Related papers: Superconducting bimodal ionic photo-memristor
Non-volatile resistive switching, also known as memristor effect in two terminal devices, has emerged as one of the most important components in the ongoing development of high-density information storage, brain-inspired computing, and…
Memristors, uniquely characterized by their pinched hysteresis loop fingerprints, have attracted significant research interest over the past decade, due to their enormous potential for novel computation and artificial intelligence…
Combining scanning electron microscopy (SEM) and electron-beam-induced current (EBIC) imaging with transport measurements, it is shown that the current flowing across a two-terminal oxide-based capacitor-like structure is preferentially…
Memristors have been suggested as neuromorphic computing elements. Spike-time dependent plasticity and the Hodgkin-Huxley model of the neuron have both been modelled effectively by memristor theory. The d.c. response of the memristor is a…
It is now widely accepted that memristive devices are perfect candidates for the emulation of biological synapses in neuromorphic systems. This is mainly because of the fact that like the strength of synapse, memristance of the memristive…
We present an integrated circuit fabricated in a process co-integrating CMOS and hafnium-oxide memristor technology, which provides a prototyping platform for projects involving memristors. Our circuit includes the periphery circuitry for…
We designed and experimentally demonstrated a four-terminal superconducting device which can function as a non-latching (reversible) superconducting switch from the diode regime to the resistive state by applying a control current much…
This study explores the impact of organic cations in bismuth iodide complexes on their memristive behavior in metal-insulator-metal (MIM) type thin-layer devices. The presence of electron-donating and electron withdrawing functional groups…
Neuromorphic computing has emerged as a promising avenue towards building the next generation of intelligent computing systems. It has been proposed that memristive devices, which exhibit history-dependent conductivity modulation, could…
Memristive associative learning has gained significant attention for its ability to mimic fundamental biological learning mechanisms while maintaining system simplicity. In this work, we introduce a high-order memristive associative…
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 engineering makes use of mixed-signal analog and digital circuits to directly emulate the computational principles of biological brains. Such electronic systems offer a high degree of adaptability, robustness, and energy…
Memristor crossbar arrays are used in a wide range of in-memory and neuromorphic computing applications. However, memristor devices suffer from non-idealities that result in the variability of conductive states, making programming them to a…
Superconducting electronics represents a promising technology, offering not only efficient integration with quantum computing systems, but also the potential for significant power reduction in high-performance computing. Nonetheless, the…
Brain-inspired computing has the potential to revolutionise the current von Neumann architecture, advancing machine learning applications. Signal transmission in the brain relies on voltage-gated ion channels, which exhibit the electrical…
Neuromorphic networks of artificial neurons and synapses can solve computational hard problems with energy efficiencies unattainable for von Neumann architectures. For image processing, silicon neuromorphic processors outperform graphic…
The development of high-performance multifunctional polymer-based electronic circuits is a major step towards future flexible electronics. Here, we demonstrate a tunable approach to fabricate such devices based on rationally designed…
Spin-torque memristors were proposed in 2009, which could provide fast, low-power and infinite memristive behavior for large-density non-volatile memory and neuromorphic computing. However, the strict requirements of combining high…
Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuron transistors gated by solid-state electrolyte films are fabricated on flexible plastic substrates for biochemical sensing…
A new mechanism for memristive switching in 2D materials is through electric-field controllable electronic/structural phase transitions, but these devices have not outperformed status quo 2D memristors. Here, we report a high-performance…