Chain of custody for samples of live crude oil using visible-near-infrared spectroscopy

In order to design oil production facilities and strategies, it is necessary to acquire crude oil samples from subsurface formations in oil wells in so-called openhole prior to production. In some environments, such as deepwater production of oil, decisions of huge economic importance are based on such samples. To date, there has been little quality control to verify that the crude oils collected in the sample bottles and analyzed up to a year later in the laboratory have any relation to the actual crude oils in the subsurface reservoirs. These high-pressure samples can undergo myriad deleterious alterations. Here, we introduce the chain-of-custody concept to the oilfield. The visible-near-infrared spectrum of the crude oil is measured in situ in the wellbore at the point of sample acquisition. This spectrum is compared with the spectrum measured on putatively the same fluid in the laboratory at the start of laboratory sample analysis. First, quantitative assessment is made of whether the fluid in the (high-pressure) sample bottle remains representative of formation fluids. Second, any specific changes in the spectrum of the fluid can be related to possible process control failures. Here, the entire process of chain of custody is proven. The chain of custody process can rapidly become routine in the petroleum industry, thereby significantly improving the reliability of any process that depends on fluid property determination.     

Identification of oil contaminants on polymer coated beverage cans using fluorescence spectroscopy

In a recent publication we introduced a novel method for detection of impurities on beverage can surfaces using Raman spectroscopy. While investigating the technique, limitations emerged due to the low sensitivity of Raman scatter. This is a particular problem with the largest contributor of impurities in beverage cans: lubricants employed in the manufacturing process. This paper presents an alternative approach, using the more sensitive technique of fluorescence spectroscopy to tackle the same problem. Measurements using fluorescence spectroscopy were conducted indirectly in a cuvette as well as directly on a can surface with the aid of fiber optics. The chemometrics methods of linear discriminant analysis (LDA) and principal components analysis (PCA) were used to classify acquired spectra as belonging to one of the 16 investigated lubricants. Fiberoptic scans revealed that a successful detection and recognition of lubricant is possible down to a volume of 0.5 microL deposited on the can surface. Contaminant detection was possible at even lower levels down to 0.01 microL, but reliable identification proved difficult at such low volumes. Indirect measurements of lubricants dissolved in cyclohexane yielded the lowest detection limits between 1-0.1 ppb.     

Nonlinear four-way kinetic-excitation-emission fluorescence data processed by a variant of parallel factor analysis and by a neural network model achieving the second-order advantage: malonaldehyde determination in olive oil samples

Four-way data were obtained by recording the kinetic evolution of excitation-emission fluorescence matrices for the product of the Hantzsch reaction between the analyte malonaldehyde and methylamine. The reaction product, 1,4-disubstituted-1,4-dihydropyridine-3,5-dicarbaldehyde, is a highly fluorescent compound. The nonlinear nature of the kinetic fluorescence data has been demonstrated, and therefore the four-way data were processed with parallel factor analysis combined with a nonlinear pseudounivariate regression, based on a quadratic polynomial fit, and also with a recently introduced neural network methodology, based on the combination of unfolded principal component analysis, residual trilinearization, and radial basis functions. The applied chemometric strategies are not only able to adequately model the nonlinear data but also to successfully determine malonaldehyde in olive oil samples. This is possible since the experimentally recorded four-way data, modeled with the above-mentioned advanced chemometric approaches, permit the achievement of the second-order advantage. This allows us to predict the analyte concentration in a complex background, in spite of the nonlinear behavior and in the presence of uncalibrated interferences. The present work is a new example of the use of higher-order data for the resolution of a complex nonlinear system, successfully employed in the context of food chemical analysis.     

Interference-free analysis using three-way fluorescence data and the parallel factor model. Determination of fluoroquinolone antibiotics in human serum

Three-way fluorescence data and multivariate calibration based on parallel factor analysis (PARAFAC) are combined for the simultaneous quantitation of three fluoroquinolone anitibiotics (norfloxacin, enoxacin, and ofloxacin) in human serum samples. The three analytes can be adequately determined with limits of detection of 0.2, 3.0, and 0.5 microg L(-1), respectively, with minimum experimental effort. The selected analytical methodology fully exploits the so-called second-order advantage of the employed three-way data, allowing obtaining individual concentrations of calibrated analytes in the presence of any number of uncalibrated (serum) components. In contrast to PARAFAC, less satisfactory results were obtained with a multidimensional partial least-squares (nPLS) model trained with the same calibration set.     

