Low-power environmental Nanosensoren

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PhD-02

Low-power environmental nanosensors and electronics

Short project description

Power consumption is still today one of the main limiting factors for the realization and deployment of ubiquitous sensor networks. While the energy budget of fully passive sensors can be accommodated within the constraints imposed by the batteries or the energy harvesting systems of the network nodes, the power demand of existing active sensors (e.g. those requiring thermal or optical energy to come into operation) is just too high. Precisely, the vast majority of sensors of interest for environmental monitoring, control and security (e.g. chemical sensors, for gases or liquids, particle sensors, etc.) are active sensors. Such a lack of suitable low-power sensor technologies limits the magnitudes that can be monitored and thus the interest, impact and use of ubiquitous networks in environmental applications.

In the last decade, the groups proposing this project have developed strategies for significantly lowering power consumption in active sensors. In the field of heated sensors, the self-heating effect in nanowires probed to be a method capable of lowering power consumption down to the μW regime, which is a 1000 times reduction compared to state of the art heaters based on MEMS. In the field of illuminated sensors, the miniaturization of LED to a few microns scale allowed for reducing power well below the mW regime, which is also a several order of magnitude improvement. At the same time, the efforts in miniaturizing heating and illumination components lead to much faster switching times. This enables the use of ultrafast time modulated methods for more selective sensing (e.g. time resolved gas response analysis, luminescence decay measurements, etc.)

This thesis proposal is part of a large research European project in which low power sensing elements based on thermal and optical excitation are being developed. Specifically, the sensors under development aim at selective sensing of chemical species using functionalized semiconductor surfaces (such as metal oxides and nitrides) and optical detection of other airborne and diluted species with absorption, fluorescence and time decay methods. Also, sensor network demonstrators integrating these devices are being developed. In this framework the candidate will learn and take responsibility on device design and test (electrical characterization and sensor properties in operation), simulation for results analysis and integration in sensor networks.

Supervisor

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PhD Student