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Related Concept Videos

Voltammetric Techniques: Cyclic Voltammetry01:10

Voltammetric Techniques: Cyclic Voltammetry

356
Cyclic voltammetry (CV) is an electrochemical technique used to investigate the redox properties of a chemical species. It involves measuring the current response of an electrochemical cell as a function of the applied potential. The setup for cyclic voltammetry typically consists of a working electrode, a reference electrode, and a counter electrode—all immersed in an electrolyte solution. The working electrode is where the redox reaction of interest occurs, while the reference electrode...
356
Voltammetry: Overview01:20

Voltammetry: Overview

1.1K
Voltammetry is an electroanalytical technique in which the current flowing through an electrochemical cell is measured as a function of applied potential, typically under conditions of concentration polarization. The technique provides valuable information about redox-active species, and the current response is plotted as a voltammogram.
A voltammetric cell uses three electrodes: a working electrode, a reference electrode, and an auxiliary electrode. The redox reactions occur in the working...
1.1K
Voltammograms: Overview01:16

Voltammograms: Overview

150
Voltammograms are current plots as a function of applied potential, offering insights into electrochemical systems. The shape of a voltammogram depends on how the current is measured and whether convection (heat transfer by fluid movement) is present or absent.
Shapes of Voltammograms
150
Voltammetry: Factors Affecting Measurements01:21

Voltammetry: Factors Affecting Measurements

124
A current produced due to the redox reactions of the analyte at the working and auxiliary electrodes is called a faradaic current. The reaction can be divided into two types. The current generated due to the reduction of the analyte is called cathodic current, and it carries a positive charge. In contrast, the current produced by analyte oxidation is known as an anodic current, and it has a negative charge. The applied potential at the working electrode determines the faradaic current flow, and...
124
Ladder Diagrams: Redox Equilibria01:30

Ladder Diagrams: Redox Equilibria

420
Ladder diagrams are useful tools for understanding redox equilibrium reactions, especially the effects of concentration changes on the electrochemical potential of the reaction. The vertical axis in the redox ladder diagrams represents the electrochemical potential, E. The area of predominance is demarcated using the Nernst equation.
Consider the Fe3+/Fe2+ half-reaction, which has a standard-state potential of +0.771 V. At potentials more positive than +0.771 V, Fe3+ predominates, whereas Fe2+...
420
Redox Titration: Overview01:21

Redox Titration: Overview

2.0K
Redox titration is a chemical analysis technique used to determine the concentration of an unknown substance by measuring the electron transfer in a redox (reduction-oxidation) reaction. The process involves gradually adding a titrant with a known concentration of an oxidizing or reducing agent, to the analyte, the solution with an unknown concentration, until reaching the endpoint, which indicates the completion of the reaction between the two substances. Ensuring the analyte is in a single...
2.0K

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Related Experiment Video

Updated: May 30, 2025

Using Cyclic Voltammetry, UV-Vis-NIR, and EPR Spectroelectrochemistry to Analyze Organic Compounds
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Redox-Detecting Deep Learning for Mechanism Discernment in Cyclic Voltammograms of Multiple Redox Events.

Benjamin B Hoar1, Weitong Zhang2, Yuanzhou Chen2

  • 1Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, California 90095, United States.

ACS Electrochemistry
|January 29, 2025
PubMed
Summary

A new deep-learning model, EchemNet, automates the detection and classification of electrochemical mechanisms in cyclic voltammetry data. This AI approach enhances accuracy and efficiency for researchers in electrochemistry.

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Area of Science:

  • Electrochemistry
  • Computational Chemistry
  • Machine Learning

Background:

  • Cyclic voltammetry is crucial for electrochemical analysis, but mechanism assignment is often subjective.
  • Automated methods are needed to improve the accuracy and efficiency of analyzing complex electrochemical data.

Purpose of the Study:

  • To develop a deep-learning (DL) model for automated detection and classification of electrochemical mechanisms in cyclic voltammograms.
  • To introduce EchemNet, a custom DL architecture designed for analyzing multi-redox event systems.

Main Methods:

  • A novel deep-learning architecture, EchemNet, was custom-designed for electrochemical data analysis.
  • The model was trained and tested on simulated cyclic voltammetry data with known electrochemical mechanisms.

Main Results:

  • EchemNet achieved over 96% detection rate for electrochemical events in simulated data.
  • The model demonstrated up to 97.2% accuracy in classifying redox events across 8 known mechanisms.

Conclusions:

  • The developed DL model proves the feasibility of automated redox-event detection and electrochemical mechanism classification with minimal prior knowledge.
  • EchemNet can significantly augment researcher productivity and contribute to autonomous electrochemistry laboratories.