Results 71 to 80 of about 15,800,744 (205)
Small, EarlyView.Bio‐inspired computing offers a route to highly energy‐efficient artificial intelligence. The unique physical properties of two‐dimensional (2D) materials can further enhance such computing approaches. This perspective highlights recent developments in 2D materials‐based neuromorphic devices and discusses future opportunities for integrating such novel
Jin Feng Leong +9 more
wiley +1 more source
A data-driven Verilog-A ReRam model
, 2018 The translation of emerging application concepts that exploit Resistive Random Access Memory (ReRAM) into large-scale practical systems requires realistic yet computationally efficient device models.
Nikolaidis, Spyridon +10 more
core +1 more source
Small, EarlyView.BNNT rods incorporated into MWCNT–ZnO quantum dot networks regulate charge transport and suppress leakage in flexible, transparent resistive memory devices. The resulting hybrid architecture preserves nonvolatile switching under static bending and after low‐temperature exposure and subcutaneous implantation.
Jaeho Shim +11 more
wiley +1 more source
Polymer-Assisted Solution Processing of TiO2 Thin Films for Resistive-Switching Random Access Memory
, 2017 In this study, we present a polymer-assisted solution (PAS) process to prepare TiO2 electrolyte layers for resistive-switching random access memory (ReRAM). The PAS process utilizes the stability of metal-polymer complexes in the coating solution to form
Kim, Jihoon +2 more
core +1 more source
Small, EarlyView.Real‐world graph data are directly mapped onto an mCBA, enabling node similarity to be computed through a single current readout. Strongly nonlinear devices suppress long‐range multi‐hop contributions while preserving local connectivity, whereas weakly nonlinear devices allow excessive signal propagation.
Jae‐Hyun Lee +7 more
wiley +1 more source
Noise and Drift Models for Protonic ECRAM and Their Impact on Analog In‐Memory Computing
Advanced Computing, Volume 1, Issue 1, December 2026.Read noise and conductance drift of protonic electrochemical random‐access memory (ECRAM) are characterized and described using physics‐informed device models. These models connect proton transport and measured current fluctuations to analog in‐memory computing (AIMC) performance.
Xin Su, Haoran Liu, Qing Cao, Ning Li
wiley +1 more source
Micromachines, 2019 Graphene oxide (GO) has been actively utilized in nonvolatile resistive switching random access memory (ReRAM) devices due to solution-processability, accessibility for highly scalable device fabrication for transistor-based memory, and cross-bar memory ...
Lei Li, Guangming Li
doaj +1 more source
Low‐Frequency Noise Evolution in Thin SiNx ReRAMs After Sequential Constant Voltage Stress
physica status solidi (a), Volume 223, Issue 21, 11 November 2026.In this work, thin SiNx films in MIS ReRAM cells are stressed with a constant voltage for various sequential durations (25, 45, 65, 110 and 250 s) and the low‐frequency noise signal generated after each stress duration is measured using different sampling rates.
Alexandros E. Mavropoulis +7 more
wiley +1 more source
Resistive Switching Behavior in HfO 2 with Nb as an Oxygen Exchange Layer
, 2015 The effect of Nb as an oxygen exchange layer in HfO2 based resistive random access memory (ReRAM) is investigated. The advantages of Nb are demonstrated by comparing the performance of Pt/HfO2/Pt and Pt/HfO2/Nb ReRAM devices.
Nandi, Sanjoy +5 more
core +1 more source
Energy-Accuracy Trade-Offs for Resistive In-Memory Computing Architectures
IEEE Journal on Exploratory Solid-State Computational Devices and CircuitsResistive in-memory computing (IMC) architectures currently lag behind SRAM IMCs and digital accelerators in both energy efficiency and compute density due to their low compute accuracy.
Saion K. Roy, Naresh R. Shanbhag
doaj +1 more source