Related papers: Nanocryotron-driven Charge Configuration Memristor
Reservoir computing is a highly efficient machine learning framework for processing temporal data by extracting features from the input signal and mapping them into higher dimensional spaces. Physical reservoir layers have been realized…
We put forward a new proposal of designing charge-based logic devices considering a cyclic molecule that can be programmed and re-programmed for different functional logical operations and suitably engineered for data storage as well. The…
In this paper, we report on the charge transport properties of hybrid nanoparticles (NPs) based on the polymeric 1D compound [Fe(Htrz)2(trz)](BF4), which is one of the most promising SCO systems for designing electronic devices. In…
Neuromorphic computing systems uses non-volatile memory (NVM) to implement high-density and low-energy synaptic storage. Elevated voltages and currents needed to operate NVMs cause aging of CMOS-based transistors in each neuron and synapse…
The first contribution of this paper is the development of extremely dense, energy-efficient mixed-signal vector-by-matrix-multiplication (VMM) circuits based on the existing 3D-NAND flash memory blocks, without any need for their…
The development of memristive device technologies has reached a level of maturity to enable the design of complex and large-scale hybrid memristive-CMOS neural processing systems. These systems offer promising solutions for implementing…
Memristor, one of the fundamental circuit elements, has promising applications in non-volatile memory and storage technology as it can theoretically achieve infinite states. Information can be stored independently in these states and…
We have calculated the key characteristics of associative (content-addressable) spatial-temporal memories based on neuromorphic networks with restricted connectivity - "CrossNets". Such networks may be naturally implemented in…
We propose carbon as new resistive memory material for non-volatile memories and compare three allotropes of carbon, namely carbon nanotubes, graphene-like conductive carbon and insulating carbon for their possible application as…
Photonic quantum memristors provide a measurement-induced route to nonlinear and history-dependent quantum dynamics. Experimental demonstrations have so far focused on isolated devices or simple cascaded devices configurations. Here, we…
High-Tc Type-II ceramic-superconductor at temperature T < Tc, under presence of magnetic-field B becomes non-superconducting if B exceeds a critical value Bc2. Thus at T < Tc, by application/absence of critical magnetic- field as a…
The demands of modern electronic components require advanced computing platforms for efficient information processing to realize in-memory operations with a high density of data storage capabilities towards developing alternatives to von…
We propose a simple model of a nanoswitch as a memory resistor. The resistance of the nanoswitch is determined by electron tunneling through a nanoparticle diffusing around one or more potential minima located between the electrodes in the…
Typical mammal brains have some form of random connectivity between neurons. Reservoir computing, a neural network approach, uses random weights within its processing layer along with built-in recurrent connections and short-term, fading…
Cuprate high-temperature superconductors, such as Yttrium Barium Copper Oxide (YBCO), are extremely promising for emerging technologies such as low-power computing, data storage, quantum sensors and superconducting electronics. However, the…
Phase-tunable hybrid devices, built upon nanostructures combining normal metal and superconductors, have been the subject of intense studies due to their numerous combinations of different charge and heat transport configurations. They…
The memristor is the fundamental non-linear circuit element, with uses in computing and computer memory. ReRAM (Resistive Random Access Memory) is a resistive switching memory proposed as a non-volatile memory. In this review we shall…
Memristor technology shows great promise for energy-efficient computing, yet it grapples with challenges like resistance drift and inherent variability. For filamentary Resistive RAM (ReRAM), one of the most investigated types of memristive…
The object of this article is to review the development of ultrahigh-density, nanoscale data storage, i.e., nanostorage. As a fundamentally new type of storage system, the recording mechanisms of nanostorage may be completely different to…
Neuromorphic computing --- brainlike computing in hardware --- typically requires myriad CMOS spiking neurons interconnected by a dense mesh of nanoscale plastic synapses. Memristors are frequently citepd as strong synapse candidates due to…