3 citations · 6 across the 7 of their papers we have counts for
7 papers
Multibit neural inference in a N-ary crossbar architecture
Anatole Moureaux, Anthony Lopes Temporao, Flavio Abreu Araujo
In-memory computing (IMC) is a paradigm that enables neural network inference by computing analog matrix-vector multiplications (MVM) directly in memory crossbar arrays, with the p…
Nanoscale resistive switching in electrodeposited MOF Prussian blue analogs driven by K-ion intercalation probed by C-AFM
L. B. Avila, O. de Leuze, M. Pohlitz +12
K-ion intercalation in Prussian blue analogs (PBAs) is a well-established charge storage mechanism in potassium-ion batteries; here, we demonstrate that this same ion intercalation…
Geometrical properties of 3D crossed nanowire networks
Tristan da Câmara Santa Clara Gomes, Nicolas Marchal, Anatole Moureaux +5
Three-dimensional interconnected nanowire networks have recently attracted notable attention for the fabrication of new devices for energy harvesting/storage, sensing, catalysis, m…
Current-controlled periodic double-polarity reversals in a spin-torque vortex oscillator
Chloé Chopin, Simon de Wergifosse, Anatole Moureaux +1
Micromagnetic simulations are used to study a spin-torque vortex oscillator excited by an out-of-plane dc current. The vortex core gyration amplitude is confined between two orbits…
Spintronics for image recognition: performance benchmarking via data-driven simulations
Anatole Moureaux, Chloé Chopin, Simon de Wergifosse +2
We present a demonstration of image classification using an extreme learning machine (ELM) based on a unique simulated magnetic tunnel junction (MTJ) delayed in time. As the ground…
Neuromorphic spintronics simulated using an unconventional data-driven Thiele equation approach
Anatole Moureaux, Simon de Wergifosse, Chloé Chopin +1
In this study, we developed a quantitative description of the dynamics of spin-torque vortex nano-oscillators (STVOs) through an unconventional model based on the combination of th…
Neuromorphic spintronics accelerated by an unconventional data-driven Thiele equation approach
Anatole Moureaux, Simon De Wergifosse, Chloé Chopin +2
We design a neural network based on a single spin-torque vortex nano-oscillator (STVO) multiplexed in time. The behavior of the STVO is simulated with an improved ultra-fast and qu…