Analysis of Quantized Electrical Characteristics of Microscale TiO2 Ink-Jet Printed Memristor

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The research presented in this article draws inspiration from previous efforts aimed at replicating the functions of various solid-state memristors using a variety of materials. The memristor circuit emulator serves as a cost-effective tool for circuit des ...

Highly data-centric AI workloads require that new computing paradigms be adopted because the performance of traditional CPU- and GPU-based systems are limited by data access and transfer. Training deep neural networks with millions of tunable parameters ta ...

Kinetic equilibrium reconstruction (KER) in tokamaks is the solution of the free-boundary MHD equilibrium that best fits the external magnetic measurements and the internal plasma profiles as imposed from modeling and/or available internal measurements. In ...

The thermal coarsening of titanate nanowires was investigated from room temperature to 1000 degrees C by AFM, SEM, XRD and Raman spectroscopy. Phase transformation kinetics and the external morphology were studied in two configurations: i) as individual an ...

The present research aims at understanding the mass transfer of air into water in a reversible pump turbine operating in condenser mode. In particular, the diffusion of oxygen through the water free-surface both in the vaneless gap between the impeller bla ...

Fractional Levy motion has been derived from its generalized Langevin equation via path integrals in earlier works and has since proven to be a useful model for nonlocal and non-Markovian processes, especially in the context of nondiffusive transport. Here ...

Recrystallization of minerals due to fluid infiltration modifies their original chemical and isotopic signature. Such processes are sought after as they give access to timescales of geologic processes, which are commonly quantified using diffusion chronome ...

Particle transport in tokamak plasmas has been intensively studied in the past, particularly in relation to density peaking and the presence of anomalous inward particle convection in L-and H-modes. While in the L-mode case the presence of the anomalous in ...

Neuromorphic systems provide brain-inspired methods of computing. In a neuromorphic architecture, inputs are processed by a network of neurons receiving operands through synaptic interconnections, tuned in the process of learning. Neurons act simultaneousl ...

Hybrid perovskites have attracted enormous attention in the next generation resistive switching (RS) memristor for the artificial synapses, owing to their ambipolar charge transport, long diffusion length, and tunable visible bandgap. However, the variable ...

We provide a theoretical description of dynamical heterogeneities in glass-forming liquids, based on the premise that relaxation occurs via local rearrangements coupled by elasticity. In our framework, the growth of the dynamical correlation length e and o ...

Neuromorphic systems using memristive devices provide a brain-inspired alternative to the classical von Neumann processor architecture. In this work, a spiking neural network (SNN) implemented using phase-change synapses is studied. The network is equipped ...

Equilibrium and nonequilibrium molecular dynamics simulations are combined to compute the full set of coefficients that appear in the phenomenological equations describing thermal transport in a binary mixture subject to a constant thermal, gradient The Dy ...

In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from m ...

We present the very first worldwide ever-reported electrochemical biosensor based on a memristive effect and DNA aptamers. This novel device is developed to propose a completely new approach in cancer diagnostics. In this study, an affinity-based technique ...

Energy in today's short-range wireless communication is mostly spent on the analog-and digital hardware rather than on radiated power. Hence, purely information-theoretic considerations fail to achieve the lowest energy per information bit and the optimiza ...

We cast the problem of source localization on graphs as the simultaneous problem of sparse recovery and diffusion ker- nel learning. An l1 regularization term enforces the sparsity constraint while we recover the sources of diffusion from a single snapshot ...

In the present work, a computational study is carried out investigating the relationship between the biosensing and the electrical characteristics of two-terminal Schottky- barrier silicon nanowire devices. The model suggested successfully reproduces compu ...

The conduction of heat in two dimensions displays a wealth of fascinating phenomena of key relevance to the scientific understanding and technological applications of graphene and related materials. Here, we use density-functional perturbation theory and a ...

Thermally stimulated current (TSC) is a widely used technique to assess trap states and extract their density, energy, and capture rate using analytical expressions. In many cases, the latter are derived from physical models pertaining to inorganic semicon ...

Analysis of Quantized Electrical Characteristics of Microscale TiO2 Ink-Jet Printed Memristor

Chattez avec Graph Search

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