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High-performance MTJ-based sensors for monitoring of atmospheric pollution.

Authors :
Amara, Selma
Aljedaibi, Abdulrahman
Alrashoudi, Ali
Ben Mbarek, Sofiane
Khan, Danial
Massoud, Yehia
Source :
AIP Advances; Mar2023, Vol. 13 Issue 3, p1-5, 5p
Publication Year :
2023

Abstract

Solid and liquid particles in the atmosphere, referred to as airborne particulate matter (PM), have been rising significantly over the past two decades. Exposure to PM carries significant health risks such as lungs damage, heart disease, cancer, and death. PM<subscript>2.5</subscript> is a subgroup of PM particles that are smaller than 2.5 µm and is a major concern as it is more harmful to health and more difficult to detect. One problematic component of PM<subscript>2.5</subscript> is magnetite nanoparticles (<200 nm), which are readily absorbed into the bloodstream through the respiratory system. Eventually, magnetite nanoparticles deposit inside the brain causing neurodegenerative diseases such as Alzheimer's or cancerous tumors by inducing oxidative stress. Additionally, Magnetite nanoparticles are often surrounded by heavy metal nanoparticles such as Cadmium and lead which are a great concern to the environment and health. Traditional PM detection methods such as laser scattering are bulky, expensive, and incapable of detecting particles smaller than 200 nm such as magnetite nanoparticles. Therefore, developing a low-cost highly sensitive sensor for monitoring magnetite nanoparticles is vital. Tunneling Magneto-Resistance (TMR) sensors are an attractive option due to their low-cost and high sensitivity toward magnetic nanoparticle detection. Moreover, developing a cheap, portable, and precise remote monitoring technique will allow for the creation of high spatial resolution highly sensitive monitoring networks for magnetic PM<subscript>2.5</subscript>. This work focuses on developing, modeling, and simulation of low-cost highly sensitive TMR sensor based on Magnetic Tunnel Junction (MTJ) that can detect and count magnetite nanoparticles. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21583226
Volume :
13
Issue :
3
Database :
Complementary Index
Journal :
AIP Advances
Publication Type :
Academic Journal
Accession number :
162858128
Full Text :
https://doi.org/10.1063/9.0000496