Journal Article


Low power memristive gas sensor architectures with improved sensing accuracy

Abstract

Memristive devices, traditionally considered for memory, logic, and neuromorphic systems, are exhibiting many interesting properties for applications in a variety of areas, such as in sensing chemicals. However, any realistic approach based on these devices must take into account their susceptibility to process and parametric variations. When used for sensing purposes this, together with wire resistance, can significantly degrade their sensing accuracy. To this end, we propose novel memristive gas sensor architectures that can significantly reduce these effects in a predictable manner, while improving accuracy and overall power consumption. Additionally, we show that in the absence of gasses this architecture can also be configured to realize multifunction logic operations as well as Complementary Resistive Switch with low hardware overhead, thereby enhancing resource reusability. We also present a method for further improving power consumption and measurability by manipulating a device's internal barrier. Our results show that the proposed architecture is significantly immune to process and parametric variations compared to a single sensor and almost unaffected by wire resistance, while offering much higher accuracy and much lower power consumption compared to existing techniques.

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Authors

Khandelwal, Saurabh
Ottavi, Marco
Martinelli, Eugenio
Jabir, Abusaleh

Oxford Brookes departments

School of Engineering, Computing and Mathematics

Dates

Year of publication: 2022
Date of RADAR deposit: 2022-04-29


Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License


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