Quantitative Raman spectroscopy of highly fluorescent samples using pseudosecond derivatives and multivariate analysis

Intense luminescence backgrounds cause significant problems in quantitative Raman spectroscopy, particularly in multivariate analysis where background suppression is essential. Taking second derivatives reduces the background, but differentiation increases the apparent noise that arises on spectra recorded with CCD detectors due to random, but fixed, variations in the pixel-to-pixel response. We have recently reported a very general method for correcting CCD fixed-pattern response in which spectra are taken at two or more slightly shifted spectrometer positions and are then subtracted to give a derivative-like shifted, subtracted Raman (SSR) spectrum. Here we show that differentiating SSR data (which has inherently higher S/N than the undifferenced data) yields spectra that are similar to those that are obtained from the normal two-step differentiation process and can be characterized as pseudo-second-derivative, PSD, spectra. The backgrounds are suppressed in the PSD spectra, which means they can be used directly in multivariate data analysis, but they have significantly higher S/N ratios than do simple second derivatives. To demonstrate the improvement brought about by using PSD spectra, we have analyzed known samples, consisting of simple binary mixtures of methanol and ethanol doped with laser dye. When the background levels of all samples included in the models were < or =10x greater than the intensity of the strongest Raman bands, partial least-squares calibration of the PSD data gave a standard error of prediction of 3.2%. Calibration using second derivatives gave a prediction error which was approximately twice as large, at 6.5%; however, when data with background levels . approximately 100x larger than the strongest Raman bands were included, the noise on the second-derivative spectra was so large as to prevent a meaningful calibration. Conversely, the PSD treatment of these samples gave a very satisfactory calibration with a standard error of prediction (3.3%) almost identical to that obtained when the most fluorescent samples were excluded. This method clearly has great potential for general purpose Raman analytical chemistry, because it does not depend on specialized equipment, is computationally undemanding, and gives stable and robust calibrations, even for samples in which the luminescence background level fluctuates between the extremes of being practically zero and completely dominating the Raman signal.     

Effects of mild heating and acidification on the molecular structure of milk components as investigated by synchronous front-face fluorescence spectroscopy coupled with parallel factor analysis

This paper reports the potential of synchronous front-face fluorescence spectroscopy in the characterization at the molecular level of milk changes during mild heating from 4 to 50 degrees C and acidification in the pH range of 6.8 to 5.1. Synchronous fluorescence spectra were collected in the 250-550 nm excitation wavelength range using offsets of 20, 40, 60, 80, 100, 120, 140, 160, 180, 200, and 240 nm between excitation and emission monochromators. The potential of parallel factor (PARAFAC) analysis in the decomposition of the whole synchronous fluorescence data set into the contribution of each of the fluorescent compounds present in milk has been investigated for heating and acidification data sets. Models were fitted from 1 to 7 components. Considering the core consistency values, PARAFAC models with three components have been considered. The first three components explained 94.43% and 94.13% of the total variance for heating and acidification data sets, respectively. The loading profiles of the first and second components derived from PARAFAC analysis performed on heating and acidification data sets corresponded quite well with the characteristics of tryptophan and vitamin A fluorescence spectra, respectively. The third component corresponded to the riboflavin fluorescence spectrum. Considering the heating experiment, the profile of the concentration mode for the second component showed large variations according to the temperature, which were assigned to the melting of triglycerides between 4 and 50 degrees C. For the acidification experiment, drastic changes in the concentration modes of the three components were observed for pH below 5.6, in agreement with structural changes in casein micelles.     

Solid-liquid extraction fluorescence line narrowing spectroscopy of fluoroquinolones in aqueous samples

We present a simple, selective, and sensitive method for the analysis of fluoroquinolones in water samples without previous separation. Octadecyl silica membranes are used with the dual purpose of sample preconcentration and solid substrate for fluorescence line narrowing spectroscopy. Measurements at liquid helium temperature (4.2 K) are easily made with the aid of a cryogenic fiber-optic probe. The entire procedure takes less than 15 minutes per sample and it consumes only 100 microL of organic solvent. Unambiguous fluoroquinolone determination is accomplished via wavelength-time matrices, which provide simultaneous information on spectral peak purity and fluorescence lifetime. We show that 10 mL of water sample are enough to detect analyte concentrations at parts-per-billion levels. The potential of this approach for the analysis of real world samples is demonstrated with the analysis of a synthetic mixture of seven fluoroquinolones spiked in a heavily contaminated water sample.     

