Results 71 to 80 of about 2,451 (213)

Silicon Nitride Resistive Memories

Advanced 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, Nikolaos Vasileiadis, Iosif‐Angelos Fyrigos, Emmanouil Stavroulakis, Caroline Bonafos, Pascal Normand, Georgios Ch. Sirakoulis, Panagiotis Dimitrakis   +7 more
wiley   +1 more source

A Fully Integrated System‐on‐Chip Design with Scalable Resistive Random‐Access Memory Tile Design for Analog in‐Memory Computing

Advanced Intelligent Systems, 2022
As the demands of big data applications and deep learning continue to rise, the industry is increasingly looking to artificial intelligence (AI) accelerators.
Fuxi Cai, She-Hwa Yen, Apurva Uppala, Luke Thomas, Tianchi Liu, Peter Fu, Xiaofeng Zhang, Ambrose Low, Deepak Kamalanathan, Joe Hsu, Buvna Ayyagari-Sangamalli   +10 more
doaj   +1 more source

GraphR: Accelerating Graph Processing Using ReRAM [PDF]

2018 IEEE International Symposium on High Performance Computer Architecture (HPCA), 2018
Accepted to HPCA ...
Linghao Song, Youwei Zhuo, Xuehai Qian, Hai Helen Li, Yiran Chen 0001   +4 more
openaire   +2 more sources

The Influence of Residual Ion Drift During Programming of Chip‐Integrated Nanoscale HfO2‐Based Memristive Devices

Advanced Electronic Materials, EarlyView.
1T1R‐arrays combining filamentary‐type memristors and CMOS transistors offer great potential for energy‐efficient analog hardware accelerators. Here, transient SET analysis of nanoscale HfO2 memristors integrated on 180 nm CMOS wafers is discussed.
Oliver Artner, Felix Cüppers, Seokki Son, Yang Chen, Xiaohua Liu, Christopher Bengel, Dennis Nielinger, André Zambanini, Stefan Wiefels, Stephan Menzel, Regina Dittmann, Susanne Hoffmann‐Eifert   +11 more
wiley   +1 more source

Compact Modeling of Volatile‐Switching Electrochemical Metallization Memory Cells by Means of the Electromotive Force

Advanced Intelligent Systems, EarlyView.
A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad, Solomon Amsalu Chekol, Julius Rasbach, Susanne Hoffmann‐Eifert, Stephan Menzel   +4 more
wiley   +1 more source

Demonstration of transfer learning using 14 nm technology analog ReRAM array

Frontiers in Electronics
Analog memory presents a promising solution in the face of the growing demand for energy-efficient artificial intelligence (AI) at the edge. In this study, we demonstrate efficient deep neural network transfer learning utilizing hardware and algorithm co-
Fabia Farlin Athena, Omobayode Fagbohungbe, Nanbo Gong, Malte J. Rasch, Jimmy Penaloza, SoonCheon Seo, Arthur Gasasira, Paul Solomon, Valeria Bragaglia, Steven Consiglio, Hisashi Higuchi, Chanro Park, Kevin Brew, Paul Jamison, Christopher Catano, Iqbal Saraf, Claire Silvestre, Xuefeng Liu, Babar Khan, Nikhil Jain, Steven McDermott, Rick Johnson, I. Estrada-Raygoza, Juntao Li, Tayfun Gokmen, Ning Li, Ruturaj Pujari, Fabio Carta, Hiroyuki Miyazoe, Martin M. Frank, Antonio La Porta, Devi Koty, Qingyun Yang, Robert D. Clark, Kandabara Tapily, Cory Wajda, Aelan Mosden, Jeff Shearer, Andrew Metz, Sean Teehan, Nicole Saulnier, Bert Offrein, Takaaki Tsunomura, Gert Leusink, Vijay Narayanan, Takashi Ando   +45 more
doaj   +1 more source

Opportunities for 2D‐Material‐Based Multifunctional Devices and Systems in Bioinspired Neural Networks

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, Maheswari Sivan, Jieming Pan, Zihang Fang, Jianan Li, Zefeng Xu, Shi Zhao, Quanzhen Wan, Evgeny Zamburg, Aaron Voon‐Yew Thean   +9 more
wiley   +1 more source

Lead‐free inorganic halide perovskite‐based synaptic memory for next generation neuromorphic computing

InfoMat, Volume 8, Issue 6, June 2026.
Lead‐free inorganic halide perovskites enable resistive switching synaptic devices capable of mimicking biological learning and multimodal information processing, offering a promising platform for next‐generation neuromorphic computing and artificial intelligence hardware. Abstract Inorganic halide perovskites (IHPs) have emerged as promising materials
Subhasish Chanda, Deepak Kumar, Iman Biswas, Manisha Sharma, Youngmin Lee, Sejoon Lee, Sanjeev Kumar Sharma, Aniruddha Mondal   +7 more
wiley   +1 more source

Electrochemical Memristive Devices Toward Brain‐Inspired Computing and In‐Memory Communication: Mechanisms, Materials, and Device Engineering

ChemElectroChem, Volume 13, Issue 9, 5 May 2026.
Electrochemical memristive devices, whose resistance is modulated by ion migration and redox reactions, offer a hardware pathway toward brain‐inspired computing. This review summarizes key switching mechanisms—electrochemical metallization (ECM), valence change mechanism (VCM), and thermochemical effects (TCM)—and discusses how materials and device ...
Junyao Xu, Yiwei Sun
wiley   +1 more source

Read margin analysis in an ReRAM crossbar array

, 2016
This paper analyzes effects of design parameters on the read margin of an ReRAM crossbar array. Because ReRAM's crossbar array suffers from small read margin, design parameters must be optimized for large read margin.
Jaehyun Seo, Byungsub Kim, Seo, J., Kim, B.   +3 more
core   +1 more source