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In Valence Change Memory (VCM) cells, the conductance of an insulating switching layer is reversibly modulated by creating and redistributing point defects under an external field. Accurate simulations of the switching dynamics of these…

Disordered Systems and Neural Networks · Physics 2023-01-02 Manasa Kaniselvan , Mathieu Luisier , Marko Mladenović

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…

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…

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

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

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

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

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

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…

The massive parallel approach of neuromorphic circuits leads to effective methods for solving complex problems. It has turned out that resistive switching devices with a continuous resistance range are potential candidates for such…

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…

Mesoscale and Nanoscale Physics · Physics 2012-06-14 Marcus Wu Shihong , Themistoklis Prodromakis , Iulia Salaoru , Christofer Toumazou

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

In this paper, we build a general modelling framework for memristors, suitable for the simulation of event-based systems such as hardware spiking neural networks, and more generally, neuromorphic computing systems composed of three…

Emerging Technologies · Computer Science 2025-12-02 Waleed El-Geresy , Christos Papavassiliou , Deniz Gündüz

We present molecular-dynamic simulations of memory resistors (memristors) including the crystal field effects on mobile ionic species such as oxygen vacancies appearing during operation of the device. Vacancy distributions show different…

Materials Science · Physics 2015-05-28 S. E. Savel'ev , A. S. Alexandrov , A. M. Bratkovsky , R. Stanley Williams

Resistive memories are outstanding electron devices that have displayed a large potential in a plethora of applications such as nonvolatile data storage, neuromorphic computing, hardware cryptography, etc. Their fabrication control and…

Resistive Random Access Memories (RRAMs) are being studied by the industry and academia because it is widely accepted that they are promising candidates for the next generation of high density nonvolatile memories. Taking into account the…

This paper examines the coexistence of resistive, capacitive, and inertia (virtual inductive) effects in memristive devices, focusing on ReRAM devices, specifically the interface-type or non-filamentary analog switching devices. A…

Mesoscale and Nanoscale Physics · Physics 2024-01-30 Sahitya Yarragolla , Torben Hemke , Jan Trieschmann , Thomas Mussenbrock

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

We model electrical conductivity in metastable amorphous $Ge_{2}Sb_{2}Te_{5}$ using independent contributions from temperature and electric field to simulate phase change memory devices and Ovonic threshold switches. 3D, 2D-rotational, and…

Applied Physics · Physics 2021-02-03 Jake Scoggin , Helena Silva , Ali Gokirmak

A powerful time series analysis modeling technique is presented to describe cycle-to-cycle variability in memristors. These devices show variability linked to the inherent stochasticity of device operation and it needs to be accurately…

Mesoscale and Nanoscale Physics · Physics 2024-02-08 Francisco J. Alonso , David Maldonado , Ana M. Aguilera , Juan B. Roldán
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