Characterization of chiral interactions using fluorescence anisotropy

This work details a study whereby the characterization of chiral selectors and identification of optimal separation conditions is evaluated by steady-state fluorescence anisotropy measurements. Earlier studies in our laboratory have shown fluorescence anisotropy to be an effective tool in evaluating chiral recognition, and in this study, the feasibility of characterizing chiral separation systems by the technique is evaluated. Four chiral selectors were examined under various conditions to explore correlation between chiral separation ability and differences in the steady-state fluorescence anisotropy of the enantiomers measured under similar conditions. A good correlation between the fluorescence anisotropy data and separation data was observed with R2 values ranging from 0.9279 to 0.9959. The fluorescence anisotropy measurements were examined under conditions that mimicked chiral separation conditions and the feasibility of a priori optimization of chiral separations is discussed.     

近红外透射光谱聚类分析快速鉴别食用油种类

以8种食用油纯油的43个样品为对象,研究了近红外透射光谱结合聚类分析法快速鉴别食用油种类的可行性.采集样品在12 500~4 000 cm-1范围内的傅立叶变换近红外透射光谱,利用光谱模式识别法中的聚类分析法对图谱进行定性分类鉴别.实验证明,光谱经二阶导数预处理后,最短距离法、最长距离法和方差平方和法均可准确无误地将食用油样品分为8类,判别模型对预测集样品的准确率达到100%.研究表明,近红外透射光谱结合聚类分析法可以为快速无损鉴别食用油种类提供一种准确可靠的方法.     

Sterol binding assay using surface plasmon fluorescence spectroscopy

We describe the design of a novel in vitro assay to study the interaction of soluble proteins with small hydrophobic sterol ligands. The sterol molecules are incorporated in an artificial membrane system in order to mimic their arrangement found in a biomembrane. The artificial membrane setup is monitored in real time by surface plasmon spectroscopy. Binding of fluorescently labeled soluble protein is observed by optical detection with surface plasmon enhanced fluorescence spectroscopy. By application of the novel assay, we demonstrate that four different oxidized sterol molecules are specifically recognized by the yeast protein Osh5p, a presumed oxysterol binding protein. Osh5p from yeast is the first oxysterol binding protein homologue for which oxysterol binding is shown with this new technique. With the design of our novel in vitro oxysterol binding assay, we have solved the technically challenging difficulty of presenting hydrophobic ligands to hydrophilic proteins in aqueous media.     

Characterization of soils using photoacoustic mid-infrared spectroscopy

This study investigates the use of photoacoustic spectroscopy (PAS) for rapid soil analysis. Photoacoustic spectroscopy requires very minimal sample preparation (air-drying), which is a major advantage compared to the more traditional transmittance technique, which requires time-consuming preparation of pellets. The amount of information contained in the PAS spectra appears to be similar to that contained in transmittance spectra, and the PAS spectra exhibit a large number of bands that can be associated with various soil constituents such as quartz, calcium carbonate, and various types of clay. Comparison with attenuated total reflection (ATR) spectra of saturated soil pastes shows that the PAS spectra provide much more information than the ATR spectra due to the strong water bands present in the latter. PAS quantitative analysis of clay, calcium carbonate, and organic matter is presented, with respective determination errors of approximately 12% clay, approximately 5% CaCO(3), and approximately 0.2% organic matter.     

