Study of complexation in methanol/water mixtures by infrared and Raman spectroscopy and multivariate curve resolution-alternating least-squares analysis

The structure of the mobile phase in liquid chromatography plays an important role in the determination of retention behavior on reversed-phase stationary materials. One of the most commonly employed mobile phases is a mixture of methanol and water. In this work, infrared and Raman spectroscopic methods were used to investigate the structure of species formed in methanol/water mixtures. Chemometric methods using multivariate curve resolution by alternating least-squares analysis were used to resolve the overlapped spectra and to determine concentration profiles as a function of composition. The results showed that the structure of these mixtures could be described by a mixture model consisting of four species, namely, methanol, water, and two complexes, methanol/water (1:1) and methanol/water (1:4). The spectral frequencies and concentration profiles found from the Raman and infrared measurements were consistent with one another and with theoretical calculations.     

Study of the hydrolysis of a sulfonylurea herbicide using liquid chromatography with diode array detection and mass spectrometry by three-way multivariate curve resolution-alternating least squares

This research is focused on the development of a novel, automated chemometric method for obtaining relevant chemical information from time-course measurements of an evolving chemical system. This paper describes an investigation of the hydrolysis of Ally, which is a sulfonylurea herbicide. The hydrolysis of this compound is observed at different pHs and temperatures by reversed-phase liquid chromatography using a diode array detector. The data are analyzed using a three-way, multivariate curve resolution technique. Of special interest was the application of a closure constraint in the kinetic dimension followed by the determination of the rate constants for each step of the pathway by using a differential equation solver and nonlinear fitting of the data.     

Approximate and exact equations for peak capacity in isocratic high-pressure liquid chromatography

In this letter, we examine an equation that had been published in Analytical Chemistry in a paper entitled "Comprehensive Study on the Optimization of Online Two-Dimensional Liquid Chromatographic Systems Considering Losses in Theoretical Peak Capacity in First- and Second-Dimensions: A Pareto-Optimality Approach" by Vivo-Truyols, G.; van der Wal, Sj.; Schoenmakers, P. J. Anal. Chem. 2010, 82, 8525-8536. In that paper, the authors considered, among many issues, the effects of extra-column and column broadening on isocratic peak capacity. They developed an equation to cover all possible conditions and offered a derivation based on two Taylor-series expansions and a regression. We have found an exact equation that covers all conditions and have compared the results using our equation to the results using their approximation in predicting ratios of peak widths. Their approximation works well, as we show, but we wish to offer the exact equation which is simpler in form than the approximate solution.     

Background correction and multivariate curve resolution of online liquid chromatography with infrared spectrometric detection

The use of multivariate curve resolution-alternating least-squares (MCR-ALS) in liquid chromatography-infrared detection (LC-IR) is troublesome due to the intense background absorption changes during gradient elution. Its use has been facilitated by previous removal of a significant part of the solvent background IR contributions due to common mobile phase systems employed during reversed phase gradient applications. Two straightforward background correction approaches based on simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) and principal component analysis (PCA) are proposed and evaluated on reversed phase gradient LC-IR data sets obtained during the analysis of carbohydrate and nitrophenol mixtures. After subtraction of the calculated background signal, MCR-ALS provided improved signal-to-noise ratios, removed remaining mobile phase and background signal contributions, and resolved overlapping chromatographic peaks. The present approach tends to enable easy-to-use background correction to facilitate the use of MCR-ALS in online LC-IR, even in challenging situations when gradient conditions are employed and only poor chromatographic resolution is achieved. It, therefore, shows great potential to facilitate the full exploitation of the advantages of simultaneous quantification and identification of a vast amount of analytes employing online IR detection, making new exciting applications more accessible.     

