Evaluation of laser induced breakdown spectroscopy for cadmium determination in soils

Cadmium is known to be a toxic agent that accumulates in the living organisms and present high toxicity potential over lifetime. Efforts towards the development of methods for microanalysis of environmental samples, including the determination of this element by graphite furnace atomic absorption spectrometry (GFAAS). inductively coupled plasma optical emission spectrometry (ICP OES), and inductively coupled plasma-mass spectrometry (ICP-MS) techniques, have been increasing. Laser induced breakdown spectroscopy (UBS) is an emerging technique dedicated to microanalysis and there is a lack of information dealing with the determination of cadmium. The aim of this work is to demonstrate the feasibility of LIBS for cadmium detection in soils. The experimental setup was designed using a laser Q-switched (Nd:YAG, 10 Hz, lambda = 1064 nm) and the emission signals were collimated by lenses into an optical fiber Coupled to a high-resolution intensified charge-coupled device (ICCD)-echelle spectrometer. Samples were cryogenically ground and thereafter pelletized before LIBS analysis. Best results were achieved by exploring a test portion (i.e. sampling spots) with larger surface area, which contributes to diminish the uncertainty due to element specific microheterogeneity. Calibration curves for cadmium determination were achieved using certified reference materials. The metrological figures of merit indicate that LIBS can be recommended for screening of cadmium contamination in soils. (C) 2009 Elsevier B.V. All rights reserved.

Simultaneous optimization by neuro-genetic approach for analysis of plant materials by laser induced breakdown spectroscopy

A simultaneous optimization strategy based on a neuro-genetic approach is proposed for selection of laser induced breakdown spectroscopy operational conditions for the simultaneous determination of macronutrients (Ca, Mg and P), micro-nutrients (B, Cu, Fe, Mn and Zn), Al and Si in plant samples. A laser induced breakdown spectroscopy system equipped with a 10 Hz Q-switched Nd:YAG laser (12 ns, 532 nm, 140 mJ) and an Echelle spectrometer with intensified coupled-charge device was used. Integration time gate, delay time, amplification gain and number of pulses were optimized. Pellets of spinach leaves (NIST 1570a) were employed as laboratory samples. In order to find a model that could correlate laser induced breakdown spectroscopy operational conditions with compromised high peak areas of all elements simultaneously, a Bayesian Regularized Artificial Neural Network approach was employed. Subsequently, a genetic algorithm was applied to find optimal conditions for the neural network model, in an approach called neuro-genetic, A single laser induced breakdown spectroscopy working condition that maximizes peak areas of all elements simultaneously, was obtained with the following optimized parameters: 9.0 mu s integration time gate, 1.1 mu s delay time, 225 (a.u.) amplification gain and 30 accumulated laser pulses. The proposed approach is a useful and a suitable tool for the optimization process of such a complex analytical problem. (C) 2009 Elsevier B.V. All rights reserved.

Evaluation of laser induced breakdown spectroscopy for the determination of micronutrients in plant materials

Laser induced breakdown spectroscopy (LIBS) has been evaluated for the determination of micronutrients (B, Cu, Fe, Mn and Zn) in pellets of plant materials, using NIST, BCR and GBW biological certified reference materials for analytical calibration. Pellets of approximately 2 mm thick and 15 mm diameter were prepared by transferring 0.5 g of powdered material to a 15 mm die set and applying 8.0 tons cm(-2). An experimental setup was designed by using a Nd:YAG laser operating at 1064 nm (200 mJ per pulse, 10 Hz) and an Echelle spectrometer with ICCD detector. Repeatability precision varied from 4 to 30% from measurements obtained in 10 different positions (8 laser shots per test portion) in the same sample pellet. Limits of detection were appropriate for routine analysis of plant materials and were 2.2 mg kg(-1) B, 3.0 mg kg(-1) Cu, 3.6 mg kg(-1) Fe, 1.8 mg kg(-1) Mn and 1.2 mg kg(-1) Zn. Analysis of different plant samples were carried out by LIBS and results were compared with those obtained by ICP OES after wet acid decomposition. (C) 2009 Elsevier B.V. All rights reserved.

