming.

Raman spectroscopic study of n-hexane was carried out in a cubic zirconia anvil cell up to approximately 2.0 GPa. Under high pressure, the C–H stretching region of the spectrum at 2850–3000 cm⁻¹ shows measurable changes in frequency, bandwidth, and intensity. These Raman bands shift towards higher frequencies with increasing pressure. At about 1.4 GPa, phase transition from liquid to solid was induced by compression, as was simultaneously observed with the built-in microscope.

A key element to improve the analytical capabilities of surface-enhanced Raman spectroscopy (SERS) resides in the performance characteristics of the SERS-active substrate. Variables such as shape, size, and homogeneous distribution of the metal nanoparticles throughout the substrate surface are important in the design of more analytically sensitive and reliable substrates. Electron-beam lithography (EBL) has emerged as a powerful tool for the systematic fabrication of substrates with periodic nanoscale features. EBL also allows the rational design of nanoscale features that are optimized to the frequency of the Raman laser source. In this work, the efficiency of EBL fabricated substrates are studied by measuring the relative SERS signals of Rhodamine 6G and 1,10-phenanthroline adsorbed on a series of cubic, elliptical, and hexagonal nanopatterned pillars of ma-N 2403 directly coated by physical vapor deposition with 25 nm films of Ag or Au. The raw analyte SERS signals, and signals normalized to metal nanoparticle surface area or numbers of loci, are used to study the effects of nanoparticle morphology on the performance of a rapidly created, diverse collection of substrates. For the excitation wavelength used, the nanoparticle size, geometry, and orientation of the particle primary axis relative to the excitation polarization vector, and particularly the density of nanoparticles, are shown to strongly influence substrate performance. A correlation between the inverse of the magnitude of the laser backscatter passed by the spectrometer and SERS activities of the various substrate patterns is also noted and provides a simple means to evaluate possible efficient coupling of the excitation radiation to localized surface plasmons for Raman enhancement.

Perchlorate (ClO₄⁻) has recently emerged as a widespread contaminant in drinking water and groundwater supplies in the United States, and a need exists for rapid detection and monitoring of this contaminant. In this study, surface-enhanced Raman spectroscopy (SERS) was studied as a means of ClO₄⁻ detection, and new sol-gel-based SERS substrates were developed by self-assembly of silver colloidal nanoparticles with various functionalized silane reagents. These substrate materials were tailored to allow detection of ClO₄⁻ in water with improved sorptivity, stability, and sensitivity and with the ability to detect ClO₄⁻ at concentrations as low as 10⁻⁶ M (or 100 μg/L) with good reproducibility. Similar techniques were used to fabricate capillary SERS flow cells by assembling functionalized silver nanoparticles capable of attracting ClO₄⁻ to the SERS surface or the internal wall of glass capillaries. These capillary flow cells could be readily configured to allow for in situ, nondestructive detection of ClO₄⁻ via fiber optics.

Surface-enhanced Raman scattering (SERS) spectra were measured for monolayers of various amino acids: L-methionine (Met), L-cysteine (Cys), L-glycine (Gly), L-leucine (Leu), L-phenylalanine (Phe), and L-proline (Pro) and their homodipeptides (Met-Met, Cys-Cys, Gly-Gly, Leu-Leu, Phe-Phe, and Pro-Pro) deposited onto a colloidal gold surface. Orientation of amino acids and their homodipeptides, as well as specific-competitive interactions of their functional groups with the gold surface, were predicted by detailed spectral analysis of the obtained SERS spectra. The analysis performed allowed us to propose a particular surface geometry for each amino acid and homodipeptide on the gold surface. In addition, we compared the structures of these molecules adsorbed on colloidal gold and silver surfaces.

