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Memristive devices hold promise to improve the scale and efficiency of machine learning and neuromorphic hardware, thanks to their compact size, low power consumption, and the ability to perform matrix multiplications in constant time.…

Emerging Technologies · Computer Science 2024-08-14 Zhenming Yu , Ming-Jay Yang , Jan Finkbeiner , Sebastian Siegel , John Paul Strachan , Emre Neftci

Two-dimensional (2D) layered ferroelectrics, as an emerging area of research, have attracted extensive attention, while memristors based on new 2D ferroelectric materials have yet to be fully explored, thereby limiting their applications in…

Neurons with internal memory have been proposed for biological and bio-inspired neural networks, adding interesting functionality. We propose and model a nanoscale optoelectronic neural node with charge-based time-limited memory and signal…

Applied Physics · Physics 2023-09-22 David Winge , Magnus Borgström , Erik Lind , Anders Mikkelsen

We present a computationally inexpensive yet accurate phenomenological model of memristive behavior in titanium dioxide devices by fitting experimental data. By design, the model predicts most accurately I-V relation at small non-disturbing…

Materials Science · Physics 2015-06-22 Farnood Merrikh-Bayat , Brian Hoskins , Dmitri B. Strukov

With the broad recent research on ferroelectric hafnium oxide for non-volatile memory technology, depolarization effects in HfO2-based ferroelectric devices gained a lot of interest. Understanding the physical mechanisms regulating the…

Emerging Technologies · Computer Science 2025-08-13 Luca Fehlings , Thomas Mikolajick , Beatriz Noheda , Erika Covi

Understanding the physical and chemical mechanisms occurring during the forming process and operation of an organic resistive memory device is a major issue for better performances. Various mechanisms were suggested in vertically stacked…

The transport of fluids at the nanoscale is fundamental to manifold biological and industrial processes, ranging from neurotransmission to ultrafiltration. Yet, it is only recently that well-controlled channels with cross-sections as small…

Mesoscale and Nanoscale Physics · Physics 2022-10-05 Nikita Kavokine , Paul Robin , Lydéric Bocquet

Memristors are an electronic device whose resistance depends on the voltage history that has been applied to its two terminals. Despite its clear advantage as a computational element, a suitable transport model is lacking for the special…

Emerging Technologies · Computer Science 2022-10-05 T. F. Tiotto , A. S. Goossens , A. E. Dima , C. Yakopcic , T. Banerjee , J. P. Borst , N. A. Taatgen

The coexistence and coupling between magnetization and electric polarization in multiferroic materials provide extra degrees of freedom for creating next-generation memory devices. A variety of concepts of multiferroic or magnetoelectric…

Materials Science · Physics 2016-06-23 Jianxin Shen , Junzhuang Cong , Dashan Shang , Yisheng Chai , Shipeng Shen , Kun Zhai , Young Sun

The memristor can be used as non volatile memory (NVM) and for emulating neuron behavior. It has the ability to switch between low resistance $R_{on}$ and high resistance values $R_{off}$, and exhibit the synaptic dynamic behaviour such as…

Emerging Technologies · Computer Science 2018-09-28 Aidana Irmanova , Grant A. Ellis , Alex Pappachen James

Magnetic skyrmions are particle-like textures in the magnetization, characterized by a topological winding number. Nanometer-scale skyrmions have been observed at room temperature in magnetic multilayer structures. The combination of small…

Strongly Correlated Electrons · Physics 2017-02-14 Jan Müller

In this work we report on the role of ion transport for the dynamic behavior of a double barrier quantum mechanical Al/Al$_2$O$_3$/Nb$_{\text{x}}$O$_{\text{y}}$/Au memristive device based on numerical simulations in conjunction with…

Materials Science · Physics 2016-05-31 Sven Dirkmann , Mirko Hansen , Martin Ziegler , Hermann Kohlstedt , Thomas Mussenbrock

High-fidelity analysis of translocating biomolecules through nanopores demands shortening the nanocapillary length to a minimal value. Existing nanopores and capillaries, however, inherit a finite length from the parent membranes. Here, we…

Polymer materials with low water uptake exhibit a highly heterogeneous interior, characterized by water clusters in the form of nanodroplets and nanochannels. Here, based on our recent insights from computer simulations, we argue that water…

Soft Condensed Matter · Physics 2022-06-16 Matej Kanduč , Rafael Roa , Won Kyu Kim , Joachim Dzubiella

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…

Nanofluidics, the field interested in flows at the smallest scales, has grown at a fast pace, reaching an ever finer control offluidic and ionic transport at the molecular level. Still, artificial pores are far from reaching the wealth of…

Soft Condensed Matter · Physics 2023-05-10 Paul Robin , Lydéric Bocquet

Electrolyte-filled channels with modulated wall charge distribution subjected to an applied DC electric field, form time-independent vortices whose sense of circulation is determined by the field direction [Physical Review Letters $…

Fluid Dynamics · Physics 2026-02-02 A. Shrestha , E. Kirkinis , M. Olvera de la Cruz

We report on hybrid memristive devices made of a network of gold nanoparticles (10 nm diameter) functionalized by tailored 3,4(ethylenedioxy)thiophene (TEDOT) molecules, deposited between two planar electrodes with nanometer and micrometer…

Overcoming the limitations of the von Neumann architecture requires new computational paradigms capable of solving complex problems efficiently. Quantum and neuromorphic computing rely on unconventional materials and device functionalities,…

Memristive reservoirs draw inspiration from a novel class of neuromorphic hardware known as nanowire networks. These systems display emergent brain-like dynamics, with optimal performance demonstrated at dynamical phase transitions. In…

Disordered Systems and Neural Networks · Physics 2023-06-23 Ruomin Zhu , Jason K. Eshraghian , Zdenka Kuncic