Related papers: Superconducting bimodal ionic photo-memristor
Iontronics is a burgeoning paradigm that employs ions in solution as information carriers for sensing and computing, e.g., in neuromorphic devices. The fundamentally different working principle as compared to electronics requires novel…
Memristors based on a double barrier design have been analysed by various nano spectroscopic methods to unveil details about its microstructure and conduction mechanism. The device consists of an AlOx tunnel barrier and a NbOy/Au Schottky…
Solid state ionic conductors are good candidates for the next generation of nonvolatile computer memory elements. Such devices have to show reproducible resistance switching at reasonable voltage and current values even if scaled down to…
Nanometallic devices based on amorphous insulator-metal thin films are developed to provide a novel non-volatile resistance-switching random-access memory (RRAM). In these devices, data recording is controlled by a bipolar voltage, which…
Memristive devices are promising elements for energy-efficient neuromorphic computing and future artificial intelligence systems. For diffusive memristors, the device state switching occurs because of the sequential formation and…
Memristors have been intensively studied in recent years as promising building blocks for next-generation non-volatile memory, artificial neural networks and brain-inspired computing systems. Even though the environment adaptability of…
Optical memristors are innovative devices that enable the integration of electro-optical functionalities - such as light modulation, multilevel optical memory, and nonvolatile reprogramming - into neuromorphic networks. Recently, their…
Neuromorphic computing based on spiking neural networks has the potential to significantly improve on-line learning capabilities and energy efficiency of artificial intelligence, specially for edge computing. Recent progress in…
Superconducting devices, which rely on modulating a complex superconducting order parameter in a Josephson junction, have been developed for low power logic operations, high-frequency oscillators, and exquisite magnetic field sensors.…
Optical communication achieves high fanout and short delay advantageous for information integration in neural systems. Superconducting detectors enable signaling with single photons for maximal energy efficiency. We present designs of…
A memristive device is a novel passive device, which is essentially a resistor with memory. This device can be utilized for novel technical applications like neuromorphic computation. In this paper, we focus on anticipation - a capability…
Beyond-Moore computing technologies are expected to provide a sustainable alternative to the von Neumann approach not only due to their down-scaling potential but also via exploiting device-level functional complexity at the lowest possible…
We discuss the physical properties of realistic memristive, memcapacitive and meminductive systems. In particular, by employing the well-known theory of response functions and microscopic derivations, we show that resistors, capacitors and…
This work introduces a fully tunable, ultra-low power unipolar memory cell inspired by the Schmitt-trigger comparator and designed in CMOS using only nine transistors. The proposed circuit operates entirely in the current domain and…
Conceptual memristors have recently gathered wider interest due to their diverse application in non-von Neumann computing, machine learning, neuromorphic computing, and chaotic circuits. We introduce a compact CMOS circuit that emulates…
In living organisms, information is processed in interconnected symphonies of ionic currents spiking through protein ion channels. As a result of dynamically switching their conductive states, ion channels exhibit a variety of…
Recent advances in nanoscale science and technology provide possibilities to directly self-assemble and integrate functional circuit elements within the wiring scheme of devices with potentially unique architectures. Electroionic resistive…
Metallic oxides encased within Metal-Insulator-Metal (MIM) structures can demonstrate both unipolar and bipolar switching mechanisms, rendering them the capability to exhibit a multitude of resistive states and ultimately function as memory…
Memristors have been positioned at the forefront of the purposes for carrying out neuromorphic computation. Their tuneable conductivity properties enable the imitation of synaptic behaviour. Multipore nanofluidic memristors have shown their…
Photonics integrated circuits have a huge potential to serve as a framework for a new class of information processing machines and can enable ultrafast artificial neural networks. They can overcome the existing speed and power limits of the…