S. Graziani

All-Organic Motion Sensors: Electromechanical Modeling

A new class of materials called ionic polymer-polymer composites has been investigated to demonstrate the sensing and acting capabilities of these all-organic structures. Samples have been realized by covering Nafion membranes, with Orgacon 3040 conducting polymer as electrode material. Membranes whose electrodes were manufactured using the drop-casting technique exhibited the best electromechanical performances. Sensors have been tested in a dedicated experimental setup to model their electromechanical transduction behavior. Thus, the obtained model has been validated.

Improving back-propagation learning using auxiliary neural networks

Multi-layered perceptrons with the back-propagation learning algorithm represent an emerging tool in non-linear systems modelling and control. One of the main drawbacks of the traditional back-propagation algorithm is its slow rate of convergence. A new method to improve the speed of the learning phase, involving the use of a suitable number of additional neural networks, is proposed. The auxiliary networks work concurrently to the principal network without slowing down the procedure. In this paper, it is shown how to choose the structure of the auxiliary networks and how these have to be trained. Several examples confirm the suitability of the proposed procedure

All organic actuation and sensing devices

In this work, all-organic structures with sensing and acting capabilities are prepared and tested. The devices have been realized by covering Nafionreg membranes with conducting polymers as electrode elements. The selection of both the materials and the deposition techniques has been addressed taking into account the chemical-physical characteristics of the membrane. Several tests have been performed in order to characterize both the morphological and electrical behavior of the obtained structures. The results show that it is possible to produce all-organic devices based on Nafionreg that have electromechanic transduction capacities. The possibility to use these devices both as sensing and acting elements has been demonstrated.

A Neural Network For Seismic Events Classification

This paper deals with the classification problem of earthquakes by using neural networks. It is shown that such devices allow to solve the problem of automatic discrimination with high degree of accuracy even if a small number of llexamplesll are used in the learning phase of the network. The criteria used to find a optimal network configuration and to carry out the training phase are discussed. In the paper some expedients to speed-up the training of the neural network are outlined.

All polymeric transducers for energy harvesting

The power harvesting properties of a new class of all polymeric ionic electroactive materials, named Ionic Polymer-Polymer composites (IP2Cs) from vibrating sources are introduced and experimentally investigated. Obtained results show that the proposed technology gives better results with respect to other ionic polymeric transducers and allow to foresee the possibility to use in the future all polymeric transducers to power post-silicon devices such as polymeric wireless sensor networks.

Multi-Layer Perceptions in Filtering Geophysical Signals

Multi-layer neural networks are used to model the influence of noise sources on some type of geophysicalsignals. The role of neural networks is to identify non-linear time invariant NARMAX models which are used to filter corrupted data using a model-based approach, avoiding the drawbacks of the classical digital filtering techniques. In this paper the goodness of the proposed approach is shown by considering a case study concerning with the filtering of tilt signals recorded in volcanic active areas.

Realization and characterization of carbon black based fractional order element

Abstract In this papers the possibility of realizing fractional capacitors by using carbon black nanostructured dielectrics is investigated. Capacitors have been realized by varying the percentage of distributed carbon black. The frequency analysis of the capacitors has been, therefore, performed. The Bode diagrams outline that this class of devices shows a non integer order behavior. Moreover, a dependance between the curing temperature and the fractional order has been shown.

From IPMC Transducers to All-Organic Transducers

This paper presents a summary about the research activity performed on characterizations and modeling of new polymeric transducers. More specifically, Ionic Polymer–Metal Composites (IPMCs) have been widely explored and a new class of totally organic transducers: Ionic Polymer-Polymer Composites (IP2Cs) have been introduced. The manufacturing technique, the electromechanical characterization and modeling of these polymeric transducers are described.

A /spl Sigma//spl Delta/ A/D converter realized by using ST52X440 microcontroller

In the paper the realization of a first order sigma-delta A/D (analog-to-digital) converter and of the software tools developed for its characterization are introduced. The A/D converter is based on the use of ST52X440 microcontroller produced by ST Microelectronics by exploiting both the availability of a comparator for the realization of the high frequency loop and its computing capability for the realization of the digital filters. A description of the hardware solutions and of the filtering blocks for the implementation of the sigma-delta converter is given. A software tool implemented in LabVIEW/spl reg/ by National Instruments/spl trade/ that realizes a custom interface for the device characterization is also described. Preliminary results suggest satisfactory performance of the device and allow to foresee interesting application in low cost sensing devices.