Electronic Systems and Integrated Microelectronic Systems
Energy Harvesting for Embedded Systems
Teacher: Davide Brunelli
Energy harvesting is the capability to convert and extract energy from the environment and power embedded electronic systems (e.g. wearable electronic, sensor networks, multimedia devices).
The activity proposed aims at designing, developing and validating energy harvesting models for Embedded Systems and Wireless Sensor Network (WSN) to improve the energy efficiency of applications towards Energy Neutral Systems.
The task primarily involves modelling of the energy harvesting sources and computation loads of the application, hardware and software co-design of the systems to optimise the performance of application with energy harvesting, power management and ambient energy storage solutions.
Thin silicon 3D radiation sensors with charge multiplication
Teacher: Gian Franco Dalla Betta
This activity aims at developing novel silicon radiation sensors with three dimensional electrodes on thin substrates (50 – 100 um), mainly oriented to High Energy Physics applications (CERN HL-LHC).
These sensors will allow for charge multiplication by avalanche effect at reasonably low bias voltages (in the order of 100V), both before and after irradiation.
Moderate gain values (lower than 10) are targeted, that are high enough to compensate the signal reduction due to the use of thin substrates and to counteract charge trapping effects even after very large radiation fluences (~1016 neq/cm2). New design solutions and modified fabrication technologies will be studied, making extensive use of TCAD simulations, and device prototypes will be processed and tested.
Optimization and characterization of position-sensitive silicon photomultipliers (co-financed project)
Position-sensitive, analog SiPM (PS-SiPM) are designed for the readout of segmented scintillators with a limited number of channels, in gamma-ray imaging applications, such as PET or SPECT. They are of great interest because they allow a fine segmentation of the scintillator without excessively increasing the complexity of the readout electronics, potentially enabling next-generation machines, such as high-resolution MR-compatible PET for small animal imaging.
The Ph.D. student will work on the experimental characterization of the first iteration of the PS-SiPM already fabricated at FBK, on the optimization of the corresponding readout electronics, and will take part in the design and optimization of the next iterations of the detector. He will also investigate the potential of the PS-SiPM in different novel applications and will have the opportunity to get in touch and collaborate with some of the most highly reputed groups in the field of molecular imaging.
Memristor-based computing architectures with advanced signal processing capabilities (co-financed project)
Memristor is the fourth fundamental two-terminal circuit element, together with resistor, capacitor and inductor. It was predicted by Leon Chua in 1971 and took more than 30 years to be realized by HP in 2008.
In this project, advanced processing architectures will be developed, exploiting the main characterisitcs of the memristor, which combines resistive and memory properties. Novel computational system architectures will be developed, enabling adaptations and learning capabilities at the hardware level.
The candidate is asked to investigate novel electronic circuits, exploiting memristor characteristics, to be the basic building blocks for the realization of prototypes of a complex adaptive network, performing complex logic functions. Starting from the electrical model of the memristor, novel CMOS electronic circuits will be designed, interfaced with memristive devices and characterized. The activity will be carried out in the framework of the project “MaDEleNA” financed by Provincia Autonoma di Trento, in collaboration other partners.
Indoor localization and positioning
Teacher: David Macii
This research topic is focused on development and characterization of localization and position tracking techniques in indoor environments, based on multi-sensor data fusion. Distance estimation relies on time-of-flight and received strength measurements of radio signals as well as on data collected from inertial sensors (e.g. accelerometers, encoders and gyroscopes).
The research activities include at first an experimental performance analysis of existing and innovative sensors.
Afterwards, suitable algorithms should be developed and optimized in order to minimize the overall measurement uncertainty.
Finally, the proposed techniques have to be tested and their performance evaluated on the field using an experimental tested.
Optical sensors for time-resolved imaging applications
Teacher: Lucio Pancheri
The goal of this activity is the development of novel image sensors for time-resolved light detection.
Time-resolved optical sensing finds both industrial and research applications, including Time-Of-Flight range measurement, time-resolved fluorescence spectroscopy, Positron Emission Tomography and Raman spectroscopy.
This activity combines device and circuit level approaches to design application-specific sensors with improved characteristics with respect to current state-of-the-art solutions. Devices and circuits will be analyzed and designed using CAD simulation tools, fabricated in an industrial CMOS process and validated through an experimental characterization.
Energy Management Under Smart Grid Schemes
Teacher: Dario Petri
This activity aims at developing a multi-level optimisation framework based on energy loads, renewable energy sources and smart grid configuration, to ease demand response and load management scenarios.
An analytical model of the loads (e.g. residential, industry, data center) will be built for different energy profiles. These profiles will be specified for the various workload levels. Grid state estimation and time synchronization techniques can also be developed to support the proposed analysis.
The proposed solution developed will be then designed, implemented in hardware and software and tested to operate with several varying factors such as workload migrations, renewable energy produced by PV systems, available grid power or energy storage capabilities.