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Langmuir-Blodgett films of pyrrole derivatives: electrical characterization by microelectronic test structures for sensor applications
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An Optimized AC/DC Buck-Boost Converter for Wind Energy Harvesting Application
No full textThe need for low cost power sources was always the scope of researchers, especially for applications such as Wireless sensor networks (WSN), where the maintenance and replacement of energy storage units is costly. In this sense, energy harvesting (EH) is more reliable and cheaper due to its unlimited availability. Though, the environment conditions are usually unpredictable, which requires a specialized circuit to be used with the energy harvesters to ensure the efficient power transfer and to adapt to the variable conditions. The proposed system is a specialized EH circuit for the fluttering wind harvester. It consists of an AC/DC buck-boost converter, controlled by a low power microcontroller which adapts the performance according the variable wind conditions, giving an edge over commercial circuits for the same purpose
Investigation of the conductivity properties of Langmuir-Blodgett films of pyrrole derivatives
No full textIn this paper, we present conductivity measurements made on Langmuir-Blodgett (LB) polymeric films obtained from pyrrole derivatives (3-hexadecyl-pyrrole and mixtures 3-hexadecyl-pyrrole/pyrrole) and deposited onto interdigitated stuctures designed ad hoc for electrical measurements on planar structures, Step response and voltage vs. current characteristics are reported and discussed, with particular attention to linearity and stability; from these data, the resistivity values of both types of film are derived. The results show that monolayers obtained from the mixtures are by far more conductive (four orders of magnitude) than pure 3-hexadecyl-pyrrole (3HP) multilayers, and that their electrical behaviour can be easily related to a pure Ohmic behaviour, while the 3HP multilayers cannot be considered as pure Ohmic components
Efficient emulation of neural networks on concurrent architectures for optimization problems
No full textSpecific optimization problems can be solved with high efficiency by neural network models, due to their intrinsic massive parallelism. The emulation of neural algorithms on concurrent architectures can preserve their computational power. The authors illustrate and discuss the implementation of Hopfield networks for the solution of the traveling salesman problem on 2-D meshes of transputers. The investigations are concentrated both on the computational efficiency and on the quality of solutions (global-local minima issue)
Scanning Tunneling Microscopy Investigations of Self-Assembled Monolayers of Poly(3-decyl-thiophene) on Graphite
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