Demand for Artificial Intelligence (AI) has been growing due to their usefulness in commercial electronics and in tackling global issues, such as a pandemic. However, conventional von Neumann devices that use AI require extensive programming and power. Thus, significant attention is dedicated to the brain-inspired neuromorphic computing (NC) as a more power-efficient alternative and a suitable platform for AI. NC involves a network of interconnected synapses and neurons that mimic their biological counterparts. In this work, we present a DW-based artificial neuron that automatically resets without applying current.
We simulated a synthetic antiferromagnetic (SAF) DW device where the free layer (CoFeB) is driven by spin-transfer-torque (STT), achieving the integrate function. In the absence of current, the antiferromagnetic coupling (AFC) between the free and pinned layers pushes the DW back towards the starting position. This happens automatically, and is indicative of the leakage function. The integrate and leakage functions are also achieved experimentally, suggesting that an SAF-based neuron is viable for NC.

Synthetic antiferromagnetic domain wall device as artificial neuron for neuromorphic computing

Demand for Artificial Intelligence (AI) has been growing due to their usefulness in commercial electronics as well as tackling global issues, such as a pandemic [1]. Current devices that perform AI rely on the conventional von Neumann architecture, which requires extensive programming and power [2]. Therefore, significant attention is dedicated to the brain-inspired neuromorphic computing (NC) as an alternative that is more power-efficient and a more suitable platform for AI [3]. Neuromorphic architecture consists of a network of interconnected synapses and neurons that mimic their biological counterparts [4]. Sengupta et al. have proposed a neuron design based on a domain wall device that uses a magnetic tunnel junction (MTJ) [5] at one end. The tunneling magnetoresistance (TMR) depends on the position of the DW. A current is required to move the domain wall forward or backward (integrate or leak functions respectively). In this work, we place emphasis on designing a domain wall (DW) based artificial neuron, which displays the leaky function without the requirement for a driving current. To achieve leaky function and self-reset process of neuron, we propose a domain wall device, which has an anisotropy field (Hk) gradient in the region of interest (ROI), as shown in Fig. 1(a). This anisotropy gradient is crucial in inducing the automatic returning motion of DW in the absence of current. The design is simulated using Mumax3, and the DW in the free layer nanowire (NW) is driven by spin-transfer-torque (STT). As shown in Fig. 1, current is first applied to propagate the DW towards the threshold position to “fire” the neuron device; current is subsequently removed and DW motion is observed. The micromagnetic parameters used here represent the magnetic properties of CoFeB film with a perpendicular magnetic anisotropy. The magnetic anisotropy constant (Ku) and saturation magnetization (Ms) are graded in ROI, so that Hk gradient is achieved. Some results are presented in Fig. 2(b), showing DW position vs time graph of the reference NW, without any gradient. One may notice that the DW does not return towards the initial position in these devices. Fig. 2(c) corresponds to a device with an Hk gradient. We can notice that the device enables natural return of the domain wall towards the starting position in the absence of current. This suggests that the device displays the leakage function, as well as the ability to reset after the neuron has fired. Fig. 2(d) corresponds to the same device as that of Fig. 2(c), except in this case, three current pulses are consecutively applied with a time interval of 60 ns. These results indicate that the neurons can function with a reset time of about 60 ns. The proposed design has potential applications for DW-based artificial neuron since it displays the integration and leakage functions, while the firing function can be achieved with the utilization of MTJ during the fabrication process.

