Journal Article


Efficient sensing approaches for high-density memristor sensor array

Abstract

Recent research shows ever growing interest in the potential applications of memristive devices. Among the many proposed fields, sensing is one of the most interesting as it could lead to unprecedented sensor density and ubiquity in electronic systems. In this paper, a framework for efficient gas detection using memristor crossbar array is proposed and analysed. A novel Verilog-A based memristor model that emulates the gas sensing behaviour of doped metal oxides is developed for simulation and integration with design automation tools. Using this model, we propose and analyse three different gas detection structures based on array of memristor-based sensors. Gas presence together with some of its properties can be detected using resistance changes and spatial information from one or group of memristive sensors. Our simulation results show that depending on the organisation of the memristive elements and the sensing method, the response of the sensor varies providing a broader design space for future designers. For instance, with a 8 × 8 memristor sensor array, there is a ten times improvement in the accuracy of the sensor’s response when compared with a single memristor sensor but at the expense of extra area overhead.

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Authors

Adeyemo, Adedotun
Mathew, Jimson
Jabir, Abusaleh
Di Natale, Corrado
Martinelli, Eugenio
Ottavi, Marco

Oxford Brookes departments

Faculty of Technology, Design and Environment\School of Engineering, Computing and Mathematics

Dates

Year of publication: 2018
Date of RADAR deposit: 2018-04-17


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


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