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Atoms and molecules interact through bonds (or forces): intramolecular and intermolecular. The forces are electrostatic as they arise from interactions (attractive or repulsive) between charged species (permanent, partial, or temporary charges) and exist with varying strengths between ions, polar, nonpolar, and neutral molecules. The different types of intermolecular forces are ion–dipole, dipole–dipole, hydrogen bonds, and dispersion; among these, dipole–dipole, hydrogen...
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Controlled-potential coulometry, also known as potentiostatic coulometry, employs a three-electrode system in which the working electrode's potential is precisely regulated using a potentiostat. Platinum working electrodes are utilized for positive potentials, while mercury pool electrodes are favored for extremely negative potentials. The platinum counter electrode is separated from the analyte using a membrane or salt bridge to avoid interference in the analysis.
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The ionic association is the association of oppositely charged ions in an electrolyte solution to form ion pairs. Bjerrum defined ion pairs as two oppositely charged ions whose electrostatic attraction exceeds the thermal energy of the system, typically expressed as 2kT. Electrostatic attraction depends on ionic charge, separation distance, and the dielectric constant of the medium. Thermal energy, represented by kT, reflects the tendency of ions to move independently due to molecular motion.
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Constant-Potential MD with Neural Network Potentials Reveals Cation Effects on CO2 Reduction at Au-Water Interfaces.

Letian Chen1, Yun Tian2, Xu Hu1

  • 1School of Materials Science and Engineering, Institute of New Energy Material Chemistry, Renewable Energy Conversion and Storage Center (ReCast), Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education), Nankai University, Tianjin 300350, China.

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Summary

This study introduces a new simulation framework for real-time, atomic-scale insights into electrochemical reactions. It reveals how alkali metal cations influence CO2 adsorption and suppress hydrogen evolution, advancing electrochemistry research.

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constant potential simulationelectrified solid−liquid interfaceelectrocatalysisneural network potential

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Area of Science:

  • Computational Chemistry
  • Electrochemistry
  • Materials Science

Background:

  • Studying dynamic changes at electrified solid-liquid interfaces during electrochemical reactions is crucial.
  • Existing methods struggle to capture these dynamics with high temporal resolution over long timescales.

Purpose of the Study:

  • To develop a computational framework for simulating electrochemical reactions with atomic precision.
  • To gain real-time insights into the evolution of electrified interfaces.
  • To elucidate the role of specific ions in reaction mechanisms.

Main Methods:

  • Developed a constant potential reactor framework.
  • Integrated an enhanced-sampling active learning protocol.
  • Utilized scalable neural network potentials trained on density functional theory (DFT) computations.
  • Employed an explicit-implicit hybrid solvent model.

Main Results:

  • Achieved ab initio-accurate simulations of electrochemical reactions.
  • Provided real-time, atomic-scale insights into interfacial evolution.
  • Uncovered the role of alkali metal cations in promoting CO2 adsorption.
  • Demonstrated suppression of the hydrogen evolution reaction by alkali metal cations.

Conclusions:

  • The framework bridges the gap between experimental and computational electrochemistry.
  • It offers a powerful tool for studying interfacial structure and reactivity.
  • Provides mechanistic insights reconciling prior experimental observations and clarifying ambiguities in electrochemistry.