In vivo identification of early-stage cartilage degradation could positively impact disease progression in osteoarthritis, but to date remains a challenge. The primary goal of this study was to develop an infrared fiber-optic probe (IFOP) chemometric method using partial least squares (PLS1) to objectively determine the degree of cartilage degradation. Arthritic human tibial plateaus (N = 61) were obtained during knee replacement surgery and analyzed by IFOP. IFOP data were collected from multiple regions of each specimen and the cartilage graded according to the Collins Visual Grading Scale of 0, 1, 2, or 3. These grades correspond to cartilage morphology that displayed normal, swelling or softening, superficially slight fibrillation, and deeper fibrillation or serious fibrillation, respectively. The model focused on detecting early cartilage degradation and therefore utilized data from grades 0, 1, and 2. The best PLS1 calibration utilized the spectral range 1733–984 cm⁻¹, and independent validation of the model utilizing 206 spectra to create a model and 105 independent test spectra resulted in a correlation between the predicted and actual Collins grade of R² = 0.8228 with a standard error of prediction of 0.258 with a PLS1 rank of 15 PLS factors. A preliminary PLS1 calibration that utilized a cross-validation technique to investigate the possibility of correlation with histological tissue grade (33 spectra from 18 tissues) resulted in R² = 0.8408 using only eight PLS factors, a very encouraging outcome. Thus, the groundwork for use of IFOP-based chemometric determination of early cartilage degradation has been established.

We built a transient absorption spectrophotometer that can determine transient absorption spectral changes that occur at times as fast as ∼200 ns and as slow as a minute. The transient absorption can be induced by a temperature-jump (T-jump) or by optical pumping from the deep ultraviolet (UV) to the infrared (IR) by use of single ns Nd:YAG laser pulses. Our use of a fiber-optic spectrometer coupled to a XeF flashlamp makes the collection of transient spectra easy and convenient in the spectral range from the near IR (1700 nm) down to the deep UV (200 nm), with high signal-to-noise (S/N) ratios. The spectral resolution is determined by the specific configuration of the fiber-optic spectrometer (grating groove density, fiber diameter, slit width) and varies between 0.3 and 10 nm. The utility of this spectrometer was demonstrated by measuring the rate at which a polymerized crystalline colloidal array (PCCA) of poly(N-isopropylacrylamide) nanogel particles optically switch light due to a T-jump induced by nanosecond 1.9 μm laser pulses. In addition, we measured the rate of optical switching induced by a 3 ns 355 nm pump pulse in PCCA functionalized with azobenzene.

We describe a state-of-the-art tunable ultraviolet (UV) Raman spectrometer for the 193–270 nm spectral region. This instrument allows for steady-state and transient UV Raman measurements. We utilize a 5 kHz Ti-sapphire continuously tunable laser (∼20 ns pulse width) between 193 nm and 240 nm for steady-state measurements. For transient Raman measurements we utilize one Coherent Infinity YAG laser to generate nanosecond infrared (IR) pump laser pulses to generate a temperature jump (T-jump) and a second Coherent Infinity YAG laser that is frequency tripled and Raman shifted into the deep UV (204 nm) for transient UV Raman excitation. Numerous other UV excitation frequencies can be utilized for selective excitation of chromophoric groups for transient Raman measurements. We constructed a subtractive dispersion double monochromator to minimize stray light. We utilize a new charge-coupled device (CCD) camera that responds efficiently to UV light, as opposed to the previous CCD and photodiode detectors, which required intensifiers for detecting UV light. For the T-jump measurements we use a second camera to simultaneously acquire the Raman spectra of the water stretching bands (2500–4000 cm⁻¹) whose band-shape and frequency report the sample temperature.

Fourier transform infrared (FT-IR) single bounce micro-attenuated total reflectance (mATR) spectroscopy, combined with multivariate and artificial neural network (ANN) data analysis, was used to determine the adulteration of industrial grade glycerol in selected red wines. Red wine samples were artificially adulterated with industrial grade glycerol over the concentration range from 0.1 to 15% and calibration models were developed and validated. Single bounce infrared spectra of glycerol adulterated wine samples were recorded in the fingerprint mid-infrared region, 900–1500 cm⁻¹. Partial least squares (PLS) and PLS first derivatives were used for quantitative analysis (r² = 0.945 to 0.998), while linear discriminant analysis (LDA) and canonical variate analysis (CVA) were used for classification and discrimination. The standard error of prediction (SEP) in the validation set was between 1.44 and 2.25%. Classification of glycerol adulterants in the different brands of red wine using CVA resulted in a classification accuracy in the range between 94 and 98%. Artificial neural network analysis based on the quick back propagation network (BPN) and the radial basis function network (RBFN) algorithms had classification success rates of 93% using BPN and 100% using RBFN. The genetic algorithm network was able to predict the concentrations of glycerol in wine up to an accuracy of r² = 0.998.