Improving peak capacity in fast online comprehensive two-dimensional liquid chromatography with post-first-dimension flow splitting

The use of flow splitters between the two dimensions in online comprehensive two-dimensional (2D) liquid chromatography (LC × LC) has not received very much attention, in comparison with their use in 2D gas chromatography (GC × GC), where they are quite common. In principle, splitting the flow after the first dimension column and performing online LC × LC on this constant fraction of the first dimension effluent should allow the two dimensions to be optimized almost independently. When there is no flow splitting, any change in the first-dimension flow rate has an immediate impact on the second dimension. With a flow splitter, one could, for example, double the flow rate into the first dimension column and perform a 1:1 flow split without changing the sample loop size or the sampler's collection time. Of course, the sensitivity would be diminished, but this can be partially compensated through the use of a larger injection; this will likely only amount to a small price to pay for this increased resolving power and system flexibility. Among other benefits, we found a 2-fold increase in the corrected 2D peak capacity and the number of observed peaks for a 15-min analysis time, using a post-first-dimension flow splitter. At a fixed analysis time, this improvement results primarily from an increase in the gradient time, resulting from the reduced system re-equilibration time, and, to a smaller extent, it is due to the increased peak capacity achieved by full optimization of the first dimension.     

Possibilities of multivariate curve resolution and partial least squares in the resolution of coeluted peaks in liquid chromatography with electrochemical detection

Two different strategies are compared for the resolution of coeluted peaks in liquid chromatography with electrochemical detection. The first is voltammetric detection (VD) for the acquisition of currents as a function of potential and time with multivariate curve resolution by alternating least squares (MCR-ALS) for data analysis and quantification. The second is amperometric detection (AD), i.e. recording currents as a function of time for a fixed potential and calibration by partial least squares (PLS). Both approaches are used to analyse a model mixture of pyrocatechol, dopamine and epinephrine. The results show that for high analyte concentrations VD-MCR-ALS provides accurate quantification with minimal effort (a single injection of the sample and each standard). However, at lower concentrations the excessive proportion of noise and the predominance of the capacitive contribution decrease the performance of VD-MCR-ALS, thus making AD-PLS preferable as its greater accuracy counters the more time-consuming calibration, which involves the injection of a large number of mixtures of different composition.     

Effect of thermal desorption kinetics on vapor injection peak irregularities by a microscale gas chromatography preconcentrator

Microscale gas chromatography (μGC) is an emerging analytical technique for in situ analysis and on-site monitoring of volatile organic compounds (VOCs) in moderately complex mixtures. One of the critical subcomponents in a μGC system is a microfabricated preconcentrator (μ-preconcentrator), which enables detection of compounds existing in indoor/ambient air at low (～sub ppb) concentrations by enhancing their signals. The prevailing notion is that elution peak broadening and tailing phenomena resulting from undesirable conditions of a microfabricated separation column (μ-column) are the primary sources of poor chromatographic resolution. However, previous experimental results indicate that the resolution degradation still remains observed for a μ-column integrated with other μGC subcomponents even after setting optimal separation conditions. In this work, we obtain the evidence that the unoptimized μ-preconcentrator vapor release/injection performance significantly contributes to decrease the fidelity of μGC analysis using our state-of-the-art passive preconcentrator microdevice. The vapor release/injection performance is highly affected by the kinetics of the thermal desorption of compounds trapped in the microdevice. Decreasing the heating rate by 20% from the optimal rate of 90 °Cs(-1) causes a 340% increase in peak tailing as well as 70% peak broadening (30% peak height reduction) to the microscale vapor injection process.     

偏最小二乘回归神经网络模型在爆破振动峰值速度预测中的应用

神经网络方法是处理非线性问题的有力工具,但当输入变量较多,输入变量间存在的多重共线性性会使得网络的建模效率下降。偏最小二乘回归方法通过提取对因变量解释性较强的成分,能较好地克服变量间的多重共线性。将两种方法相结合,建立了爆破振动峰值速度的偏最小二乘回归BP神经网络预测模型。利用偏最小二乘法对影响爆破振动的因素进行分析,提取出3个新综合变量,使BP网络的输入层节点数目由9个减少到3个,简化了网络结构,提高了计算速度,增强了网络稳定性。分析结果表明,耦合模型的平均预测误差为7.62%,相较于传统的萨氏公式及标准的BP神经网络模型其预测精度有了明显提高。     