**References:**

[1] Z. Hu, Q. Ge, S. Li, L. Jin, and M. Xiong, “Artificial Intelligence Forecasting of Covid-19 in China,” Feb. 2020, Accessed: Jun. 25, 2020. [Online]. Available: http://arxiv.org/abs/2002.07112. [2] R. A. Nawrocki, R. M. Voyles, and S. E. Shaheen, “A Mini Review of Neuromorphic Architectures and Implementations,” IEEE Trans. Electron Devices, vol. 63, no. 10, pp. 3819–3829, 2016, doi: 10.1109/TED.2016.2598413. [3] H. Farkhani, M. Tohidi, S. Farkhani, J. K. Madsen, and F. Moradi, “A Low-Power High-Speed Spintronics-Based Neuromorphic Computing System Using Real-Time Tracking Method,” IEEE J. Emerg. Sel. Top. Circuits Syst., vol. 8, no. 3, pp. 627–638, Sep. 2018, doi: 10.1109/JETCAS.2018.2813389. [4] J. Grollier, D. Querlioz, K. Y. Camsari, K. Everschor-Sitte, S. Fukami, and M. D. Stiles, “Neuromorphic spintronics,” Nat. Electron., 2020, doi: 10.1038/s41928-019-0360-9. [5] A. Sengupta, P. Panda, P. Wijesinghe, Y. Kim, and K. Roy, “Magnetic tunnel junction mimics stochastic cortical spiking neurons,” Sci. Rep., vol. 6, no. July, pp. 1–9, 2016, doi: 10.1038/srep30039.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/e015896fad0991ac5a8452eee8bf2d23.jpg)
The proposed 3T-MTJ device. Magnetizations of the pinned layers are fixed while that of the MTJ free layer NW can be manipulated by applying electrical current. Conduction electrons are polarized by a pinned layer and push the DW by STT. Neuronal firing happens when the DW propagates past the MTJ device, i.e. when parallel configuration of the MTJ is achieved.

![](https://assets.underline.io/uploads/markdown_image/1/image/e66f29e5f0d82f3c0bbcc2c2314dc9be.jpg)
(a) Schematic of the NW with the ROI labelled. (b and c) DW position vs time graphs for the reference NW and the result where DWs returned and stabilized around the initial position after neuronal firing. (d) is the case with three pulses sequentially applied. The interval is the same between each pulse, sufficient for DWs to stabilize around the initial position.

 Domain wall device with a graded anisotropy field as artificial neuron for neuromorphic computing

Spin-based neuromorphic computing (NC) is investigated as a power-efficient enabler for artificial intelligence [1-3]. Hence, magnetic tunnel junction (MTJ) based domain wall devices are investigated as synthetic synapses and neurons to mimic their biological counterparts [2-3]. While a biological neuron resets itself after firing, such a function has not been demonstrated experimentally in spintronic systems [3]. The self-reset feature of neurons reduces the power consumption and the complexity of NC architecture. In this work, we present a domain wall (DW) based artificial neuron that automatically resets without applying a reset pulse. At first, we simulated a synthetic antiferromagnetic (SAF) DW device where the free layer (CoFeB) is driven by spin-transfer-torque (STT) to achieve integrate function. Leakage function was achieved when the antiferromagnetic coupling (AFC) between the free and pinned layers pushes the DW towards the starting position automatically (Fig. 1). The left quarter region of the free layer is ferromagnetically coupled (FC) to the pinned layer so that as DW returns (during reset), it is stabilized at the initial position (Fig. 2(a) and Fig. 2(b)). Experimentally, the integrate and leakage functions are also achieved as illustrated in Fig. 2(d) and Fig. 2(e), suggesting that an SAF-based neuron is viable for NC.

![](https://assets.underline.io/uploads/markdown_image/1/image/4f911e30d06059db93a1e69c895660a8.jpg)

Fig.1 Proposed design of the artificial neuron. Domain wall is moved forward by STT and (after firing), reset backward by SAF coupling.


![](https://assets.underline.io/uploads/markdown_image/1/image/c297c876d46646d24593590c9f897b4d.jpg)

Fig. 2 (a and b) DW position (free layer) vs time graphs for different AFC strength in the simulations. (c, d and e) Kerr images of the fabricated SAF neuron device with magnetic field in the -z direction. (c) No current applied and device is in antiparallel configuration, (d) current is applied, pushing the DW and achieving the integrate function, and (e) current is removed and the device automatically resets, indicating the leakage function.