Evaluation of laser induced breakdown spectroscopy for the determination of macronutrients in plant materials

Laser induced breakdown spectroscopy (LIBS) has become an analytical tool for the direct analysis of a large variety of materials in order to provide qualitative and/or quantitative information. However, there is a lack of information for LIBS analysis of agricultural and environmental samples. In this work a LIBS system has been evaluated for the determination of macronutrients (P, K, Ca, Mg) in pellets of vegetal reference materials. An experimental setup was designed by using a Nd:YAG laser operating at 1064 nm and an Echelle spectrometer with ICCD detector. The plasma temperature was estimated by Boltzmann plots and instrumental paragmeters such as delay time, lens-to-sample distance and pulse energy were evaluated. Certified reference materials as well as reference materials were used for analytical calibrations of P, K, Ca, and Mg. Most results of the direct analysis of plant samples by LIBS were in reasonable agreement with those obtained by ICP OES after wet acid decomposition. (C) 2008 Elsevier B.V. All rights reserved.

Laser-induced breakdown spectroscopy and chemometrics for classification of toys relying on toxic elements

Quality control of toys for avoiding children exposure to potentially toxic elements is of utmost relevance and it is a common requirement in national and/or international norms for health and safety reasons. Laser-induced breakdown spectroscopy (LIBS) was recently evaluated at authors` laboratory for direct analysis of plastic toys and one of the main difficulties for the determination of Cd. Cr and Pb was the variety of mixtures and types of polymers. As most norms rely on migration (lixiviation) protocols, chemometric classification models from LIBS spectra were tested for sampling toys that present potential risk of Cd, Cr and Pb contamination. The classification models were generated from the emission spectra of 51 polymeric toys and by using Partial Least Squares - Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA) and K-Nearest Neighbor (KNN). The classification models and validations were carried out with 40 and 11 test samples, respectively. Best results were obtained when KNN was used, with corrected predictions varying from 95% for Cd to 100% for Cr and Pb. (C) 2011 Elsevier B.V. All rights reserved.

Estimation of hexenuronic acids and kappa number in kraft pulps of Eucalyptus globulus by Fourier transform near infrared spectroscopy and multivariate analysis

Fourier transform near infrared (FT-NIR) spectroscopy was evaluated as an analytical too[ for monitoring residual Lignin, kappa number and hexenuronic acids (HexA) content in kraft pulps of Eucalyptus globulus. Sets of pulp samples were prepared under different cooking conditions to obtain a wide range of compound concentrations that were characterised by conventional wet chemistry analytical methods. The sample group was also analysed using FT-NIR spectroscopy in order to establish prediction models for the pulp characteristics. Several models were applied to correlate chemical composition in samples with the NIR spectral data by means of PCR or PLS algorithms. Calibration curves were built by using all the spectral data or selected regions. Best calibration models for the quantification of lignin, kappa and HexA were proposed presenting R-2 values of 0.99. Calibration models were used to predict pulp titers of 20 external samples in a validation set. The lignin concentration and kappa number in the range of 1.4-18% and 8-62, respectively, were predicted fairly accurately (standard error of prediction, SEP 1.1% for lignin and 2.9 for kappa). The HexA concentration (range of 5-71 mmol kg(-1) pulp) was more difficult to predict and the SEP was 7.0 mmol kg(-1) pulp in a model of HexA quantified by an ultraviolet (UV) technique and 6.1 mmol kg(-1) pulp in a model of HexA quantified by anion-exchange chromatography (AEC). Even in wet chemical procedures used for HexA determination, there is no good agreement between methods as demonstrated by the UV and AEC methods described in the present work. NIR spectroscopy did provide a rapid estimate of HexA content in kraft pulps prepared in routine cooking experiments.

Further improvements on impedance-based fault location for power distribution systems

In this study, further improvements regarding the fault location problem for power distribution systems are presented. The proposed improvements relate to the capacitive effect consideration on impedance-based fault location methods, by considering an exact line segment model for the distribution line. The proposed developments, which consist of a new formulation for the fault location problem and a new algorithm that considers the line shunt admittance matrix, are presented. The proposed equations are developed for any fault type and result in one single equation for all ground fault types, and another equation for line-to-line faults. Results obtained with the proposed improvements are presented. Also, in order to compare the improvements performance and demonstrate how the line shunt admittance affects the state-of-the-art impedance-based fault location methodologies for distribution systems, the results obtained with two other existing methods are presented. Comparative results show that, in overhead distribution systems with laterals and intermediate loads, the line shunt admittance can significantly affect the state-of-the-art methodologies response, whereas in this case the proposed developments present great improvements by considering this effect.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

