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Related Concept Videos

Standard Electrode Potentials03:02

Standard Electrode Potentials

On comparing the reactivity of silver and lead, it is observed that the two ionic species, Ag+ (aq) and Pb2+ (aq), show a difference in their redox reactivity towards copper: the silver ion undergoes spontaneous reduction, while the lead ion does not. This relative redox activity can be easily quantified in electrochemical cells by a property called cell potential. This property is commonly known as cell voltage in electrochemistry, and it is a measure of the energy which accompanies the charge...
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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+...
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Redox Reactions

Oxidation-reduction or redox reactions involve the transfer of electrons from one molecule or atom to another. When an atom gains an electron, another atom must lose an electron, meaning oxidation and reduction must occur together. Since the redox occurs in pairs, the atom that gets oxidized is also called the reducing agent or reductant, and the atom that is reduced is also called the oxidizing agent or oxidant. A straightforward way to remember the definitions of oxidation and reduction is...
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Redox reactions are vital biochemical processes that underpin energy metabolism in cells. These reactions involve the transfer of electrons between molecules, occurring in tandem as oxidation and reduction. Oxidation refers to the loss of electrons, while reduction denotes their gain. This coupling ensures the seamless flow of electrons through metabolic pathways. For example, in bacterial metabolism, glucose undergoes oxidation to carbon dioxide, while oxygen is simultaneously reduced to...
Redox Equilibria: Overview01:23

Redox Equilibria: Overview

A reduction-oxidation reaction is commonly called a redox reaction. In a redox reaction, electrons are transferred from one species to another rather than being shared between or among atoms. The reducing agent or reductant is the species that loses electrons and gets oxidized in the process. The species that gains electrons and gets reduced in the process is the oxidizing agent or oxidant. Redox reactions are represented as two separate equations called half-reactions, where one equation...
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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...

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  3. Benchmarking Foundation Potentials Against Quantum Chemistry Methods For Predicting Molecular Redox Potentials.
  1. Home
  3. Benchmarking Foundation Potentials Against Quantum Chemistry Methods For Predicting Molecular Redox Potentials.

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Using Cyclic Voltammetry, UV-Vis-NIR, and EPR Spectroelectrochemistry to Analyze Organic Compounds
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Published on: October 18, 2018

Benchmarking Foundation Potentials against Quantum Chemistry Methods for Predicting Molecular Redox Potentials.

Yicheng Chen1, Lixue Cheng2, Yan Jing1

  • 1Department of Materials Science and Engineering, National University of Singapore, Singapore 117575, Singapore.

Precision Chemistry
|June 1, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Machine learning potentials accurately predict proton-coupled electron transfer (PCET) redox potentials, but struggle with electron transfer (ET) reactions. A hybrid workflow combining machine learning and density functional theory (DFT) offers a scalable solution for sustainable chemistry screening.

Keywords:
carbon capturehigh-throughput screeningmachine learning interatomic potentialproton-coupled electron transferredox potential

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Area of Science:

  • Computational chemistry
  • Materials science
  • Sustainable chemistry

Background:

  • High-throughput virtual screening is crucial for identifying molecules for sustainable applications like electrochemical carbon capture.
  • Accurate quantum chemistry calculations, essential for this process, are computationally expensive.
  • Machine learning foundation potentials (FPs) offer a computationally efficient alternative to density functional theory (DFT).

Purpose of the Study:

  • To benchmark MACE-OMol-0 and UMA FPs against DFT functionals for predicting molecular redox potentials in electron transfer (ET) and proton-coupled electron transfer (PCET) reactions.
  • To identify limitations of FPs in predicting redox potentials, particularly for ET reactions.
  • To propose an optimized hybrid workflow for accelerating virtual screening in sustainable chemistry.

Main Methods:

  • Benchmarking MACE-OMol-0 and UMA FPs against DFT functionals.
  • Evaluating FP accuracy for ET and PCET reactions using experimental molecular redox potentials.
  • Developing and testing a hybrid workflow involving FPs for geometry optimization and DFT for energy refinement.

Main Results:

  • FPs demonstrated exceptional accuracy for PCET processes, comparable to the target DFT method.
  • FP performance decreased for ET reactions, especially multielectron transfers involving underrepresented reactive ions.
  • The proposed hybrid workflow showed robust and scalable performance for accelerating high-throughput virtual screening.

Conclusions:

  • While FPs show promise, their accuracy for ET reactions is limited by training data representation.
  • A hybrid approach combining FPs and DFT provides a pragmatic and efficient strategy for sustainable chemistry applications.
  • This workflow enhances the scalability and robustness of virtual screening for identifying redox-active molecules.