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Pietro Siciliano

Researcher at National Research Council

Publications -  408
Citations -  9933

Pietro Siciliano is an academic researcher from National Research Council. The author has contributed to research in topics: Thin film & Wearable computer. The author has an hindex of 51, co-authored 386 publications receiving 9000 citations. Previous affiliations of Pietro Siciliano include Nuclear Regulatory Commission & International Military Sports Council.

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Solid state gas sensors: state of the art and future activities

TL;DR: In this paper, the authors give an overview of the principles and technologies used in solid-state gas sensors, which work by measuring a physical property changed by adsorption/desorption processes and chemical reactions on the surface of a sensing element.
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Flexible thermoelectric generator for ambient assisted living wearable biometric sensors

TL;DR: In this paper, the authors proposed design, fabrication and functional characterization of a very low cost energy autonomous, maintenance free, flexible and wearable micro thermoelectric generator (μTEG), finalized to power very low consumption electronics ambient assisted living (AAL) applications.
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Sensing characteristics of NiO thin films as NO2 gas sensor

TL;DR: In this article, the results concerning the characterisation of nickel oxide thin films deposited by d.c. reactive magnetron sputtering were presented, where different NiO thin films were prepared by changing some deposition parameters, such as the oxygen content in the reactive plasma and the sputtering mode.
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The Role of Surface Oxygen Vacancies in the NO2 Sensing Properties of SnO2 Nanocrystals

TL;DR: In this paper, the SnO2 nanocrystals were prepared by injecting a hydrolyzed methanol solution of SnCl4 into a tetradecene solution of dodecylamine.
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On the study of feature extraction methods for an electronic nose

TL;DR: In this paper, the transient information of microsensors based on tin oxide sol-gel thin film has been analyzed for data analysis and discrimination among different volatile organic compounds, and several feature extraction methods have been considered, including Fourier and wavelet descriptors, integral and derivatives.