Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

MOS Capacitor01:25

MOS Capacitor

631
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...
631
Resting Membrane Potential01:24

Resting Membrane Potential

17.6K
The relative difference in electrical charge, or voltage, between the inside and the outside of a cell membrane, is called the membrane potential. It is generated by differences in permeability of the membrane to various ions and the concentrations of these ions across the membrane.
The Inside of a Neuron is More Negative
The membrane potential of a cell can be measured by inserting a microelectrode into a cell and comparing the charge to a reference electrode in the extracellular fluid. The...
17.6K
The Resting Membrane Potential01:21

The Resting Membrane Potential

127.2K
Overview
127.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Oligo(ethylene glycol)-functionalized polycarbonate lipid nanoparticles for mRNA delivery with attenuated PEG immunogenicity.

Journal of controlled release : official journal of the Controlled Release Society·2026
Same author

Tryptophan-Restricted Intermittent Diet Alleviates Estrogen Deficiency-Induced Osteoporosis via Regulating Coupling Effects of "Gut-Bone" Axis.

International journal of biological sciences·2026
Same author

Coupled hydrological pulse and geochemical buffering controls on acid mine drainage evolution: Insights from typical abandoned pyrite mines in Southern Shaanxi, China.

Environmental research·2026
Same author

EZH2 depletion blocks the proliferation and collagen deposition of keloid fibroblasts via ferroptosis.

Connective tissue research·2026
Same author

Hydroa Vacciniforme: When and How to Suspect It.

Clinical, cosmetic and investigational dermatology·2026
Same author

A coarse-to-fine restoration framework integrating deep semantic inpainting and texture-aware refinement for Jinling school landscapes.

Scientific reports·2026
Same journal

Lasing characteristics and stress-tuning effects in GaN beam microcavities.

Nanoscale·2026
Same journal

Unraveling the synergy of core doping and the motif shell in atomically precise PtAg nanoclusters for CF<sub>3</sub>-ketone alkynylation.

Nanoscale·2026
Same journal

A dual-functional heavy-metal-free quantum dot/TiO<sub>2</sub> hybrid system for simultaneous pollutant degradation and green hydrogen production.

Nanoscale·2026
Same journal

Rational design of spherical NiCoB@rGO nanocomposites for efficient electrochemical energy storage.

Nanoscale·2026
Same journal

Ligand-controlled engineering of Cu-H active sites on Cu<sub>25</sub> hydride nanoclusters for efficient CO<sub>2</sub> electroreduction.

Nanoscale·2026
Same journal

Isostructural Co/Ni-containing banana-shaped polyoxometalates for visible-light-driven hydrogen production.

Nanoscale·2026
See all related articles

Related Experiment Video

Updated: May 15, 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

Quantum dot-based memristors for information processing and artificial intelligence applications.

Dingshu Tian1,2, Chuan Ke1,2, Bai Sun3

  • 1Key Laboratory of Advanced Technologies of Materials, (Ministry of Education), Southwest Jiaotong University, Chengdu, Sichuan 610031, China. cke@swjtu.edu.cn.

Nanoscale
|April 11, 2025
PubMed
Summary
This summary is machine-generated.

Quantum dot memristors offer a powerful, low-power solution for artificial intelligence computing, overcoming limitations of traditional technologies. These advancements promise enhanced cycle stability and reduced energy consumption for future AI applications.

More Related Videos

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping
14:58

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping

Published on: June 3, 2015

14.4K
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

Related Experiment Videos

Last Updated: May 15, 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
Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping
14:58

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping

Published on: June 3, 2015

14.4K
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

Area of Science:

  • Materials Science
  • Computer Engineering
  • Artificial Intelligence

Background:

  • Traditional computing struggles to meet the demands of AI and scientific innovation.
  • Existing memristors face challenges like poor cycle stability, high energy use, and non-uniform conductivity.
  • A new generation of computing technology is urgently needed.

Purpose of the Study:

  • To review the progress of quantum dot memristors.
  • To explore their application in artificial synapses for AI.
  • To identify challenges and future potential.

Main Methods:

  • Review of existing research on quantum dot memristors.
  • Analysis of their integration into artificial synapse simulations.
  • Summary of current development hurdles and future prospects.

Main Results:

  • Quantum dots enhance memristor properties, addressing traditional limitations.
  • Quantum dot memristors show promise for artificial synapse applications.
  • Progress has been made in stability and energy efficiency.

Conclusions:

  • Quantum dot memristors are a viable next-generation computing technology.
  • They offer solutions for AI hardware challenges, including energy consumption and stability.
  • Further research is needed to overcome current development challenges and unlock full potential in AI.