most citedAnalytical Modelling of the Transport in Analog Filamentary Conductive-Metal-Oxide/HfOx ReRAM Devices

13 citations · 13 across the 3 of their papers we have counts for

collaborators

8 papers

cs.NE2025

Unsupervised local learning based on voltage-dependent synaptic plasticity for resistive and ferroelectric synapses

Nikhil Garg, Ismael Balafrej, Joao Henrique Quintino Palhares +11

The deployment of AI on edge computing devices faces significant challenges related to energy consumption and functionality. These devices could greatly benefit from brain-inspired…

cs.ET202513 cited

Analytical Modelling of the Transport in Analog Filamentary Conductive-Metal-Oxide/HfOx ReRAM Devices

Donato Francesco Falcone, Stephan Menzel, Tommaso Stecconi +4

The recent co-optimization of memristive technologies and programming algorithms enabled neural networks training with in-memory computing systems. In this context, novel analog fi…

cs.ET2025

Energy-convergence trade off for the training of neural networks on bio-inspired hardware

Nikhil Garg, Paul Uriarte Vicandi, Yanming Zhang +5

The increasing deployment of wearable sensors and implantable devices is shifting AI processing demands to the extreme edge, necessitating ultra-low power for continuous operation.…

cond-mat.mtrl-sci2025

Decoupling Electric Field and Temperature-Driven Atomistic Forming Mechanisms in TaOx/HfO2-Based ReRAMs using Reactive Molecular Dynamics Simulations

Simanta Lahkar, Valeria Bragaglia, Behnaz Bagheri +4

Resistive random access memories (ReRAMs) with a bilayer TaOx/HfO2 stack structure have shown unique multi-level resistive switching capabilities. However, the physical processes g…

cond-mat.mtrl-sci2025

Electroforming Kinetics in HfOx/Ti RRAM: Mechanisms Behind Compositional and Thermal Engineering

Manasa Kaniselvan, Kevin Portner, Donato Francesco Falcone +6

A critical issue affecting filamentary resistive random access memory (RRAM) cells is the requirement of high voltages during electroforming. Reducing the magnitude of these voltag…

cs.ET2025

Hardware Implementation of Ring Oscillator Networks Coupled by BEOL Integrated ReRAM for Associative Memory Tasks

Wooseok Choi, Thomas van Bodegraven, Jelle Verest +8

We demonstrate the first hardware implementation of an oscillatory neural network (ONN) utilizing resistive memory (ReRAM) for coupling elements. A ReRAM crossbar array chip, integ…