Body Dust: Modeling of NanoAntennas for Remote Powering by UltraSound
**** Master Project ****
Imagine an advance in technology that could enable the development of fully drinkable and autonomous bio-electronic CMOS sensors in the form of dust particles, capable of identifying the source of a disease by targeting a specific region in organs and tissue such as a tumor mass and automatically sending diagnostic information wirelessly outside the body. We call this swarm of sensing dust particles ‘Body Dust’. A diagnostic system in the form of Body Dust would need to be small enough to support free circulation in human tissues, which requires a total size of less than 10 μm3, in order to mimic the typical sizes of a blood cell (e.g., white cells have the diameter around 30 μm). Whilst with present state-of-the-art in CMOS technology, this requirement in terms of size is currently un-feasible, recent research has advanced technology such that we can begin to work towards such an approach. Therefore, we propose here to investigate the current limits of CMOS technology as well as the challenges related to the development of such a system.
Concept of the project showing the piezo-electric transducer
for the ultrasound powering signal
Towards the above-mentioned goal, this Master project aims to investigate the possibility for remote powering such a system with an ultrasonic powering from outside of the body. The target of the project is to investigate the feasibility to built a piezoelectric transducer for remote powering by Ultra-Sounds with suitable sizes compatible with the design of drinkable CMOS diagnostic system. Starting from the state-of-the-art analysis in Ultra-Sounds remote power and data links, the analysis should highlight the trade-offs of such a system and provide the main specifications, represented by the transferred power and its efficiency, the area occupation, the link constraints in range and frequency for a future prototype implementation.
Tracking cancer-cell development with “drinkable” electronic sensors, EPFL News: https://actu.epfl.ch/news/tracking-cancer-cell-development-with-drinkable-el/
Seo, D., Carmena, J. M., Rabaey, J. M., Alon, E., & Maharbiz, M. M. (2013). Neural dust: An ultrasonic, low power solution for chronic brain-machine interfaces. arXiv preprint arXiv:1307.2196.