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

Metal-Semiconductor Junctions01:24

Metal-Semiconductor Junctions

292
The contact of metal and semiconductor can lead to the formation of a junction with either Schottky or Ohmic behavior.
Schottky Barriers
Schottky barriers arise when a metal with a work function (Φm) contacts a semiconductor with a different work function (Φs). Initially, electrons transfer until the Fermi levels of the metal and semiconductor align at equilibrium. For instance, if Φm > Φs, the semiconductor Fermi level is higher than the metal's before contact. The...
292
Biasing of Metal-Semiconductor Junctions01:27

Biasing of Metal-Semiconductor Junctions

212
Biasing metal-semiconductor junctions involves applying a voltage across the junction. Specifically, the metal is connected to a voltage source, while the semiconductor is grounded. This technique is essential for controlling the direction and magnitude of current flow in electronic devices, including diodes, transistors, and photovoltaic cells.
In Schottky junctions, where the semiconductor is n-type, applying a positive voltage to the metal relative to the semiconductor reduces its Fermi...
212
Fermi Level Dynamics01:12

Fermi Level Dynamics

221
The vacuum level denotes the energy threshold required for an electron to escape from a material surface. It is usually positioned above the conduction band of a semiconductor and acts as a benchmark for comparing electron energies within various materials.
Electron affinity in semiconductors refers to the energy gap between the minimum of its conduction band and the vacuum level and it is a critical parameter in determining how easily a semiconductor can accept additional electrons.
The work...
221

You might also read

Related Articles

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

Sort by
Same author

Mercury (II) Ion Sensing Through in Situ Synthesis of Gold Nanoparticles.

ACS applied nano materials·2026
Same author

mRNA lipid nanoparticle cancer vaccine platform delivering multiple STING activators for enhanced antitumor activity.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Large-area two-dimensional MoO<sub>3</sub> as a high-κ dielectric for van der Waals integration.

Nature communications·2026
Same author

Quantum tunnelling and leakage current across two-dimensional materials.

Nature materials·2026
Same author

Case Report: Left ventricular hemorrhage associated with early neonatal mortality in multi-gene engineered cloned pigs.

Frontiers in veterinary science·2026
Same author

Sub-femtosecond figure-of-merit millimeter-wave switches via solution-processed MoS<sub>2</sub> for 6G radio-frequency front-ends.

Nature communications·2026

Related Experiment Video

Updated: Jun 4, 2025

A Fabrication and Measurement Method for a Flexible Ferroelectric Element Based on Van Der Waals Heteroepitaxy
10:40

A Fabrication and Measurement Method for a Flexible Ferroelectric Element Based on Van Der Waals Heteroepitaxy

Published on: April 8, 2018

8.2K

Enhanced Synaptic Memory Window and Linearity in Planar In2Se3 Ferroelectric Junctions.

Yu-Rim Jeon1, Dongyoon Kim2, Chandan Biswas1

  • 1Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, 78712, USA.

Advanced Materials (Deerfield Beach, Fla.)
|December 21, 2024
PubMed
Summary

This study introduces advanced 2D Indium Selenide (In2Se3) ferroelectric junctions for neuromorphic computing. These junctions achieve a significantly enhanced memory window and on/off ratio, enabling efficient synaptic operations with low power consumption.

Keywords:
2D vdW materialCNNMNISTferroelectric tunneling junctionneuromorphic computing systemsynaptic deviceα‐In2Se3

More Related Videos

Measuring Magnetically-Tuned Ferroelectric Polarization in Liquid Crystals
07:03

Measuring Magnetically-Tuned Ferroelectric Polarization in Liquid Crystals

Published on: August 15, 2018

8.7K
Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

12.8K

Related Experiment Videos

Last Updated: Jun 4, 2025

A Fabrication and Measurement Method for a Flexible Ferroelectric Element Based on Van Der Waals Heteroepitaxy
10:40

A Fabrication and Measurement Method for a Flexible Ferroelectric Element Based on Van Der Waals Heteroepitaxy

Published on: April 8, 2018

8.2K
Measuring Magnetically-Tuned Ferroelectric Polarization in Liquid Crystals
07:03

Measuring Magnetically-Tuned Ferroelectric Polarization in Liquid Crystals

Published on: August 15, 2018

8.7K
Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

12.8K

Area of Science:

  • Materials Science
  • Nanotechnology
  • Neuromorphic Engineering

Background:

  • Neuromorphic computing utilizes synaptic memristors for low-power, adaptive systems.
  • Current 2D ferroelectric synaptic devices face limitations in operational voltage memory window and on/off current ratio.
  • These limitations hinder the practical application of advanced computing technologies.

Purpose of the Study:

  • To develop high-performance 2D ferroelectric synaptic devices for neuromorphic computing.
  • To overcome the limitations of existing memristor devices in terms of voltage memory window and on/off ratio.
  • To demonstrate the potential of 2D In2Se3 ferroelectric junctions for efficient synaptic operations.

Main Methods:

  • Fabrication of planar memristor devices using 2D In2Se3 ferroelectric junctions.
  • Integration of a 3 nm SiO2 interface layer between alpha-In2Se3 and Au electrodes.
  • Characterization of device performance, including voltage memory window, on/off current ratio, and power consumption.
  • Emulation of synaptic plasticity (LTP/LTD) using electrical pulses.
  • On-chip training of single-layer perceptron (SLP) and convolutional neural network (CNN) models.

Main Results:

  • Achieved a record voltage memory window of 16 V (±8 V) and an on/off current ratio of 10^8.
  • Demonstrated ultra-low power consumption of 10^-5 W in the on state.
  • Successfully mimicked synaptic plasticity with nonlinearity factors of 1.25 for LTP and -0.25 for LTD.
  • Attained high on-chip training accuracy of up to 90% for SLP and CNN models.
  • The SiO2 interface significantly boosted device performance, outperforming existing 2D ferroelectric junctions.

Conclusions:

  • The developed 2D In2Se3 ferroelectric junction demonstrates exceptional performance for neuromorphic computing applications.
  • The device offers a promising solution for ultra-low power consumption and high-efficiency synaptic operations.
  • The enhanced synaptic device paves the way for next-generation intelligent computing systems.