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

Electrodeposition

Electrodeposition

Electrodeposition is a technique used to separate an analyte from interferents by electrochemical processes. Here, the analyte is a metal ion that can be deposited on an electrode immersed in the sample solution. The electrochemical setup consists of an anode and a cathode. When an electric current is applied to the setup, oxidation occurs at the anode. At the cathode, which consists of a large metal surface, metal ions undergo reduction and deposit onto the surface.
Electrodeposition can...

You might also read

Related Articles

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

Sort by

Same author

Roll-to-Roll Scalable Manufacturing of Nanoporous Separators for High-Safety Lithium-Ion Batteries.

ACS nano·2026

Same author

Multiscale Design Strategies for Fast-Charging Graphite Anodes in Lithium-Ion Batteries.

Small (Weinheim an der Bergstrasse, Germany)·2026

Same author

Decoding polarity gradient enabled ultra-high lithium ion conduction.

National science review·2026

Same author

Quinone-Imine Enhanced PVA Binder: A Universal Strategy for High-Loading Electrodes With Low Binder Content in Li/Na-Ion Batteries.

Small (Weinheim an der Bergstrasse, Germany)·2025

Same author

Design Rules for Selecting Suitable Weakly Solvating Electrolytes for Lithium Metal Batteries.

The journal of physical chemistry letters·2025

Same author

Three-Dimensional Covalent Organic Framework for Efficient Hydrogen Storage through Polarization-Wall Engineering.

Nano letters·2025

Same journal

Neural Regulation of Cardiac Arrhythmias: From the Brain-Heart Axis to Emerging Precision Therapies.

Research (Washington, D.C.)·2026

Same journal

N<sup>6</sup>-Methyladenosine on Key Messenger RNAs Governs Reproductive Development and Metabolic Adaptation in Human Blood Fluke.

Research (Washington, D.C.)·2026

Same journal

Additive-Free Contact-Electro-Catalysis/Vacuum Ultraviolet System for Rapid Mitigation of Antimicrobial-Resistance-Associated Contaminants in Water.

Research (Washington, D.C.)·2026

Same journal

Predicting 1-Year Renal Outcomes in Patients with Diabetic Kidney Disease in CKD Stages 3 to 4: A Multimodal Machine Learning Approach Fusing Clinical Composites and Pathology Images.

Research (Washington, D.C.)·2026

Same journal

Antioxidant Nanozymes: From Rational Design to Biomedical Applications.

Research (Washington, D.C.)·2026

Same journal

Quantum-Inspired Fast Algorithm and Circuit Realization for Constrained Combinatorial Optimization Problem.

Research (Washington, D.C.)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 13, 2025

Characterization of Electrode Materials for Lithium Ion and Sodium Ion Batteries Using Synchrotron Radiation Techniques

Characterization of Electrode Materials for Lithium Ion and Sodium Ion Batteries Using Synchrotron Radiation Techniques

Published on: November 11, 2013

Machine Learning for Selecting High-Energy Phosphate Cathode Materials.

Yongchun Dang¹, Zechen Li², Yongchao Yu¹

¹National Engineering Research Center of Electric Vehicles, Beijing Co-innovation Centre for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China.

Research (Washington, D.C.)

|July 30, 2025

Summary

This summary is machine-generated.

Machine learning identified key properties for high-energy-density sodium-ion battery cathodes. Researchers synthesized a novel material, Na3Mn0.5V0.5Ti0.5Zr0.5(PO4)3, demonstrating superior performance.

More Related Videos

Construction and Testing of Coin Cells of Lithium Ion Batteries

Construction and Testing of Coin Cells of Lithium Ion Batteries

Published on: August 2, 2012

Author Spotlight: Design and Evaluation of Au-Electroplated Carbon Fiber Cloth Electrodes for Hydrogen Peroxide Fuel Cells

Author Spotlight: Design and Evaluation of Au-Electroplated Carbon Fiber Cloth Electrodes for Hydrogen Peroxide Fuel Cells

Published on: October 20, 2023

Related Experiment Videos

Last Updated: Sep 13, 2025

Characterization of Electrode Materials for Lithium Ion and Sodium Ion Batteries Using Synchrotron Radiation Techniques

Characterization of Electrode Materials for Lithium Ion and Sodium Ion Batteries Using Synchrotron Radiation Techniques

Published on: November 11, 2013

Construction and Testing of Coin Cells of Lithium Ion Batteries

Construction and Testing of Coin Cells of Lithium Ion Batteries

Published on: August 2, 2012

Author Spotlight: Design and Evaluation of Au-Electroplated Carbon Fiber Cloth Electrodes for Hydrogen Peroxide Fuel Cells

Author Spotlight: Design and Evaluation of Au-Electroplated Carbon Fiber Cloth Electrodes for Hydrogen Peroxide Fuel Cells

Published on: October 20, 2023

Area of Science:

Materials Science
Electrochemistry
Computational Chemistry

Background:

Limited energy density in cathode materials hinders sodium-ion battery adoption.
Understanding atomic and crystalline influences on energy density is crucial for material design.

Purpose of the Study:

To develop a machine learning approach for identifying high-energy-density cathode materials.
To accelerate the rational design of advanced sodium-ion battery materials.

Main Methods:

Machine learning model predicting cathode material properties.
Identification of critical factors: entropy, electronegativity, molecular mass, electron affinity, and ionic radius.
Sol-gel synthesis of Na3Mn0.5V0.5Ti0.5Zr0.5(PO4)3 (NMVTZP) electrodes.

Main Results:

The synthesized NMVTZP electrodes achieved a reversible specific capacity of 148.27 mAh g-1 at 0.1-C.
Demonstrated an average operating voltage of 3.14 V and an energy density of 465 Wh kg-1.
Exhibited excellent rate capability, retaining 90.20 mAh g-1 at 5-C.

Conclusions:

Machine learning effectively identifies promising cathode materials for sodium-ion batteries.
The novel NMVTZP material shows significant potential for high-performance energy storage.
This approach can accelerate the development of next-generation sodium-ion battery technologies.