Void fraction measurement and signal analysis from multiple-electrode impedance sensors

Void fraction sensors are important instruments not only for monitoring two-phase flow, but for furnishing an important parameter for obtaining flow map pattern and two-phase flow heat transfer coefficient as well. This work presents the experimental results obtained with the analysis of two axially spaced multiple-electrode impedance sensors tested in an upward air-water two-phase flow in a vertical tube for void fraction measurements. An electronic circuit was developed for signal generation and post-treatment of each sensor signal. By phase shifting the electrodes supplying the signal, it was possible to establish a rotating electric field sweeping across the test section. The fundamental principle of using a multiple-electrode configuration is based on reducing signal sensitivity to the non-uniform cross-section void fraction distribution problem. Static calibration curves were obtained for both sensors, and dynamic signal analyses for bubbly, slug, and turbulent churn flows were carried out. Flow parameters such as Taylor bubble velocity and length were obtained by using cross-correlation techniques. As an application of the void fraction tested, vertical flow pattern identification could be established by using the probability density function technique for void fractions ranging from 0% to nearly 70%.

Recycling Krylov subspaces for efficient large-scale electrical impedance tomography

Electrical impedance tomography (EIT) captures images of internal features of a body. Electrodes are attached to the boundary of the body, low intensity alternating currents are applied, and the resulting electric potentials are measured. Then, based on the measurements, an estimation algorithm obtains the three-dimensional internal admittivity distribution that corresponds to the image. One of the main goals of medical EIT is to achieve high resolution and an accurate result at low computational cost. However, when the finite element method (FEM) is employed and the corresponding mesh is refined to increase resolution and accuracy, the computational cost increases substantially, especially in the estimation of absolute admittivity distributions. Therefore, we consider in this work a fast iterative solver for the forward problem, which was previously reported in the context of structural optimization. We propose several improvements to this solver to increase its performance in the EIT context. The solver is based on the recycling of approximate invariant subspaces, and it is applied to reduce the EIT computation time for a constant and high resolution finite element mesh. In addition, we consider a powerful preconditioner and provide a detailed pseudocode for the improved iterative solver. The numerical results show the effectiveness of our approach: the proposed algorithm is faster than the preconditioned conjugate gradient (CG) algorithm. The results also show that even on a standard PC without parallelization, a high mesh resolution (more than 150,000 degrees of freedom) can be used for image estimation at a relatively low computational cost. (C) 2010 Elsevier B.V. All rights reserved.

Evidences of the evolution from solid solution to surface segregation in Ni-doped SnO(2) nanoparticles using Raman spectroscopy

Ni-doped SnO(2) nanoparticles, promising for gas-sensing applications, have been synthesized by a polymer precursor method. X-ray diffraction (XRD) and transmission electron microscopy (TEM) data analyses indicate the exclusive formation of nanosized particles with rutile-type phase (tetragonal SnO(2)) for Ni contents below 10 mol%. The mean crystallite size shows a progressive reduction with the Ni content. Room-temperature Raman spectra of Ni-doped SnO(2) nanoparticles show the presence of Raman active modes and modes activated by size effects. From the evolution of the A(1g) mode with the Ni content, a solubility limit at similar to 2 mol% was estimated. Below that content, Raman results are consistent with the occurrence of solid solution (ss) and surface segregation (seg.) of Ni ions. Above similar to 2 mol% Ni, the redshift of A(1g) mode suggests that the surface segregation of Ni ions takes place. Disorder-activated bands were determined and their integrated intensity evolution with the Ni content suggest that the solid-solution regime favors the increase of disorder; meanwhile, that disorder becomes weaker as the Ni content is increased. Copyright (C) 2010 John Wiley & Sons, Ltd.