Multi-analyte calibration curve for high-performance liquid chromatography with an inductively coupled plasma carbon emission detector

A liquid chromatography system with an inductively coupled plasma detector is used to prepare a single calibration curve that is useful for multiple analytes. The detector monitors the atomic emission from carbon at 193.09 nm. Hence, the analytes need not exhibit appreciable molar absorptivity or native fluorescence. Since the carbon signal is independent of molecular structure, the sensitivities for different compounds are similar as long as nebulization efficiencies are comparable. In fact, with a suitable internal standard, no calibration curve is necessary. The capability of the system is demonstrated with a test mixture of nine amino acids separated with a C30 reversed-phase column and a 20 mM phosphate buffered mobile phase. The system provides a detection limit of 30 ng carbon. A multi-analyte calibration curve is prepared with 135 distinct measurements: each of nine analytes, at five different concentrations, repeated in triplicate. The average relative standard deviation for 27 measurements of different amino acids at a given concentration is 2.5%. Clearly, a single analyte will suffice for the calibration of all nine test compounds. Similarly, the internal standard method provides an average percent error of 2.0% for the determination of 45 different amino acid concentrations using only a single replicate for each sample.     

Application of multivariate curve resolution for analysis of FT-IR microspectroscopic images of in situ plant tissue

The chemometric techniques of multivariate curve resolution (MCR) are aimed at extracting the spectra and concentrations of individual components present in mixtures using a minimum set of initial assumptions. We present results from the application of alternating least squares (ALS) based MCR to the analysis of hyperspectral images of in situ biological material. The spectra of individual pure components were mathematically extracted and then identified by searching the spectra against a commercial library. No prior information about the chemical composition of the material was used in the data analysis. The spectra recovered by ALS-MCR analysis of an FT-IR microspectroscopic image of an 8-micron-cornkernel section matched very well the spectra of the corn storage protein, zein, and starch. Through the application of MCR, we were able to show the presence of a second spectrally different protein, which could not be easily seen using univariate analysis. These results demonstrate the value of multivariate curve resolution techniques for the analysis of biological tissue. The value of principal components analysis (PCA) for hyperspectral image analysis is also discussed.     

Application of raman spectroscopy and sequential injection analysis for pH measurements with water dispersion of polyaniline nanoparticles

A novel method for pH measurements between pH 7.5 and 10.4 is reported in this paper. The method combines Raman spectroscopy and the automated sequential injection analysis system (SIA) and makes use of the acid-base properties of a commercially available water dispersion of polyaniline (PANI) nanoparticles with a mean particle size of 46 nm. The useful pH range of the PANI nanoparticles is broader than for conventional acid-base indicators, due to the 1:2 reaction stoichiometry of the proton-ligand complex of the nanoparticles. The pH measurements were conducted with the 633-nm laser excitation wavelength by calculating the difference between the Raman intensities of the primary and reference wavenumbers. In this study, the pH-sensitive CH=CH stretching band at 1422 cm-1 and C-H in-plane bending band of the quinoid form at 1163 cm-1 were chosen as the primary wavenumbers. The presented method is fast and allows pH to be measured with a precision of 0.2 pH unit. The advantage of the proposed method is that the hysteresis effect, which is usually observed for PANI films, can be overcome with the PANI nanoparticles, because a fresh nanoparticle solution is used in each measurement. It should be pointed out, that this work is a fundamental study showing the applicability of Raman spectroscopy in combination with the SIA technique for pH measurements in specific applications, where the conventional glass pH electrode cannot be used.     

