Related papers: Electric selective activation of memristive interf…
We present a computationally inexpensive yet accurate phenomenological model of memristive behavior in titanium dioxide devices by fitting experimental data. By design, the model predicts most accurately I-V relation at small non-disturbing…
Owing to the outstanding properties provided by nontrivial band topology, topological phases of matter are considered as a promising platform towards low-dissipation electronics, efficient spin-charge conversion, and topological quantum…
Dual-layer resistive switching devices with horizontal W electrodes, vertical Pd electrodes and WOx switching layer formed at the sidewall of the horizontal electrodes have been fabricated and characterized. The devices exhibit…
Brain-inspired computing and neuromorphic hardware are promising approaches that offer great potential to overcome limitations faced by current computing paradigms based on traditional von-Neumann architecture. In this regard, interest in…
Achieving reliable resistive switching in oxide-based memristive devices requires precise control over conductive filament (CF) formation and behavior, yet the fundamental relationship between oxide material properties and switching…
Memristor technologies have been rapidly maturing for the past decade to support the needs of emerging memory, artificial synapses, logic gates and bio-signal processing applications. So far, however, most concepts are developed by…
Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Their additive…
The persistent and switchable polarization of ferroelectric materials based on HfO$_2$-based ferroelectric compounds, compatible with large-scale integration, are attractive synaptic elements for neuromorphic computing. To achieve a record…
In this paper, we review the different memristive threshold logic (MTL) circuits that are inspired from the synaptic action of flow of neurotransmitters in the biological brain. Brain like generalisation ability and area minimisation of…
Neuromorphic computing aims to develop energy-efficient devices that mimic biological synapses. One promising approach involves memristive devices that can dynamically adjust their electrical resistance in response to stimuli, similar to…
The objective of this paper is to explore the possibility to couple two van der Pol (vdP) oscillators via a resistance-capacitance (RC) network comprising a Ag-TiOx-Al memristive device. The coupling was mediated by connecting the gate…
Memristors are continuously tunable resistors that emulate synapses. Conceptualized in the 1970s, they traditionally operate by voltage-induced displacements of matter, but the mechanism remains controversial. Purely electronic memristors…
The recent co-optimization of memristive technologies and programming algorithms enabled neural networks training with in-memory computing systems. In this context, novel analog filamentary conductive-metal-oxide (CMO)/HfOx redox-based…
Memristors are non-volatile nano-resistors. Their resistance can be tuned by applied currents or voltages and set to a large number of levels between two limit values. Thanks to these properties, memristors are ideal building blocks for a…
Vertical structures of SiO$_{2}$ sandwiched between a top tungsten electrode and conducting non-metal substrate were fabricated by dry and wet etching methods. Both structures exhibit similar voltage-controlled memory behaviors, in which…
Reversible resistive switching between high-resistance and low-resistance states in metal-oxide-metal heterostructures makes them very interesting for applications in random access memories. While recent experimental work has shown that…
Construction and training principles have been proposed and tested for an artificial neural network based on metal-oxide thin-film nanostructures possessing bipolar resistive switching (memristive) effect. Experimental electronic circuit of…
Acting as artificial synapses, two-terminal memristive devices are considered fundamental building blocks for the realization of artificial neural networks. Organized into large arrays with a top-down approach, memristive devices in…
Resistance Random Access Memory (RRAMTM) device, with its electrically induced nanoscale resistive switching capacity, has been gaining considerable attention as future non-volatile memory device. Here, we propose a mechanism of switching…
Memristors, when utilized as electronic components in circuits, can offer opportunities for the implementation of novel reconfigurable electronics. While they have been used in large arrays, studies in ensembles of devices are comparatively…