In-Line Monitoring of Particle Size during Emulsion Polymerization under Different Operational Conditions using NIR Spectroscopy

In the present work, the sensitivity of NIR spectroscopy toward the evolution of particle size was studied during emulsion homopolymerization of styrene (Sty) and emulsion copolymerization of vinyl acetate-butyl acrylate conducted in a semibatch stirred tank and a tubular pulsed sieve plate reactor, respectively. All NIR spectra were collected online with a transflectance probe immersed into the reaction medium. The spectral range used for the NIR monitoring was from 9 500 to 13 000 cm(-1), where the absorbance of the chemical components present is minimal and the changes in the NIR spectrum can be ascribed to the effects of light scattering by the polymer particles. Off-line measurements of the average diameter of the polymer particles by DLS were used as reference values for the development of the multi-variate NIR calibration models based on partial least squares. Results indicated that, in the spectral range studied, it is possible to monitor the evolution of the average size of the polymer particles during emulsion polymerization reactions. The inclusion of an additional spectral range, from 5 701 to 6 447 cm(-1), containing information on absorbances (""chemical information"") in the calibration models was also evaluated.

Using Imaging Spectroscopy to study soil properties

Imaging Spectroscopy (IS) is a promising tool for studying soil properties in large spatial domains. Going from point to image spectrometry is not only a journey from micro to macro scales, but also a long stage where problems such as dealing with data having a low signal-to-noise level, contamination of the atmosphere, large data sets, the BRDF effect and more are often encountered. In this paper we provide an up-to-date overview of some of the case studies that have used IS technology for soil science applications. Besides a brief discussion on the advantages and disadvantages of IS for studying soils, the following cases are comprehensively discussed: soil degradation (salinity, erosion, and deposition), soil mapping and classification, soil genesis and formation, soil contamination, soil water content, and soil swelling. We review these case studies and suggest that the 15 data be provided to the end-users as real reflectance and not as raw data and with better signal-to-noise ratios than presently exist. This is because converting the raw data into reflectance is a complicated stage that requires experience, knowledge, and specific infrastructures not available to many users, whereas quantitative spectral models require good quality data. These limitations serve as a barrier that impedes potential end-users, inhibiting researchers from trying this technique for their needs. The paper ends with a general call to the soil science audience to extend the utilization of the IS technique, and it provides some ideas on how to propel this technology forward to enable its widespread adoption in order to achieve a breakthrough in the field of soil science and remote sensing. (C) 2009 Elsevier Inc. All rights reserved.

Quantitative Determination of Dimethylaminoethanol in Cosmetic Formulations by Nuclear Magnetic Resonance Spectroscopy

A nuclear magnetic resonance (NMR) spectroscopic method was validated for the quantitative determination of dimethylaminoethanol (DMAE) in cosmetic formulations. The linearity in the range from 0.5000 to 1.5000 g (DMAE salt/mass maleic acid) presents a correlation coefficient > 0.99 for all DMAE salts. The repeatability (intraday), expressed as relative standard deviation, ranged from 1.08 to 1.44% for samples and 1.31 to 1.88% for raw materials. The detection limit and quantitation limit were 0.0017 and 0.0051 g for DMAE, 0.0018 and 0.0054 g for DMAE bitartrate, and 0.0023 and 0.0071 g for DMAE acetamidobenzoate, respectively. The proposed method is simple, precise, and accurate and can be used in the quality control of raw materials and cosmetic gels containing these compounds as active substances.

Quantification of chlorpheniramine maleate enantiomers by ultraviolet spectroscopy and chemometric methods

Chlorpheniramine maleate (CLOR) enantiomers were quantified by ultraviolet spectroscopy and partial least squares regression. The CLOR enantiomers were prepared as inclusion complexes with beta-cyclodextrin and 1-butanol with mole fractions in the range from 50 to 100%. For the multivariate calibration the outliers were detected and excluded and variable selection was performed by interval partial least squares and a genetic algorithm. Figures of merit showed results for accuracy of 3.63 and 2.83% (S)-CLOR for root mean square errors of calibration and prediction, respectively. The ellipse confidence region included the point for the intercept and the slope of 1 and 0, respectively. Precision and analytical sensitivity were 0.57 and 0.50% (S)-CLOR, respectively. The sensitivity, selectivity, adjustment, and signal-to-noise ratio were also determined. The model was validated by a paired t test with the results obtained by high-performance liquid chromatography proposed by the European pharmacopoeia and circular dichroism spectroscopy. The results showed there was no significant difference between the methods at the 95% confidence level, indicating that the proposed method can be used as an alternative to standard procedures for chiral analysis.