Dispersion of chitosan on perlite for enhancement of copper(II) adsorption capacity

Chitosan coated perlite beads were prepared by drop-wise addition of slurry, made of chitosan dissolved in oxalic acid and perlite, to an alkaline bath (0.7 M NaOH). The beads that contained 32% chitosan enhanced the accessibility of OH and amine groups present in chitosan for adsorption of copper ions. The experiments using Cu(II) ions were carried out in the concentration range of 50-4100 mg/L (0.78-64.1 mmol/L). Adsorption capacity for Cu(II) was pH dependent and a maximum uptake of 104 mg/g of beads (325 mg/g of chitosan) was obtained at pH 4.5 when its equilibrium concentration in the solution was 812.5 mg/L at 298 K. The XPS and TEM data suggested that copper was mainly adsorbed as Cu(II) and was attached to amine groups. The adsorption data could be fitted to one-site Langmuir adsorption model. Anions in the solution had minimal effect on Cu(II) adsorption by chitosan coated perlite beads. EDTA was used effectively for the regeneration of the bed. The diffusion coefficient of Cu(II) onto chitosan coated beads was calculated from the breakthrough curve and was found to be 2.02 x 10(-8) cm(2)/s.     

High-throughput sequential injection method for simultaneous determination of plutonium and neptunium in environmental solids using macroporous anion-exchange chromatography, followed by inductively coupled plasma mass spectrometric detection

This paper reports an automated analytical method for rapid and simultaneous determination of plutonium and neptunium in soil, sediment, and seaweed, with detection via inductively coupled plasma mass spectrometry (ICP-MS). A chromatographic column packed with a macroporous anion exchanger (AG MP-1 M) was incorporated in a sequential injection (SI) system for the efficient retrieval of plutonium, along with neptunium, from matrix elements and potential interfering nuclides. The sorption and elution behavior of plutonium and neptunium onto AG MP-1 M resin was compared with a commonly utilized AG 1-gel-type anion exchanger. Experimental results reveal that the pore structure of the anion exchanger plays a pivotal role in ensuring similar separation behavior of plutonium and neptunium along the separation protocol. It is proven that plutonium-242 ((242)Pu) performs well as a tracer for monitoring the chemical yield of neptunium when using AG MP-1 M resin, whereby the difficulties in obtaining a reliable and practicable isotopic neptunium tracer are overcome. An important asset of the SI setup is the feasibility of processing up to 100 g of solid substrates using a small-sized (ca. 2 mL) column with chemical yields of neptunium and plutonium being ≥79%. Analytical results of three certified/standard reference materials and two solid samples from intercomparison exercises are in good agreement with the reference values at the 0.05 significance level. The overall on-column separation can be completed within 3.5 h for 10 g of soil samples. Most importantly, the anion-exchange mini-column suffices to be reused up to 10-fold with satisfactory chemical yields (>70%), as demanded in environmental monitoring and emergency scenarios, making the proposed automated assembly well-suited for unattended and high-throughput analysis.     

Unfolded partial least-squares with residual quadrilinearization: A new multivariate algorithm for processing five-way data achieving the second-order advantage. Application to fourth-order excitation-emission-kinetic-pH fluorescence analytical data

Unfolded partial least-squares in combination with residual quadrilinearization (U-PLS/RQL), is developed as a new latent structured algorithm for the processing of fourth-order instrumental data. In order to check its analytical predictive ability, fluorescence excitation-emission-kinetic-pH data were measured and processed. The concentration of the fluorescent pesticide carbaryl was determined in the presence of the pesticides fuberidazole and thiabendazole as uncalibrated interferents, in the first example of fourth-order multivariate calibration. The hydrolysis of the analyte was followed at different pH values using a fast-scanning spectrofluorimeter, recording the excitation-emission fluorescence matrices during its evolution to produce 1-naphthol, which does also emit fluorescence. A set of test samples containing the above mentioned fluorescent contaminants was analyzed with the new model, comparing the results with those from parallel factor analysis (PARAFAC). The newly developed U-PLS/RQL model provides better figures of merit for analyte quantitation (average prediction error, 7 μg L⁻¹, relative prediction error, 5%, calibration range, 50-250 μg L⁻¹), and is considerably simpler than PARAFAC in its implementation. The latter, however, furnishes important physicochemical information regarding the chemical process under study, although this requires the data to be unfolded into an array of lower dimensions, due to the lack of quadrilinearity of the experimental data.     