High-throughput screening of selectivity of melt polymerization catalysts using fluorescence spectroscopy and two-wavelength fluorescence imaging

A new general approach for rapid assessment of polymerization catalysts is introduced. Native fluorescence emission of solid polymers is measured directly in combinatorial 96-microreactor arrays and polymers produced in a laboratory-scale validation reactor. Fluorescence features collected with a CCD-based spectrofluorometer are correlated with chemical properties of interest such as polymer molecular weight, amount of branching, and catalyst selectivity. The approach is illustrated by screening of selectivity of melt polymerization catalysts used in synthesis of an aromatic bisphenol A polycarbonate. Selectivity of catalysts correlated with the ratio of fluorescence intensities at 400 and 500 nm at 340-nm excitation. The relative standard deviation (RSD) in spectroscopic serial measurements was 1-12.5%. This spread included instrument variability (< or = 1% RSD) and sample inhomogeneity. Parallel quantitative screening of catalyst selectivity in combinatorial 96-microreactor arrays was performed as a two-wavelength ratiometric fluorescence imaging through 400- and 500-nm interference filters and showed a good correlation (R2 = 0.994) with serial screening. Our approach is an attractive alternative to traditional separation-based techniques if speed and nondestructive nature of analysis are critical and when the high cross-linking or solvent resistance of polymers complicates traditional analysis.     

On rotational ambiguity in parallel factor analysis

Although, in many cases parallel factor analysis (PARAFAC) resolves the trilinear data arrays to the true physical factors that form the data, i.e., unique solution can be found, the algorithm does not always converge to chemically meaningful solutions. Kiers and Smilde [J. Chemom. 1995; 9: 179-195] rigorously proved that unique decomposition does not hold in cases with ‘rank overlap’. They showed when PARAFAC is applied on a three-way data array which has rank overlap in one of its loading modes; the solution obtained is not unique and at best cannot be easily compared with the underlying physical factors owing to a rotational ambiguity.An aspect which is significantly less documented in the previous publications is the reliable detection of rotational ambiguities in multi-way methods. A few reported methods are based on bilinear models for calculating the feasible bands of three-way data. In this paper we propose a method to calculate feasible bands of resolved profiles of components in three-way methods and visualize the rotational ambiguity in three-way data in the results of the three-way methods. Most of discussion is in the PARAFAC algorithm. The principle behind the algorithm is described in detail and tested for simulated data set. Completely general and exhaustive results are presented for the two-component cases. In particular, the effect of the noise is investigated and a comparison is made between feasible solutions obtained from PARAFAC and matrix-augmented with trilinearity. It is shown that the results obtained from both methods are identical.     

Element-specific detection in capillary electrophoresis using X-ray fluorescence spectroscopy

X-ray fluorescence spectroscopy is demonstrated here as a novel, element-specific detector for capillary electrophoresis. Monochromatic 10 keV X-rays from a synchrotron light source are used to excite core electrons, causing emission of characteristic Kalpha X-ray fluorescence (XRF) lines. Using this technique, XRF energies provide elemental identification, while XRF intensities can be used to quantitate the metal composition of each eluent. An X-ray transparent polymer coupling is used to create a window for the on-line, X-ray detection. This coupling contributes no measurable extra-column variance, and electrophoretic mobilities for the metal complexes used as model solutes are highly reproducible. The combination of XRF detection with capillary electrophoresis (CE-XRF) creates the first on-line detection system that is element-specific, nondestructive, and directly applicable to a broad range of applications including nonelectroactive species. CE-XRF is successfully demonstrated here for high binding-constant complexes of Fe(III), Co(II), Cu(II), and Zn(II). Within a single injection, electropherograms are obtained for each element of interest, with the element identity obtained directly from the emission energy. In contrast with ICPMS, this detection technique is directly on-line and does not require volatilization of the eluent. As a result, element-specific detection is not limited by the sample or the buffer volatility or atomization efficiency. Simultaneous XRF and UV absorbance detection can be used to provide an on-line determination of metal/chelate ratios. Although XRF detection limits are presently only in the 0.1 mM (0.5 ng) range, both collection geometry and incident intensity have yet to be optimized. Further optimization is expected to enhance this detection limit by another 2-3 orders of magnitude. As a result, the advent of XRF detection combined with the separating power of CE presents new possibilities for on-line, element-specific analysis.     

