Spintronic Nanodevices for Neuromorphic Sensing Chips (original) (raw)

Zuo, Siming, Ghannam, Rami ORCID logoORCID: https://orcid.org/0000-0001-6910-9280 and Heidari, Hadi ORCID logoORCID: https://orcid.org/0000-0001-8412-8164(2018) Spintronic Nanodevices for Neuromorphic Sensing Chips. 11th International Conference on Developments in e-Systems Engineering (DeSE 2018), Cambridge, UK, 2-5 Sep 2018.

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Abstract

Recent developments in spintronics materials and physics are promising to develop a new type of magnetic sensors which can be embedded into the silicon chips. These neuromorphic sensing chips will be designed to capture the biomagnetic signals from active biological tissue exploited as brain-machine interface. They lead to machines that are able to sense and interact with the world in humanlike ways and able to accelerate years of fitful advance in artificial intelligence. To detect the weak biomagnetic signals, this work aims to develop a CMOS-compatible spintronic sensor based on the magnetoresistive (MR) effect. As an alternative to bulky superconducting quantum interference device (SQUID) systems, the miniaturised spintronic devices can be integrated with standard CMOS technologies makes it possible to detect weak biomagnetic signals with micron-sized, non-cooled and low-cost. Fig. 1 shows the finite element method (FEM)-based simulation results of a Tunnelling-Magnetoresistive (TMR) sensor with an optimal structure in COMSOL Multiphysics. The finest geometry and material are demonstrated and compared with the state-of-the-art. The proposed TMR sensor achieves a linear response with a high TMR ratio of 172% and sensitivity of 223 μV/Oe. The results are promising for utilizing the TMR sensors in future miniaturized brain-machine interface, such as Magnetoencephalography (MEG) systems for neuromorphic sensing.

Item Type: Conference or Workshop Item
Status: Published
Refereed: Yes
Glasgow Author(s) Enlighten ID: Heidari, Professor Hadi and Zuo, Dr Siming and Ghannam, Professor Rami
Authors: Zuo, S., Ghannam, R., and Heidari, H.
College/School: College of Science and Engineering > School of EngineeringCollege of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
Related URLs: Organisation

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Deposit and Record Details

ID Code: 168292
Depositing User: Dr Aniko Szilagyi
Datestamp: 05 Sep 2018 12:18
Last Modified: 02 May 2025 19:05
Date of acceptance: 15 August 2018
Date of first online publication: 4 September 2018
Date Deposited: 10 September 2018