Results 101 to 110 of about 16,611 (244)

Study on ion dynamics of hafnium oxide RRAM by electrode thermal effect

, 2022
Sichen Qin, Yifei Ma, Qian Wang, Jiawei Zhang, Guiquan Zhang, Lixin Yang, Rui Liu   +6 more
openalex   +1 more source

Chemically‐Linked Heterostructures of Palladium Nanosheets and 2H‐MoS2

Small, EarlyView.
The photoresponse of MoS2 devices is extended to the near‐infrared region (up to 1700 nm) through chemical connection to Pd nanosheets (PdNS). A maleimide is used for covalent connection to MoS2, and a phenyl bromide moiety for linkage to the PdNS. In the absence of the chemical linker, van der Waals heterostructures show poorer enhancement of the ...
Ramiro Quirós‐Ovies, Pablo Bastante, Simon Hettler, Víctor Vega‐Mayoral, Sergio Aina, Vasileios Balos, Thomas Pucher, Andrés Castellanos‐Gomez, Raul Arenal, Juan Cabanillas‐Gonzalez, Emilio M. Pérez, Jesús Santamaría, Víctor Sebastian   +12 more
wiley   +1 more source

Rapid Temperature Annealing Effect on Bipolar Switching and Electrical Properties of SiC Thin Film-Resistant Random-Access Memory Devices

Engineering Proceedings
In this study, silicon carbide (SiC) thin films for resistive random-access memory (RRAM) devices were successfully prepared using the radio-frequency magnetron sputtering method at deposition powers of 50 and 75 W for 1 h.
Kai-Huang Chen, Ming-Cheng Kao, Yao-Chin Wang, Hsin-Chin Chen, Chin-Chueh Huang Kao   +4 more
doaj   +1 more source

MXene‐Based Flexible Memory and Neuromorphic Devices

Small, EarlyView.
The unique two‐dimensional structure, excellent electrical conductivity, and diverse surface groups of MXenes have garnered significant attention. Coupled with their exceptional flexibility, MXene‐based devices hold immense potential for flexible memory and neuromorphic systems. This review comprehensively discusses the fundamentals of flexible devices,
Yan Li, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Yan Yan, Shuangmei Xue, Kui Zhou, Meng Zhang, Yutong Zhang, Qi‐Jun Sun, Yi Liu, Vellaisamy A. L. Roy, Ye Zhou, Su‐Ting Han   +13 more
wiley   +1 more source

Self‐Powered Neuromorphic Touch Sensors Based on Triboelectric Devices: Current Approaches and Open Challenges

Small, EarlyView.
This review outlines how triboelectric self‐powered tactile sensors can be integrated with neuromorphic devices to emulate human touch. It summarizes current coupling strategies, operational modes, and synaptic functions enabled by triboelectric nanogerator (TENG)‐based systems, while highlighting key mechanisms, performance considerations, and future ...
Fabrizio Torricelli, Giuseppina Pace
wiley   +1 more source

Bayesian Inference via GeTex‐OTS Based Stochastic Synapse for Uncertainty‐Aware Medical Diagnostics

SmartMat, Volume 7, Issue 1, February 2026.
This work reports a GeTex ovonic threshold switch integrated into a compact 1S1T1R stochastic synapse that directly realizes an MC‐Dropconnect Bayesian neural network. Tunable probabilistic switching enables uncertainty‐aware COVID‐19 diagnosis and MNIST recognition while remaining compatible with conventional 1T1R CIM architectures, highlighting a ...
Xinyu Wen, Lun Wang, Kuan Wang, Vivian Zhao, Zixuan Liu, Kexun He, Jianguo Yang, Hao Tong, Xiangshui Miao, Yuhui He   +9 more
wiley   +1 more source

Statistical temperature coefficient distribution in analog RRAM array: impact on neuromorphic system and mitigation method

, 2021
Heng Xu, Yue Sun, Yangyang Zhu, Xiaohu Wang, Guoxuan Qin   +4 more
openalex   +1 more source

Exploring the Impact of Variability in Resistance Distributions of RRAM on the Prediction Accuracy of Deep Learning Neural Networks [PDF]

, 2020
Nagaraj Lakshmana Prabhu, Desmond Loy Jia Jun, Putu Andhita Dananjaya, Wen Siang Lew, Eng Huat Toh, Nagarajan Raghavan   +5 more
openalex   +1 more source

Analysis on the Filament Structure Evolution in Reset Transition of Cu/HfO2/Pt RRAM Device [PDF]

, 2016
Meiyun Zhang, Shibing Long, Yang Li, Qi Liu, Hangbing Lv, E. Miranda, J. Suñé, Ming Liu   +7 more
openalex   +1 more source

Low-Rank Compensation in Hybrid 3D-RRAM/SRAM Computing-in-Memory System for Edge Computing

Eng
Artificial intelligence (AI) has made significant strides, with computing-in-memory (CIM) emerging as a key enabler for energy-efficient AI acceleration.
Weiye Tang, Long Nie, Cailian Ma, Hao Wu, Yiyang Yuan, Shuaidi Zhang, Qihao Liu, Feng Zhang   +7 more
doaj   +1 more source