Measurement of polystyrene nanospheres using excimer laser fragmentation fluorescence spectroscopy

Monodisperse polystyrene nanospheres with a mean diameter of 102 nm are photofragmented with 193 nm light in N2 at laser fluences from 1 to 20 J/cm2. Carbon atom fluorescence at 248 nm from the disintegration of the particles is used as a signature of the polystyrene. The normalized fluorescence signals are self-similar with an exponential decay lifetime of approximately 10 ns. At fluences above 17 J/cm2, optical breakdown occurs and a strong continuum emission is generated that lasts significantly longer. A non-dimensional parameter, the photon-to-atom ratio (PAR), is used to interpret the laser-particle interaction energetics. Carbon fluorescence from polystyrene particles is compared with that from soot, and a similarity between the two particles is observed when normalized with PAR. Carbon emission from bulk polystyrene was also measured. Similar emission signals were observed, but the breakdown threshold of the surface is significantly lower at 0.2 J/cm2.     

X射线荧光分析在区域地球化学勘查样品分析中的应用

详细论述了X-射线荧光光谱分析化探样品中24个元素的测试条件、方法及其精密度和准确度。采用粉末压片法,选用国家一级标准物质GBW07401～GBW07408、GBW07423～GBW07430和GBW07301～GBW07312为基准物质,使用经验系数法和康普顿散射线作内标校正基体效应。实验数据说明分析结果可靠,完全满足区域化探要求。     

Automated resolution of nontarget analyte signals in GC x GC-TOFMS data using parallel factor analysis

We previously reported a method for the automated (objective) selection of a PARAFAC model having an appropriate number of factors for mathematical resolution of signal from a target analyte in GC x GC-TOFMS data (i.e., for an analysis in which the identity of the analyte is known a priori). While the previous target method has been successfully applied in several studies, the target method requires that the identity of the analyte be known. Also, multiple applications of the target method are required in cases where several analytes of interest are present in a single subsection of the chromatogram. Thus, having to know the analyte identity a priori restricts the applicability of the automated implementation of PARAFAC. The method presented in this report generalizes the previous method to allow analysis of one or more nontarget analyte signals in a subsection of a GC x GC-TOFMS chromatogram (i.e., for analyses when identities of analyte and interferences are not known a priori), thereby addressing and overcoming the limitations of the target method. Herein, we put the nontarget analyte PARAFAC method into theoretical context and illustrate the mechanics of the method using simulated data. We use real experimental GC x GC-TOFMS data to demonstrate the broad applicability of the method, with various analysis situations selected to illustrate challenging chemical analysis scenarios.     

Label-free parallel screening of combinatorial triazine libraries using reflectometric interference spectroscopy

The parallel reflectometric interference spectroscopy is presented as a label-free optical detection method. A new setup was adapted to accommodate sample carriers in a 96-well microplate. It allows for the first time simultaneous plate imaging by a CCD camera for the parallel detection of specific biomolecular interaction in the microplate wells at heterogeneous phase using direct optical monitoring. The detection of binding events with time resolution enables a highly parallel functional biomolecular interaction analysis (BIA). The combination of this new screening setup with combinatorial solid-phase synthesis is performed in the wells of glass-bottom microplates to accomplish the synthesis and the screening platform within one device. As a model system for a solid-phase substance library, synthesis of a triazine library and the subsequent BIA with four different antibodies were carried out. The presented setup enables a time resolution of 18 s with a total screening time of less than 35 min including baseline adjustment, BIA, and regeneration of the screening device for 96 samples in parallel. The binding studies reveal a fast classification of the different monoclonal and polyclonal antibodies and enable the detection of triazines with high binding affinity. The presented prototype is the first parallelized optical label-free detection system for biomolecular interaction analysis that is suitable for a high-throughput screening based on the 96-well microplate format.     

Characterization of microorganisms using UV resonance Raman spectroscopy and chemometrics

The past decade has seen an increased interest in the application of several physicochemical analytical techniques for the rapid detection and identification of microorganisms. We report the development of UV resonance Raman (UVRR) spectroscopy for the reproducible acquisition of information rich Raman fingerprints from endospore-forming bacteria belonging to the genera Bacillus and Brevibacillus. UVRR was conducted at 244 nm, and spectra were collected in typically 60 s. Cluster analyses of these spectra showed that UVRR spectroscopy could be used to discriminate between these microorganisms to species level, and the clustering pattern from this phenotypic classification was highly congruent with phylogenetic trees constructed from 16S rDNA sequence analysis. Therefore, we conclude that UVRR spectroscopy when coupled with chemometrics constitutes a powerful approach to the characterization and speciation of microorganisms.