Programmable Pulsed Acidic Water Oxidation for Enhanced H₂O₂ Production.

Area of Science:

• Electrochemistry
• Materials Science
• Catalysis

Background:

• Hydrogen peroxide (H2O2) is a vital chemical with broad medical and industrial uses.
• Efficient electrosynthesis of H2O2 in acidic media via water oxidation reaction (WOR) remains a significant challenge.
• Boron-doped diamond (BDD) is a promising catalyst for electrochemical applications.

Purpose of the Study:

• To develop a novel, optimized method for H2O2 electrosynthesis in acidic conditions.
• To investigate the influence of programmable pulse potential electrolysis (PPE) and machine learning (ML) on H2O2 production.
• To elucidate the mechanism of H2O2 generation on the BDD catalyst.

Main Methods:

• Electrosynthesis of H2O2 using programmable pulse potential electrolysis (PPE) on a Boron-doped diamond (BDD) catalyst.
• Optimization of PPE parameters using machine learning (ML).
• Characterization of the BDD catalyst surface and analysis of reaction intermediates using experimental and Density Functional Theory (DFT) methods.

Main Results:

• Achieved a high Faradaic efficiency (FE) of 64.16% and a production rate of 25.62 µmol cm⁻² min⁻¹ for H2O2.
• Demonstrated a 28.9-fold increase in FE and a 51.8-fold boost in H2O2 yields compared to constant potential electrolysis (CPE).
• Identified that H2O2 generation is influenced by non-Faradaic current and cathode hydrogenation, enhancing surface C-H functional groups.

Conclusions:

• Programmable pulse potential electrolysis (PPE) coupled with ML optimization offers a highly effective strategy for H2O2 electrosynthesis.
• The study reveals a mechanistic pathway involving •OH radical formation for H2O2 production.
• This work highlights the potential of advanced electrochemical techniques and ML for optimizing chemical synthesis.