Assessing the dynamic range and peak capacity of nanoflow LC-FAIMS-MS on an ion trap mass spectrometer for proteomics

Proteomics experiments on complex mixtures have benefited greatly from the advent of fast-scanning ion trap mass spectrometers. However, the complexity and dynamic range of mixtures analyzed using shotgun proteomics is still beyond what can be sampled by data-dependent acquisition. Furthermore, the total liquid chromatography-mass spectrometry (LC-MS) peak capacity is not sufficient to resolve the precursors within these mixtures, let alone acquire tandem mass spectra on all of them. Here we describe the application of a high-field asymmetric waveform ion mobility spectrometry (FAIMS) device as an interface to an ion trap mass spectrometer. The dynamic range and peak capacity of the nanoflow LC-FAIMS-MS analysis was assessed using a complex tryptic digest of S. cerevisiae proteins. By adding this relatively simple device to the front of the mass spectrometer, we obtain an increase in peak capacity >8-fold and an increase in dynamic range of >5-fold, without increasing the length of the LC-MS analysis. Thus, the addition of FAIMS to the front of a table-top mass spectrometer can obtain the peak capacity of multidimensional protein identification technology (MudPIT) while increasing the throughput by a factor of 12.     

Coupling thin-layer chromatography with vibrational cooling matrix-assisted laser desorption/ionization Fourier transform mass spectrometry for the analysis of ganglioside mixtures

Thin-layer chromatography (TLC), which is widely used for separation of glycolipids, oligosaccharides, lipids, and compounds of environmental and pharmaceutical interest, can be readily coupled to matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometers, but this arrangement usually compromises mass spectral resolution due to the irregularity of the TLC surface. However, TLC can be coupled to an external ion source MALDI-Fourier transform (FT) MS instrument without compromising mass accuracy and resolution of the spectra. Furthermore, when the FTMS has a vibrationally cooled MALDI ion source, fragile glycolipids can be desorbed from TLC plates without fragmentation, even to the point that desorption of intact molecules from "hot"matrixes such as alpha-cyano-4-hydroxycinnamic acid is possible. In this work, whole brain gangliosides are separated using TLC; the TLC plates are attached directly to the MALDI target, where the gangliosides are desorbed, ionized, and detected in the FTMS with >70 000 resolving power.     

On-line concentration of neutral analytes for micellar electrokinetic chromatography. 5. Field-enhanced sample injection with reverse migrating micelles

Elementary conditions for the on-line concentration of neutral analytes by field-enhanced sample injection with reverse migrating micelles for micellar electrokinetic chromatography is presented. Acidic phosphate buffers containing micelles of sodium dodecyl sulfate are utilized as both sample solvent and separation solution. After the capillary is conditioned with a separation solution, a water plug is hydrodynamically injected to achieve field enhancement at the injection end of the capillary during injection by application of voltage. A model is provided to give insight into the stacking scheme. Significant detector response improvements are confirmed experimentally. Moreover, utility of the technique for the analysis of a real sample is tested using urine spiked with testosterone and progesterone.     

MCR-NAS: A combined hard-soft multivariate curve resolution method based on net analyte signal concept for modeling kinetic data with inert interference and baseline drift

This paper demonstrates a novel implementation of a net analyte signal (NAS) algorithm for resolving kinetic model. The evaluation of spectroscopic kinetics data by the established hard-modeling approach assumes that all the variation related to the response is linked to the species involved in the kinetic process. If effects are present in the data that cannot be explained by the model, such as baseline drift or inert interference, the estimated rate constant might be incorrect. An iterative net analyte signal procedure is shown to yield good rate constant estimates when the spectroscopic data is influenced by additional sources of variance. Simulated and real examples are used to confirm this statement.