Results 91 to 100 of about 16,903,176 (225)
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
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
This thesis introduces fabrication and physical as well as electrical characterizations of oxide-based resistive random access memory (RRAM) which has been recently explored as one of the most promising nonvolatile memory technology.
Fang, Zheng
core +1 more source
SPICE‐Compatible Compact Modeling of Cuprate‐Based Memristors Across a Wide Temperature Range
A physics‐guided compact model for YBCO memristors is introduced, incorporating carrier trapping, field‐induced detrapping, and a differential balance equation to describe their switching dynamics. The model is compared with experiments and implemented in LTspice, allowing realistic circuit‐level simulations.
Thomas Günkel +6 more
wiley +1 more source
Low-Rank Compensation in Hybrid 3D-RRAM/SRAM Computing-in-Memory System for Edge Computing
Artificial intelligence (AI) has made significant strides, with computing-in-memory (CIM) emerging as a key enabler for energy-efficient AI acceleration.
Weiye Tang +7 more
doaj +1 more source
Silicon Nitride Resistive Memories
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
Array‐Level Characterization of Cryogenic RRAM
This paper reports the first array‐level comprehensive electrical characterization of a 1024‐device HfO2‐based RRAM array from 300, 77 to 4 K, covering forming, set/reset switching, endurance, retention, relaxation, and read disturb. The results manifest the high performance of RRAM array at cryogenic temperatures and huge application potential for ...
Yuyao Lu +7 more
wiley +1 more source
Stochastic‐MTJ Sampler Arrays for In‐Array Monte–Carlo Estimation
A low‐energy‐barrier magnetic tunnel junction array is operated as a probability‐domain sampler: each cell's random switching, programmed through a shared digital‐to‐analog converter, makes the per‐column multiply–accumulate an unbiased Monte–Carlo expectation estimator that returns both a mean and a calibrated uncertainty.
Ran Zhang +6 more
wiley +1 more source
Investigation of resistive random-accesss memory (RRAM) materials and devices
An advancement in the current technology is pushing for better technological memory devices in terms of performance and reliability. As the current technology such as DRAM and FLASH memory is reaching its limits in its technology to scale down, other ...
Sim, Wei Kiat
core
Composition‐dependent structural evolution in GeXSe1‐X selector‐only memory (SOM) is correlated with device switching behavior. Increasing Ge strengthens network rigidity, suppresses atomic motion, and stabilizes threshold switching, while narrowing the memory window. The revealed structure–property relationship provides a guideline for compositionally
Tien Anh Nguyen +9 more
wiley +1 more source
Multilevel resistive switching in Hf-based RRAM
In this paper, the multilevel switching behaviors of resistive random-access memory (RRAM) devices with three different dielectric materials such as HfO2, HfZrO2 and HfAlO2 are investigated. We have further explored the switching characteristics with two
Wajda, C. S. +7 more
core +1 more source

