Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

MOS Capacitor

MOS Capacitor

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...

You might also read

Related Articles

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

Sort by

Same author

Promoting Psychological Resilience Against Academic Burnout: A JD-R Framework Analysis of Self-Compassion as a Mental Health Resource for Diverse Student Populations.

Healthcare (Basel, Switzerland)·2026

Same author

Governing Thermal Transport in Three-Dimensional Electronics.

ACS nano·2026

Same author

Correction: INO80 regulates promoter-associated R-loops to coordinate transcription and maintain genome stability in embryonic stem cells.

Biological research·2026

Same author

Sensorimotor network hyperactivity and impaired psychomotor performance associated with cumulative occupational stress in firefighters.

Brain research bulletin·2026

Same author

Network-level structural alterations distinguish persistent from remitted post-traumatic stress disorder: a morphometric covariance approach.

European journal of psychotraumatology·2026

Same author

Gate dielectric stack design for 2D materials-based electronics.

Nano convergence·2026

Same journal

Enriching Magneto-Optical Functionalities in Iron Garnet Films via Compensation-Driven Magnetic Tuning.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

Quartz-Like Supramolecular Glass Enabled by Host-Guest Size Mismatch.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

Reliable and Reusable All-Solid-State Contact-Type Pre-Lithiation Platform for High-Performance All-Solid-State Batteries.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

Cross-Scale Design of Electrocatalytic Systems for Steering Alcohol Oxidation Toward High-Value-Added Chemicals.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

Synergistic Control of Radiative Decay and Exciton Splitting Dynamics for Efficient Organic Solar Cells Processed by Non-Halogenated Solvent.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

Nitrogen-Incorporated Silicon Dioxide Interlayer Enables Pinhole-Reduced and Robust TOPCon With a High Implied Open-Circuit Voltage over 760 mV.

Advanced materials (Deerfield Beach, Fla.)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 6, 2025

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

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

Published on: March 9, 2019

Crystallinity-Controlled Hexagonal Boron Nitride-Based Memristors for Fully Integrated Reservoir Computing

Wonbae Ahn¹, Sejin Lee¹, Jungyeop Oh¹

¹School of Electrical Engineering, Graduate School of Semiconductor Technology, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea.

Advanced Materials (Deerfield Beach, Fla.)

|December 2, 2024

Summary

This summary is machine-generated.

Researchers developed a new method to synthesize nanocrystalline hexagonal boron nitride (NC h-BN) for memristors. This innovation enables the creation of highly accurate, integrated reservoir computing processors for temporal data inference.

Keywords:

2D materials 3D integration crystallinity control hexagonal boron nitride memristor reservoir computing

More Related Videos

A Method for Growing Bio-memristors from Slime Mold

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

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

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

Published on: May 13, 2020

Related Experiment Videos

Last Updated: Jun 6, 2025

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

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

Published on: March 9, 2019

A Method for Growing Bio-memristors from Slime Mold

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

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

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

Published on: May 13, 2020

Area of Science:

Materials Science
Nanotechnology
Neuroscience

Background:

Memristors utilizing 2D materials (2DMs) show promise for advanced computing.
Traditional 2DM synthesis methods lead to defects and device non-uniformity in memristor arrays.
High synthesis temperatures and mechanical transfer hinder large-area integration of 2DM memristors.

Purpose of the Study:

To develop a novel synthesis method for nanocrystalline 2DMs for memristor applications.
To demonstrate a fully integrated reservoir computing processor using crystallinity-controlled hexagonal boron nitride (h-BN).
To investigate the switching characteristics of NC h-BN and amorphous boron nitride (a-BN) memristors.

Main Methods:

Direct synthesis of crystallinity-controlled hexagonal boron nitride on metal electrodes.
Fabrication of memristors using both nanocrystalline h-BN (NC h-BN) and amorphous boron nitride (a-BN).
Three-dimensional integration of NC h-BN and a-BN memristors to create a reservoir computing processor.

Main Results:

NC h-BN memristors exhibited volatile switching and reliable reservoir dynamics.
a-BN memristors demonstrated nonvolatile switching with linear potentiation/depression.
The integrated 3D processor achieved high accuracy in inferring temporal data.

Conclusions:

Crystallinity-controlled synthesis of h-BN is crucial for uniform memristor arrays.
The developed method enables the creation of efficient, integrated reservoir computing processors.
This approach facilitates the realization of advanced neural network hardware for temporal data processing.