Exploiting the Electric Field Control of Spintronics for Brain-Inspired Systems

Laboratory: Centre de Nanosciences et de Nanotechnologies Orsay
(formely known as Institut d’Electronique Fondamentale), Université Paris-Sud

Address: Bat 220, Campus Scientifique, 91405 Orsay
Advisor: Damien QUERLIOZ and Liza HERRERA DIEZ

E-mail: damien.querlioz@c2n.upsaclay.fr , liza.herrera-diez@c2n.upsaclay.fr


Spin electronics, which exploits both the charge and the spin properties of electrons, is a major breakthrough in nanoelectronics. A simple device can provide rich and tunable behaviors, which cannot be obtained with devices relying exclusively on the charge of electrons. Currently, one of the most exciting development in spin electronics research is to use such devices as basic elements for brain-inspired electronic systems1,2,3. Indeed, the brain itself computes using nanodevices with rich and tunable devices, and this is believed one of the key reasons of its efficiency and intelligence.

In this project, the student will create spintronic devices that are ideal for this purpose. During the Master’s internship, the student will simulate and design novel types of spintronic structures that have a special potential for bioinspired computing, using primarily “micromagnetic” simulation. These structures exploit the electric field control of spin electronics4, and domain wall motion5. During the subsequent PhD thesis, the student will fabricate (in the new C2N clean room in Palaiseau) and characterize his/her designs.

This effort is part of a large project that recently received 1.5M€ of funding through the European Research Council (ERC) for the invention of natively intelligent memory.

Scientific and technical work, prerequisites:

More specifically, the student will design superparamagnetic devices that can be controlled using electric field. Such devices can allow forms of “stochastic computing” that mirror the concept of population coding in neuroscience. After this first study, the student will design structures that associate memory and stochastic effects by controlling the motion of domain walls. Such devices could mirror some complex behaviors of synapses in the brain and allow very powerful learning systems.

The internship will mostly be based on simulation studies to understand the topic and design novel spintronic structures. The student will design and simulate spintronic structures using. The subsequent PhD work will associate device simulation, clean room work and electrical characterization.

This challenging project is ideal for a physics student with curiosity toward bioinspiration, or for an engineering student with a strong interest in physics. Comfort with computers is necessary but the knowledge of programming is not needed for this project. Some experience of clean room work is appreciated, but not essential. No knowledge of neuroscience or artificial intelligence is expected, but the student should be excited to learn about those topics.

The project takes place within the interdisciplinary INTEGNANO research group, which associates research on nanodevices, bioinspired computing and artificial intelligence. Researchers and students of very diverse backgrounds work in this group, making it an exciting environment that fosters interdisciplinary thinking.

1 J. Torrejon, …, D. Querlioz, …, “Neuromorphic computing with nanoscale spintronic oscillators”, Nature, Vol. 547, p. 428. 2017.

2D. Vodenicarevic, …, and D. Querlioz, “Low-energy truly random number generation with superparamagnetic tunnel junctions for unconventional computing”, Physical Review Applied, accepted, 2017.

3D. Querlioz, et al, “Bioinspired Programming of Memory Devices for Implementing an Inference Engine”, Proceedings of the IEEE, Vol. 103, No. 8, p. 1398, 2015.

4Y.T. Liu, … and L Herrera Diez, Electric field controlled domain wall dynamics and magnetic easy axis switching in liquid gated CoFeB/MgO films. Journal of Applied Physics, 122(13), 133907 2017.

.5J-P. Tetienne, …, L. Herrera Diez, … “Nanoscale imaging and control of domain-wall hopping with a nitrogen-vacancy center microscope.” Science 344.6190 (2014): 1366-1369.

Skills to be learnt: The student will learn methodologies of simulation, device fabrication and characterization in spin electronics. He/she will also learn a lot about bioinspired computing and artificial intelligence. The PhD is adapted to a career in both academia and industry.

Funding: Funding for the internship and the PhD thesis is available through the ERC project.