Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

MOS Capacitor01:25

MOS Capacitor

627
A Metal-Oxide-Semiconductor (MOS) capacitor is a fundamental structure used extensively in semiconductor device technology, particularly in the fabrication of integrated circuits and MOSFETs (metal-oxide-semiconductor field-effect transistors). The MOS capacitor consists of three layers: a metal gate, a dielectric oxide, and a semiconductor substrate.
The metal gate is typically made from highly conductive materials such as aluminum or polysilicon. Beneath the metal gate lies a thin layer of...
627

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Reconfigurable Photoelectric Coaxial Fiber-Based Memristors for Neuromorphic Computing.

ACS nano·2026
Same author

A C57BL/6N mice model of CP/CPPS established by prostate antigen immunization with DPT and BCG co-administration.

Frontiers in immunology·2026
Same author

ASO Visual Abstract: Exploring the Associations and Mechanisms Between Antihypertensive Drugs and Urologic Tumors-Insights from a Mendelian Randomization Study.

Annals of surgical oncology·2026
Same author

ASO Author Reflections: From Blood Pressure Control to Tumor Risk: Genetic Clues Linking Antihypertensive Drug Targets to Urological Tumors.

Annals of surgical oncology·2026
Same author

Ultralow Power Optoelectronic Reconfigurable Hf<sub>0.2</sub>Zr<sub>0.8</sub>O<sub><i>x</i></sub>-Based Antiferroelectric Device for Adaptive Image Recognition.

ACS applied materials & interfaces·2026
Same author

Exploring the Associations and Mechanisms Between Antihypertensive Drugs and Urological Tumors: Insights from a Mendelian Randomization Study.

Annals of surgical oncology·2026

相关实验视频

Updated: May 13, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

7.7K

用于神经形态计算的低功耗memristor:从材料到应用.

Zhipeng Xia1,2, Xiao Sun1,2, Zhenlong Wang1,2

  • 1School of Integrated Circuits, Shandong University, Jinan, 250100, People's Republic of China.

Nano-micro letters
|April 14, 2025
PubMed
概括

这篇评论探讨了用于神经形态计算的低功耗memristor. 它涵盖了先进的存储,逻辑和模拟计算中的设备结构,材料,数组和应用,强调了未来的挑战.

关键词:
数字逻辑门是数字逻辑门.低功率的低功率电源是什么记忆力 记忆力 记忆力多价值存储器多价值存储器神经形态计算是一种神经形态计算.

更多相关视频

A Method for Growing Bio-memristors from Slime Mold
07:46

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

8.9K
In Situ Transmission Electron Microscopy with Biasing and Fabrication of Asymmetric Crossbars Based on Mixed-Phased a-VOx
09:49

In Situ Transmission Electron Microscopy with Biasing and Fabrication of Asymmetric Crossbars Based on Mixed-Phased a-VOx

Published on: May 13, 2020

4.0K

相关实验视频

Last Updated: May 13, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

7.7K
A Method for Growing Bio-memristors from Slime Mold
07:46

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

8.9K
In Situ Transmission Electron Microscopy with Biasing and Fabrication of Asymmetric Crossbars Based on Mixed-Phased a-VOx
09:49

In Situ Transmission Electron Microscopy with Biasing and Fabrication of Asymmetric Crossbars Based on Mixed-Phased a-VOx

Published on: May 13, 2020

4.0K

科学领域:

  • 材料科学 材料科学 材料科学
  • 电气工程 电气工程
  • 计算机科学 计算机科学

背景情况:

  • 记忆器是新兴的存储器设备,具有低功耗神经形态计算的巨大潜力.
  • 它们的独特特性比传统的计算架构提供了优势.

研究的目的:

  • 在神经形态计算的各个方面审查低功耗memristors的应用.
  • 讨论设备概念,材料,数组结构和潜在的应用.

主要方法:

  • 介绍了memristor设备的概念和结构.
  • 讨论功能性材料 (离子传输,相变,磁电阻,铁电).
  • 对1T1R和1S1R交叉阵列和边缘计算记忆器芯片的分析.

主要成果:

  • 记忆器能够实现先进的多值存储,数字逻辑门和模拟神经形态计算.
  • 详细介绍了低功耗memristor的应用,包括它们与边缘计算芯片的集成.

结论:

  • 低功耗的memristors对于神经形态计算的进步至关重要.
  • 需要进一步的研究来克服挑战,并实现基于memristor的神经形态系统的全部潜力.