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Related papers: An Atomistic Model of Field-Induced Resistive Swit…

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We present a framework dedicated to modelling the resistive switching operation of Valence Change Memory (VCM) cells. The method combines an atomistic description of the device structure, a Kinetic Monte Carlo (KMC) model for the creation…

Materials Science · Physics 2022-11-23 Manasa Kaniselvan , Mathieu Luisier , Marko Mladenović

The construction of the Hamiltonian matrix \textbf{H} is an essential, yet computationally expensive step in \textit{ab-initio} device simulations based on density-functional theory (DFT). In homogeneous structures, the fact that a unit…

Disordered Systems and Neural Networks · Physics 2026-02-03 Chen Hao Xia , Manasa Kaniselvan , Marko Mladenoivić , Mathieu Luisier

A large number of simulation models have been proposed over the years to mimic the electrical behaviour of memristive devices. The models are based either on sophisticated mathematical formulations that do not account for physical and…

Emerging Technologies · Computer Science 2022-04-20 Sahitya Yarragolla , Torben Hemke , Jan Trieschmann , Finn Zahari , Hermann Kohlstedt , Thomas Mussenbrock

Resistance switching memory cells such as electrochemical metallization cells and valence change mechanism cells have the potential to revolutionize information processing and storage. However, the creation of deterministic resistance…

Mesoscale and Nanoscale Physics · Physics 2023-10-03 V. A. Slipko , Y. V. Pershin

Valence change memory (VCM) cells based on SrTiO$_3$ (STO), a perovskite oxide, are a promising type of emerging memory device. While the operational principle of most VCM cells relies on the growth and dissolution of one or multiple…

Quantum-accurate computer simulations play a central role in understanding phase-change materials (PCMs) for advanced memory technologies. However, direct quantum-mechanical simulations are necessarily limited to simplified models,…

Materials Science · Physics 2022-09-20 Yuxing Zhou , Wei Zhang , En Ma , Volker L. Deringer

Resistive switching devices emerged a huge amount of interest as promising candidates for non-volatile memories as well as artificial synapses due to their memristive behavior. The main physical and chemical phenomena which define their…

Materials Science · Physics 2018-08-01 Tobias Gergs , Sven Dirkmann , Thomas Mussenbrock

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…

The growing energy demands of information and communication technologies, driven by data-intensive computing and the von Neumann bottleneck, underscore the need for energy-efficient alternatives. Resistive random-access memory (RRAM)…

Applied Physics · Physics 2025-09-23 Md Tawsif Rahman Chowdhury , Alireza Moazzeni , Gozde Tutuncuoglu

Memristive switching devices, candidates for resistive random access memory technology, have been shown to switch off through a progression of states with quantized conductance and subsequent non-integer conductance (in terms of conductance…

Mesoscale and Nanoscale Physics · Physics 2016-11-23 Xiaoliang Zhong , Ivan Rungger , Peter Zapol , Olle Heinonen

We survey the current state of phase change memory (PCM), a non-volatile solid-state memory technology built around the large electrical contrast between the highly-resistive amorphous and highly-conductive crystalline states in so-called…

Memristive devices, whose resistance can be controlled by applying a voltage and further retained, are attractive as possible circuit elements for neuromorphic computing. This new type of devices poses a number of both technological and…

Mesoscale and Nanoscale Physics · Physics 2023-05-31 Oleg G. Kharlanov

Non-volatile magnetic storage, from 1940s magnetic core to present day racetrack memory and magnetic anisotropy switching devices rely on the metastability of magnetic domains to store information. However, the inherent inefficiency of…

Simulation frameworks such MemTorch, DNN+NeuroSim, and aihwkit are commonly used to facilitate the end-to-end co-design of memristive machine learning (ML) accelerators. These simulators can take device nonidealities into account and are…

Emerging Technologies · Computer Science 2024-03-12 Zhenming Yu , Stephan Menzel , John Paul Strachan , Emre Neftci

We present atomistic simulations of conductive bridging random access memory (CBRAM) cells from first-principles combining density-functional theory and the Non-equilibrium Green's Function formalism. Realistic device structures with an…

Polymer-assisted ion transport underpins both energy storage technologies and emerging neuromorphic computing devices. Efficient modeling of ion migration is essential for understanding the performance of batteries and memristors, but it…

We present a multiscale simulation framework to compute the current vs. voltage (I-V ) characteristics of metal/oxide/metal structures building the core of conductive bridging random access memory (CBRAM) cells and to shed light on their…

We report on resistive switching of memristive electrochemical metallization devices using 3D kinetic Monte Carlo simulations describing the transport of ions through a solid state electrolyte of an Ag/TiO$_{\text{x}}$/Pt thin layer system.…

Materials Science · Physics 2017-06-06 Sven Dirkmann , Thomas Mussenbrock

Phase-change memory (PCM), a promising candidate for next-generation non-volatile memories, exploits quenched glassy and thermodynamically stable crystalline states as reversibly switchable state variables. We demonstrate PCM functions…

Strongly Correlated Electrons · Physics 2015-01-15 H. Oike , F. Kagawa , N. Ogawa , A. Ueda , H. Mori , M. Kawasaki , Y. Tokura

Memristors as emergent nano-electronic devices have been successfully fabricated and used in non-conventional and neuromorphic computing systems in the last years. Several behavioral or physical based models have been developed to explain…

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