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

990
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...
990

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

Combined resistive switching memory and multi-state operation in terpyridine-based Pd(II) and Fe(III) complexes for neuromorphic applications.

Nanoscale·2026
Same author

Combined optical and electrical control of a low-power consuming (∼fJ) two-terminal organic artificial synapse for associative learning and neuromorphic applications.

Nanoscale·2024
Same author

Spike rate dependent synaptic characteristics in lamellar, multilayered alpha-MoO<sub>3</sub> based two-terminal devices - efficient way to control the synaptic amplification.

RSC advances·2024
Same author

Bio-inspired artificial synapse for neuromorphic computing based on NiO nanoparticle thin film.

Scientific reports·2023
Same author

Room-Temperature Deep-UV Photoluminescence from Low-Dimensional Hexagonal Boron Nitride Prepared Using a Facile Synthesis.

ACS omega·2022
Same author

A Comparative Study of Crystallography and Defect Structure of Corneal Nipple Array in <i>Daphnis nerii</i> Moth and <i>Papilio polytes</i> Butterfly Eye.

ACS omega·2020

相关实验视频

Updated: Sep 17, 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

7.9K

能源效率高的多层存储器使用基于纸张的二级MLGraphene/MoO3 - /MLGraphene记忆器设备,用于模拟突触功能.

Meenu Maria Sunny1, R Thamankar2

  • 1Department of Physics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.

Discover nano
|July 2, 2025
PubMed
概括

研究人员开发了一种新型的人工突触装置,使用三氧化物嵌入在纸上. 这种环保的神经形态计算方法为先进的内存应用提供了多位状态和低能耗.

关键词:
阿拉维拉是一种.能源消耗 能源消耗是指能源的消耗.多层石墨烯 (MLG) 是一种多层石墨烯.多级别的内存多层次的内存.第二阶段的记忆器.

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

9.1K
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

4.2K

相关实验视频

Last Updated: Sep 17, 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

7.9K
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

9.1K
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

4.2K

科学领域:

  • 材料科学 材料科学 材料科学
  • 神经科学是一个神经科学.
  • 计算机工程 计算机工程

背景情况:

  • 神经形态计算旨在模仿人类大脑的效率,超越传统的·诺伊曼架构.
  • 现有的神经形态设备经常面临电力消耗,稳定性和制造复杂性的挑战.

研究的目的:

  • 开发一种新,低功耗,环保的人工突触装置.
  • 探索基于纸张的电子产品在神经形态计算应用中的潜力.

主要方法:

  • 使用三氧化物 (MoO3) 嵌入在纸上花矩阵中的人工突触装置的制造.
  • 使用的多层石墨烯电极 (MLG) 通过纸上笔 (PoP) 方法创建.
  • 对多位状态和活动依赖的突触重量更新进行设备编程的研究.

主要成果:

  • 基于纸质的突触装置在环境条件下表现出多位状态可编程性 (2^n,n=1,2,3,4) 与低能耗 (~pJ).
  • 发现突触重量更新 (增强和抑郁) 是依赖历史的,可以调节的.
  • 强化和抑郁的非线性行为可以使用非相同的脉冲序列来控制.

结论:

  • 基于纸张的MoO3-Aloe vera突触装置代表了神经形态计算的重大进步.
  • 笔在纸上的方法为用于突触和记忆应用的便携式,环保和灵活的电子设备提供了一个有前途的途径.