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Understanding pH effects in electrocatalysis requires advanced modeling. A hierarchical model integrating microkinetics, double-layer charging, and mass transport accurately explains formic acid oxidation reaction (FAOR) pH behavior.

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Area of Science:

  • Electrocatalysis
  • Physical Chemistry
  • Chemical Engineering

Background:

  • Solution pH significantly influences electrocatalytic reactions by altering reactant concentrations and the local reaction environment (LRE).
  • Disentangling pH effects is complex due to interwoven factors like mass transport and electric double layer (EDL) phenomena.
  • Accurate interpretation of pH effects necessitates sophisticated physical modeling.

Purpose of the Study:

  • To develop and apply a hierarchical model for understanding pH effects in the formic acid oxidation reaction (FAOR).
  • To investigate the interplay between microkinetics, EDL charging, and mass transport in determining FAOR activity.
  • To elucidate the limitations of simpler models in predicting experimental observations.

Main Methods:

  • Development of a hierarchical model integrating microkinetics, EDL charging, and macroscopic mass transport.
  • Simulation of the formic acid oxidation reaction (FAOR) across a range of pH values.
  • Comparison of model predictions with experimental data in various electrolyte solutions.

Main Results:

  • Intrinsic pH effects predict a bell-shaped activity curve, inconsistent with experimental data.
  • Incorporating mass transport qualitatively reproduces the experimentally observed trapezoidal shape.
  • Quantitative agreement requires accounting for EDL effects beyond standard correlations, highlighting the impact on adsorbed intermediate energetics.
  • Anion adsorption effects were discussed for phosphate and chloride solutions.

Conclusions:

  • A comprehensive hierarchical model is crucial for accurately interpreting pH effects in electrocatalysis.
  • EDL effects and specific ion adsorption significantly modulate electrocatalytic performance.
  • This work emphasizes the necessity of considering multiple coupled factors for a complete understanding of pH-dependent reactions.