Celio Pasquini

Laser Induced Breakdown Spectroscopy

This review describes the fundamentals, instrumentation, applications and future trends of an analytical technique that is in its early stages of consolidation and is establishing its definitive niches among modern spectrometric techniques. The technique has been named Laser Induced Breakdown Spectroscopy (LIBS) and its main characteristic stands in the use of short laser pulses as the energy source to vaporize samples and excite the emission of electromagnetic radiation from its elements and/or molecular fragments. The emitted radiation is analyzed by high resolution optics and the intensities are recorded, usually by fast triggered solid state detectors. Together, these devices allow producing and registering a wide ranging emission spectrum of the short-lived phenomenon induced by the laser pulse. The spectrum contains qualitative and quantitative information which can be correlated with sample identity or can be used to determine the amount of its constituents. This review is divided in four parts. First, the relevant historical and theoretical concepts associated with LIBS are presented; then the main practical aspects of the several experimental and instrumental approaches employed for implementation of the technique are critically described; the applications related in the literature, including those making use of chemometrics, are classified and exemplified with relevant and recently published work. Finally, an attempt to portray an overall evaluation and future perspectives of the technique are presented.

Identification of counterfeit drugs using near-infrared spectroscopy

This work was aimed at the investigation of the use of near-infrared spectroscopy (NIRS) for the identification of counterfeit drugs. The identification is based on the comparison of the NIR spectrum of a sample with typical spectra of the authentic drug using multivariate modelling and classification algorithms (PCA/SIMCA). Initially, NIRS was evaluated for spectrum acquisition of various drugs, selected in order to observe the diversity of physico-chemical characteristics found among commercial products. The parameters which could affect the spectra of a given drug (especially if presented in solid form) were investigated and the results showed that the first derivative can minimise spectral changes associated with tablet geometry, physical differences in their faces and position in relation to the probe beam. The power of NIRS in distinguishing among similar pharmaceuticals was demonstrated and a protocol is proposed to construct a multivariate model and to include it in a library allowing testing for drug authenticity. The methodology was evaluated with real samples of counterfeit drugs and was able to recognise all those presenting changes in composition as false. The results show unequivocally the potential of NIRS for rapid, on-site and non-destructive identification of counterfeit pharmaceuticals.

Determination of total sulfur in diesel fuel employing NIR spectroscopy and multivariate calibration

A method for sulfur determination in diesel fuel employing near infrared spectroscopy, variable selection and multivariate calibration is described. The performances of principal component regression (PCR) and partial least square (PLS) chemometric methods were compared with those shown by multiple linear regression (MLR), performed after variable selection based on the genetic algorithm (GA) or the successive projection algorithm (SPA). Ninety seven diesel samples were divided into three sets (41 for calibration, 30 for internal validation and 26 for external validation), each of them covering the full range of sulfur concentrations (from 0.07 to 0.33% w/w). Transflectance measurements were performed from 850 to 1800 nm. Although principal component analysis identified the presence of three groups, PLS, PCR and MLR provided models whose predicting capabilities were independent of the diesel type. Calibration with PLS and PCR employing all the 454 wavelengths provided root mean square errors of prediction (RMSEP) of 0.036% and 0.043% for the validation set, respectively. The use of GA and SPA for variable selection provided calibration models based on 19 and 9 wavelengths, with a RMSEP of 0.031% (PLS-GA), 0.022% (MLR-SPA) and 0.034% (MLR-GA). As the ASTM 4294 method allows a reproducibility of 0.05%, it can be concluded that a method based on NIR spectroscopy and multivariate calibration can be employed for the determination of sulfur in diesel fuels. Furthermore, the selection of variables can provide more robust calibration models and SPA provided more parsimonious models than GA.

Classification of Brazilian soils by using LIBS and variable selection in the wavelet domain

This paper proposes a novel analytical methodology for soil classification based on the use of laser-induced breakdown spectroscopy (LIBS) and chemometric techniques. In the proposed methodology, linear discriminant analysis (LDA) is employed to build a classification model on the basis of a reduced subset of spectral variables. For the purpose of variable selection, three techniques are considered, namely the successive projection algorithm (SPA), the genetic algorithm (GA), and a stepwise formulation (SW). The use of a data compression procedure in the wavelet domain is also proposed to reduce the computational workload involved in the variable selection process. The methodology is validated in a case study involving the classification of 149 Brazilian soil samples into three different orders (Argissolo, Latossolo and Nitossolo). For means of comparison, soft independent modelling of class analogy (SIMCA) models are also employed. The best discrimination of soil types was attained by SPA-LDA, which achieved an average classification rate of 90% in the validation set and 72% in cross-validation. Moreover, the proposed wavelet compression procedure was found to be of value by providing a 100-fold reduction in computational workload without significantly compromising the classification accuracy of the resulting models.

