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  4. From 0.18 mu m to 28nm CMOS Down-scaling for Data Links in Body Dust Applications
 
conference paper

From 0.18 mu m to 28nm CMOS Down-scaling for Data Links in Body Dust Applications

Barbruni, Gian Luca  
•
Carrara, Sandro  
•
Ros, Paolo Motto
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January 1, 2021
2021 Ieee Sensors
20th IEEE Sensors Conference

In this work, we study the effect of transistor downscaling in a wireless communication circuit for Body Dust application. The system requires a chip lateral size smaller than 10 mu m miming the typical size of a red blood cell and so, supporting free circulation in human tissues. Moreover, an ultra-low-power architecture is needed since the system is battery-less and wirelessly powered via acoustic power transfer. The aim of this paper is to present a data communication system for Body Dust systems, which works from the multiplexed sensor read-out front-end to the transmitter back-end taking account diagnostic information on different metabolite concentrations in human body. This work shows that scaling the architecture from a 0.18-mu m to 28-nm CMOS processes, it is possible to improve both size and power consumption. The improvement is about 40 times in size (2000 mu m(2) down to 50 mu m2) and two order of magnitude in average power consumption (10 mu W to cents of nW).

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Type
conference paper
DOI
10.1109/SENSORS47087.2021.9639639
Web of Science ID

WOS:000755468300144

Author(s)
Barbruni, Gian Luca  
Carrara, Sandro  
Ros, Paolo Motto
Demarchi, Danilo
Date Issued

2021-01-01

Publisher

IEEE

Publisher place

New York

Published in
2021 Ieee Sensors
ISBN of the book

978-1-7281-9501-8

Series title/Series vol.

IEEE Sensors

Subjects

Engineering, Electrical & Electronic

•

Remote Sensing

•

Engineering

•

Remote Sensing

•

body dust

•

ulp cmos design

•

transistor downscaling

•

active biosensors

•

sub-10 mu m cmos architectures

•

ook modulation

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
ICLAB  
Event nameEvent placeEvent date
20th IEEE Sensors Conference

ELECTR NETWORK

Oct 31-Nov 04, 2021

Available on Infoscience
February 28, 2022
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/185794
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