Memristor-based neural networks: a bridge from device to artificial intelligence
Since the beginning of the 21st century, there is no doubt that the importance of artificial
intelligence has been highlighted in many fields, among which the memristor-based artificial …
intelligence has been highlighted in many fields, among which the memristor-based artificial …
Oxygen Vacancy Transition in HfOx‐Based Flexible, Robust, and Synaptic Bi‐Layer Memristor for Neuromorphic and Wearable Applications
In this work, a reliable bilayer flexible memristor is demonstrated using TaOx/HfOx Bi‐layer
(BL) to mimic synaptic characteristics by using oxygen concentration engineering in the …
(BL) to mimic synaptic characteristics by using oxygen concentration engineering in the …
High‐Performance and Environmentally Robust Multilevel Lead‐Free Organotin Halide Perovskite Memristors
With a striking explosion of digital information, organic–inorganic halide perovskite (OHP)
memristors have been regarded as a promising solution to break the von Neumann …
memristors have been regarded as a promising solution to break the von Neumann …
Low Power Stochastic Neurons From SiO2-Based Bilayer Conductive Bridge Memristors for Probabilistic Spiking Neural Network Applications—Part I: Experimental …
P Bousoulas, C Tsioustas, J Hadfield… - … on Electron Devices, 2022 - ieeexplore.ieee.org
The development of low-power neurons with an intrinsic degree of stochasticity is
considered quite important for the emulation of the respective probabilistic procedures that …
considered quite important for the emulation of the respective probabilistic procedures that …
Self-Assembled Au Nanoelectrodes: Enabling Low-Threshold-Voltage HfO2-Based Artificial Neurons
Filamentary-type resistive switching devices, such as conductive bridge random-access
memory and valence change memory, have diverse applications in memory and …
memory and valence change memory, have diverse applications in memory and …
Simulation of low power self-selective memristive neural networks for in situ digital and analogue artificial neural network applications
C Tsioustas, P Bousoulas, J Hadfield… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Self-selective memory devices are considered promising candidates for suppressing the
undesired sneak path currents that appear within crossbar memory structures and …
undesired sneak path currents that appear within crossbar memory structures and …
Conduction mechanism analysis of abrupt-and gradual-switching InGaZnO memristors
In this work, two types of InGaZnO (IGZO) memristors were fabricated to confirm the
conduction mechanism and degradation characteristics of memristors with different …
conduction mechanism and degradation characteristics of memristors with different …
Impact of inert electrode on the volatility and non-volatility switching behavior of SiO2-based conductive bridge random access memory devices
C Tsioustas, P Bousoulas, G Kleitsiotis… - Applied Physics …, 2024 - pubs.aip.org
The development of disruptive artificial neural networks (ANNs) endowed with brain-inspired
neuromorphic capabilities is emerging as a promising solution to deal with the challenges of …
neuromorphic capabilities is emerging as a promising solution to deal with the challenges of …
Phosphorylation Enables Nano‐Graphene for Tunable Artificial Synapses
Flexible and robust memristors with controllable resistance‐switching characteristics are
important to neuromorphic computing. However, the nanomaterials‐based, solution …
important to neuromorphic computing. However, the nanomaterials‐based, solution …
Emulating low power nociceptive functionalities with a forming-free SiO2/VOx conductive bridge memory with Pt nanoparticles
P Bousoulas, C Tsioustas, D Tsoukalas - Applied Physics Letters, 2022 - pubs.aip.org
The fabrication of low-power and scalable electronic devices that will have the ability to
emulate the properties of the biological nociceptors is of great importance for the …
emulate the properties of the biological nociceptors is of great importance for the …