Assessment of infrared spectroscopy and multivariate techniques for monitoring the service condition of diesel-engine lubricating oils

This paper presents two methodologies for monitoring the service condition of diesel-engine lubricating oils on the basis of infrared spectra. In the first approach, oils samples are discriminated into three groups, each one associated to a given wear stage. An algorithm is proposed to select spectral variables with good discriminant power and small collinearity for the purpose of discriminant analysis classification. As a result, a classification accuracy of 93% was obtained both in the middle (MIR) and near-infrared (NIR) ranges. The second approach employs multivariate calibration methods to predict the viscosity of the lubricant. In this case, the use of absorbance measurements in the NIR spectral range was not successful, because of experimental difficulties associated to the presence of particulate matter. Such a problem was circumvented by the use of attenuated total reflectance (ATR) measurements in the MIR spectral range, in which an RMSEP of 3.8cSt and a relative average error of 3.2% were attained.

Flow-injection determination of ammonia in kjeldahl digests by gas diffusion and conductometry

Abstract A flow injection/conductometric method is proposed for determing ammonia in solutions obtained from Kjeldahl digestion. The method is based on diffusion of ammonia through a PTFE membrane from an alkaline (NaOH/EDTA) medium to a deionized water stream. The change in conductance of the deionized water stream is proportional to the ammonia concentration present in the digest. The effects of flow parameters, temperature and potential interferences are reported. Approximately 100 samples can be injected per hour; the precision is about 1%. Results for total nitrogen in vegetable tissues, animal feeds and fertilizers are in good agreement with those obtained by the usual distillation/titration method.

Simultaneous determination of methanol and ethanol in gasoline using NIR spectroscopy: effect of gasoline composition.

Near infrared (NIR) spectroscopy was employed for simultaneous determination of methanol and ethanol contents in gasoline. Spectra were collected in the range from 714 to 2500 nm and were used to construct quantitative models based on partial least squares (PLS) regression. Samples were prepared in the laboratory and the PLS regression models were developed using the spectral range from 1105 to 1682 nm, showing a root mean square error of prediction (RMSEP) of 0.28% (v/v) for ethanol for both PLS-1 and PLS-2 models and of 0.31 and 0.32% (v/v) for methanol for the PLS-1 and PLS-2 models, respectively. A RMSEP of 0.83% (v/v) was obtained for commercial samples. The effect of the gasoline composition was investigated, it being verified that some solvents, such as toluene and o-xylene, interfere in ethanol content prediction, while isooctane, o-xylene, m-xylene and p-xylene interfere in the methanol content prediction. Other spectral ranges were investigated and the range 1449-1611 nm showed the best results.

Flow-injection determination of inorganic forms of nitrogen by gas diffusion and conductimetry

Abstract A flow-injection—conductimetric method was applied to the determination of ammonia, nitrate and nitrite at concentrations down to 5, 20 and 20 ng ml −1 , respectively. Ammonia was determined by merging the injected sample with an alkaline solution (NaOHEDTA) and passing the mixture through a diffusion cell. The ammonia released was collected by a flowing stream of deionized water that passed through a conductance flow cell. Nitrate and nitrite concentrations were determined after reduction to ammonia in alkaline medium using a column filled with metallic zinc. The ammonia produced was then measured as described above. About 60 samples per hour can be processed with a relative standard deviation of about 1%. Satisfactory agreement was observed between results for ammonia in samples of natural water and nitrate in tap and mineral water determined by the proposed method and by standard spectrophotometric procedures. Speciation can be achieved by adding sulphanilic acid to remove nitrite from the sample and determining the ammonia without the use of the column.

Short-term toxicity test using Escherichia coli: Monitoring CO2 production by flow injection analysis

Abstract Short-term toxicity tests using Escherichia coli were carried out for different stressing agents such as metal ions [Cd(II), Cu(II) and Hg(II)], sediments and one type of antibiotic (Bactrin). Inhibition of the microbial respiration was monitored using flow injection analysis (FIA) with a conductometric detector. Inhibition in the respiration of E. coli suspensions were detected within 20 min for Hg(II) ions and the antibiotic, whereas sediment samples from eutrophic water bodies stimulated CO 2 production.

Cold Vapor Atomic Absorption determination of mercury by Flow Injection Analysis using a Teflon membrane phase separator coupled to the absorption cell

Abstract A Flow Injection Analysis (FIA) procedure for the determination of trace amounts of mercury by the Cold Vapor Atomic Absorption (CVAA) method is presented. In order to make efficient use of the FIA technique, a new flow cell was developed to permit a rapid separation of elemental mercury from the carrier solution. The design of this device is based on the permeability of Hg 0 in commercially available Teflon (PTFE) tape, which acts as a membrane phase separator. The calibration curve is linear up to 70 ng.ml −1 ( A = 0.005 + 0.008 Hg(ng.ml −1 ); r = 0.9996) using a 15-cm open cell approach, with a detection limit of 1.4 ng. ml −1 (0.66 ng of mercury), considering a signal to noise ratio of three. The standard deviation is s = ±0.004 absorbance units, calculated at a level of 50 ng.ml −1 of Hg 2+ . The sampling rate was 110 samples per h.