Ivo M. Raimundo

Construction and evaluation of an optical pH sensor based on polyaniline-porous Vycor glass nanocomposite

This work describes the preparation of a polyaniline (Pani)‐porous Vycor glass (PVG) nanocomposite and its use as sensing phase in an optical fibre pH sensor. Nanocomposites of Pani‐PVG were prepared by in situ polymerisation of aniline absorbed inside the pores of a PVG (Corning 7930) with an average porous size of 8 nm. The optical sensor was constructed by fixing a PVG slide onto a distal end of bifurcated optical fibre bundle, with a cyanoacrylic resin. The sensor response was found to be reversible in the pH range from 5 to 12 and linear from pH 7.4 to 9.5. Response times of 4, 8 and >16 min were obtained for slide thickness’ of 0.5, 1 and 1.5 mm, respectively. Changes of temperature, ranging from 20 to 408C, showed minor effect on the dynamic range. Similarly, the ionic strength (0.15, 0.30 and 0.50 mol l ˇ1 ) and the nature of the ions (NaCl, KCl and NaClO4) showed minor influence on the sensor response. Leaching of Pani was not observed and the sensor lifetime was determined as being at least 5 months. These results indicate that a Pani‐PVG nanocomposite is suitable for the construction of optical pH sensors, with good analytical performance, since the glass slides can be prepared with good reproducibility and durability. # 2001 Elsevier Science B.V. All rights reserved.

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.

Direct Solid-Phase Optical Measurements in Flow Systems: A Review

Measurements based on absorption, reflectance, or luminescence of molecular species or complex ions can be carried out directly on a solid support simultaneously to the retention of the analyte. The use of this strategy in flow-based systems is advantageous in view of the reproducible handling of solutions in retention and elution steps of the analyte. This approach can be exploited to increase sensitivity, minimize reagent consumption as well as waste generation, improve selectivity or for simultaneous determination based on selective retention or differences in sorption rates of the analytes. This review focuses on the main characteristics of direct solid-phase measurements in flow systems, including the discussion of advantages and limitations and practical guidelines to the successful implementation of this approach. Selected applications in diverse fields, such as pharmaceutical, food, and environmental analysis are discussed.

Classification of Brazilian Coffee Using Near-Infrared Spectroscopy and Multivariate Calibration

This work describes the use of near infrared spectroscopy (NIRS) and chemometric techniques calibration for the classification of coffee samples from different lots and producers acquired in supermarkets and roasting industries in some Brazilian cities. Seventy-three samples of finely ground roasted coffee were acquired in the market and 91 samples of roasted ground Arabica beans were analyzed in the full NIR spectral range (800–2500 nm) using a diffuse reflectance accessory coupled to an MB160 Bomem spectrophotometer. Two classification models were constructed: Soft Independent Modeling Class Analogy (SIMCA) and PLS Discriminant Analysis (PLS-DA). All findings reveal that NIR spectroscopy, coupled with either SIMCA or PLS-DA multivariate models, can be a useful tool to differentiate roasted coffee grains and to replace sensory tests.