Wine classification by taste sensors made from ultra-thin films and using neural networks

This paper reports on a sensor array able to distinguish tastes and used to classify red wines. The array comprises sensing units made from Langmuir-Blodgett (LB) films of conducting polymers and lipids and layer-by-layer (LBL) films from chitosan deposited onto gold interdigitated electrodes. Using impedance spectroscopy as the principle of detection, we show that distinct clusters can be identified in principal component analysis (PCA) plots for six types of red wine. Distinction can be made with regard to vintage, vineyard and brands of the red wine. Furthermore, if the data are treated with artificial neural networks (ANNs), this artificial tongue can identify wine samples stored under different conditions. This is illustrated by considering 900 wine samples, obtained with 30 measurements for each of the five bottles of the six wines, which could be recognised with 100% accuracy using the algorithms Standard Backpropagation and Backpropagation momentum in the ANNs. (C) 2003 Elsevier B.V. All rights reserved.

A layer-by-layer film of chitosan in a taste sensor application

Chitosan is alternated with sulfonated polystyrene (PSS) to build layer-by-layer (LBL) films that are used as sensing units in an electronic tongue. Using impedance spectroscopy as the principle method of detection, an array using chitosan/PSS LBL film and a bare gold electrode as the sensing units was capable of distinguishing the basic tastes - salty, sweet, bitter, and sour - to a concentration below the human threshold. The suitability of chitosan as a sensing material was confirmed by using this sensor to distinguish red wines according to their vintage, vineyard, and brands.

Taking Advantage of Electrostatic Interactions To Grow Langmuir-Blodgett Films Containing Multilayers of the Phospholipid Dipalmitoylphosphatidylglycerol

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Coupling Surface-Enhanced Resonance Raman Scattering and Electronic Tongue as Characterization Tools to Investigate Biological Membrane Mimetic Systems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Natural Polysaccharides as Active Biomaterials in Nanostructured Films for Sensing

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Analysis of the Al-PANI interfaces by complex impedance spectroscopy

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Sensor array made with nanostructured films to detect a phenothiazine compound

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Projections Onto Convex Sets through Particle Swarm Optimization and its application for remote sensing image restoration

Image restoration attempts to enhance images corrupted by noise and blurring effects. Iterative approaches can better control the restoration algorithm in order to find a compromise of restoring high details in smoothed regions without increasing the noise. Techniques based on Projections Onto Convex Sets (POCS) have been extensively used in the context of image restoration by projecting the solution onto hyperspaces until some convergence criteria be reached. It is expected that an enhanced image can be obtained at the final of an unknown number of projections. The number of convex sets and its combinations allow designing several image restoration algorithms based on POCS. Here, we address two convex sets: Row-Action Projections (RAP) and Limited Amplitude (LA). Although RAP and LA have already been used in image restoration domain, the former has a relaxation parameter (A) that strongly depends on the characteristics of the image that will be restored, i.e., wrong values of A can lead to poorly restoration results. In this paper, we proposed a hybrid Particle Swarm Optimization (PS0)-POCS image restoration algorithm, in which the A value is obtained by PSO to be further used to restore images by POCS approach. Results showed that the proposed PSO-based restoration algorithm outperformed the widely used Wiener and Richardson-Lucy image restoration algorithms. (C) 2010 Elsevier B.V. All rights reserved.

Impedance of carrier injection at the metal-organic interface mediated by surface states in electron-only tris(8-hydroxyquinoline) aluminium (Alq(3)) thin layers

Capacitance spectra of thin (< 200 nm) Alq(3) electron-only devices have been measured as a function of bias voltage. Capacitance spectra exhibit a flat response at high frequencies (> 10(3) Hz) and no feature related to the carrier transit time is observed. Toward low frequencies the spectra reach a maximum and develop a negative excess capacitance. Capacitance response along with current-voltage (J-V) characteristics are interpreted in terms of the injection of electrons mediated by surface states at the metal organic interface. A detailed model for the impedance of the injection process is provided that highlights the role of the filling/releasing kinetics of energetically distributed interface states. This approach connects the whole capacitance spectra to the occupancy of interface states, with no additional information about bulk trap levels. Simulations based on the model allow to derive the density of interface states effectively intervening in the carrier injection (similar to 1.5 x 10(12) cm (2)). (C) 2008 Elsevier B.V. All rights reserved.

Time-domain analysis of piezoelectric impedance-based structural health monitoring using multilevel wavelet decomposition

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sizing PZT Transducers in Impedance-Based Structural Health Monitoring

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Optimal Frequency Range Selection for PZT Transducers in Impedance-Based SHM Systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Real-time multi-sensors measurement system with temperature effects compensation for impedance-based structural health monitoring

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Structural FRF acquisition via electric impedance measurement applied to damage location

Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

Dielectric and impedance properties of Nd3/2Bi3/2Fe5O12 ceramics

The polycrystalline sample of Nd3/2Bi3/2Fe5O12 was prepared by a high- temperature solid-state reaction technique. Preliminary X-ray structural analysis exhibits the formation of a single-phase tetragonal structure at room temperature. Microstructural analysis by scanning electron microscopy shows that the sintered sample has well defined grains. These grains are distributed uniformly throughout the surface of the sample. Detailed studies of dielectric response at various frequencies and temperatures exhibit a dielectric anomaly at 400 A degrees C. The electrical properties (impedance, modulus and conductivity) of the material were studied using a complex impedance spectroscopy technique. These studies reveal a significant contribution of grain and grain boundary effects in the material. The frequency dependent plots of modulus and the impedance loss show that the conductivity relaxation is of non-Debye type. Studies of electrical conductivity with temperature demonstrate that the compound exhibits Arrhenius-type of electrical conductivity. Study of ac conductivity with frequency suggests that the material obeys Jonscher's universal power law.