**Session Chair: **Hyunsoo Yang

SYM I - Probabilistic Computing and Orbital Hall Effect/Bio-inspired Devices

technical paper

**Please view our Welcome to MH21 video.**

<center>
<figure class="video_container">
	 <iframe src="https://screencast-o-matic.com/watch/cr1UYHV1pcz?v=6&ff=1&title=0&controls=1" width=826 height=526 frameborder="0" allowfullscreen="true"> </iframe>
</figure>
	</center>


**Walkthrough Video**

Here is a Walkthrough showing how to navigate the conference and network with others 

<center>
<figure class="video_container">
	 <iframe src="https://screencast-o-matic.com/watch/cr1vnrV1paE?v=6&ff=1&title=0&controls=1" width=826 height=526 frameborder="0" allowfullscreen="true"> </iframe>
</figure>
	</center>




	 Organized by
 
<a href="https://mrs.org.sg/">
<img src="https://assets.underline.io/uploads/markdown_image/1/image/95d5789689d5f900b90e9fe54ea3cf0d.jpg"</a>

 
	
	 In association with
 
<a href="http://www.ntu.edu.sg/">
<img src="https://assets.underline.io/uploads/markdown_image/1/image/334cd171ad2fdee033c635b368e5e160.png"</a>
	<a href="https://www.nus.edu.sg/">
<img src="https://assets.underline.io/uploads/markdown_image/1/image/32e6f82c0440f7bb24c590f9f67821bd.png"</a>
		<a href="https://www.a-star.edu.sg/">
<img src="https://assets.underline.io/uploads/markdown_image/1/image/72557865b589cfa3d2a0243ffce4a270.png"</a>
	
 


	 Supported by
 
		 <a href="https://www.visitsingapore.com/mice/en/about-us/about-secb/">
<img src="https://assets.underline.io/uploads/markdown_image/1/image/6e679842ead62be522ba6a630b82d5c9.png"</a>

To access the MH 21 Conference, [please register](https://mh21.mrs.org.sg/event/da3f9651-429f-4763-81b2-ebd7311b6bc8/websitePage:206f7605-1731-41f9-8421-56d3890f398f)

MATERIALS FOR HUMANITY (MH 21)

MH 21 is arranged around 6 themes that focus attention on pressing needs that should be addressed to enhance the well-being of communities and provide a forum for presenting breakthrough discoveries.

*Session Co-Chair: Xin Fan, University of Denver Division of Natural Sciences and Mathematics*

*Session Co-Chair: Shuyuan Shi, Beihang University*

These on-demand presentations are available to view at your leisure. 

CP: Spintronics Fundamentals

poster

INTERMAG 2021 Welcome Video



	
<figure class="video_container">
 <iframe src="https://screencast-o-matic.com/player/crflqFVnUpZ?v=6&ff=1&title=0&controls=1" width=640 height=360 frameborder="0" allowfullscreen="true"> </iframe>
</figure>

Want to buy a ticket? 

Register for INTERMAG 2021 here

[![](https://assets.underline.io/uploads/markdown_image/1/image/17ce76e7960db633258024eef8d6da7f.png)](https://intermag.org/register)

Got your ticket, but still can’t access the event?

Contact us and our team will look into it.

INTERMAG 2021

**Session chairs:** Liliana Buda-Prejbeanu, SPINtronique et Technologie des Composants and Yoshinobu Nakatani, The University of Electro-Communications



HPA - Magnetization Dynamics

The 15th Joint MMM-INTERMAG Conference (2022 Joint) is sponsored jointly by AIP Publishing and the IEEE Magnetics Society. Members of the international scientific and engineering communities interested in recent developments in fundamental and applied magnetism are invited to attend and contribute to the technical sessions. The technical program will include invited and contributed papers in oral and poster sessions, invited symposia, a plenary session, and an evening session, with about 1500 presentations overall. This Conference provides an outstanding opportunity for worldwide participants to meet their colleagues and collaborators and discuss developments in all areas of magnetism research.

The 2022 Joint Conference will offer both in-person and prerecorded on-demand content.

For tickets to the event, please register at the following link: https://magnetism.org/register

Please register for the Joint MMM-Intermag conference to join the event.

2022 Joint MMM-INTERMAG

This Conference provides an outstanding opportunity for worldwide participants to meet their colleagues and collaborators and discuss developments in all areas of magnetism research.

Wai Lum William Mah

3

SHORT BIO

Presentations

Synthetic antiferromagnetic domain wall device as artificial neuron for neuromorphic computing

Domain wall device with a graded anisotropy field as artificial neuron for neuromorphic computing

Synthetic antiferromagnetic domain wall device as artificial neuron for neuromorphic computing

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES