Results 31 to 40 of about 227,656 (114)

A Dual‐Programmable 2M NOR Flash Architecture for Energy‐Efficient In‐Memory Computing

open access: yesAdvanced Science, EarlyView.
In conventional NOR Flash, the access transistor occupies area but stores no information. Here, it is repurposed as a programmable second memory device that plays two functional roles: an analog memory element that lowers the minimum read current from 72.7 nA to 4.22 pA, and a current‐path gating element enabling true‐off pruning and current‐range ...
Suhan Kim   +4 more
wiley   +1 more source

Investigation of the potentialities of Vertical Resistive RAM (VRRAM) for neuromorphic applications

open access: yes, 2015
International audienceCombining Resistive RAM concept with Vertical NAND technology and design, Vertical RRAM (VRRAM) was recently proposed as a cost-effective and extensible technology for future mass data storage applications [1].
Carabasse, C.   +35 more
core   +1 more source

Model‐Based Time‐Modulated Write Algorithm for 1R Analog Memristive Crossbar Arrays

open access: yesAdvanced Electronic Materials, EarlyView.
A novel model‐based time‐modulated write algorithm efficiently programs analog 1R memristive crossbar arrays by varying pulse duration at a fixed voltage. By leveraging a physics‐based compact model and a dynamic gain mechanism, this approach overcomes device nonlinearities and parasitic effects.
Richard Schroedter   +7 more
wiley   +1 more source

Insight into physics-based RRAM models – review

open access: yesThe Journal of Engineering, 2019
This article presents a review of physical, analytical, and compact models for oxide-based RRAM devices. An analysis of how the electrical, physical, and thermal parameters affect resistive switching and the different current conduction mechanisms that ...
Arya Lekshmi Jagath   +3 more
doaj   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

open access: yesAdvanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho   +6 more
wiley   +1 more source

Fundamental variability limits of filament-based RRAM

open access: yes, 2016
While Resistive RAM (RRAM) are seen as an alternative to NAND Flash, their variability and cycling understanding remain a major roadblock. Extensive characterizations of multi-kbits RRAM arrays during Forming, Set, Reset and cycling operations are ...
C. Zambelli   +21 more
core   +1 more source

Enabling Quantum‐Compatible Nonvolatile Memory: Cryogenic Evaluation of 1T1R HfO2‐Based RRAM From 300 to 1.5 K

open access: yesAdvanced Electronic Materials, EarlyView.
Resistive memory devices are explored for operation at extremely low temperatures relevant to quantum computing. The study reveals how transistor behavior strongly influences memory performance under cryogenic conditions and introduces an optimized programming strategy.
Emilio Pérez‐Bosch Quesada   +11 more
wiley   +1 more source

Silicon Nitride Resistive Memories

open access: yesAdvanced Electronic Materials, EarlyView.
Amorphous SiNx is an attractive resistance switching material for ReRAM applications due to its physicochemical properties, such as humidity resistance, low oxygen diffusivity, and is used as a metal diffusion blocker. By modifying the ratio between N and Si atoms, the microstructure of the SiNx is affected, rendering it possible to change the ...
Alexandros‐Eleftherios Mavropoulis   +7 more
wiley   +1 more source

Environmental Effects on RRAM Cells Based on 2D Halide Perovskite Materials

open access: yesAdvanced Electronic Materials, EarlyView.
RRAM offers high speed, scalability, and low power, positioning it as a next‐generation non‐volatile memory. Two‐dimensional halide perovskites show promise due to tunable optoelectronic properties and flexible processing but suffer from environmental sensitivity. This review examines degradation from humidity, temperature, light, and strain, discusses
Mojtaba Joodaki   +3 more
wiley   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

open access: yesAdvanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj   +2 more
wiley   +1 more source

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