Rational Design of Carbon‐Based Electrocatalysts for H2O2 Production by Machine Learning and Structural Engineering DOI
Rong Ma, Gao‐Feng Han, Li Feng

et al.

Advanced Energy Materials, Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Abstract Electrochemical synthesis of hydrogen peroxide (H 2 O ) via two‐electron oxygen reduction reaction (2e − ORR) represents an economically viable alternative to conventional anthraquinone processes. While noble metal catalysts have dominated this field, carbon‐based materials are emerging as promising alternatives due their low cost, abundant reserves, and tunable properties. This mini‐review summarizes recent advances in computational methods, particularly the integration density functional theory (DFT) with machine learning (ML), accelerate rational design electrocatalysts by enabling rapid screening structure‐training predictions. Meanwhile, optimization strategies systematically investigated, focusing on four key aspects: atomic‐level heterochromatic doping, defect engineering, microenvironment control, morphological design. Despite significant progress achieving high selectivity activity, challenges remain scaling these for industrial applications. Moving H will require multidisciplinary efforts combining advanced situ characterization techniques, modeling, process engineering develop robust suitable diverse operating conditions.

Language: Английский

Modulating Selectivity and Stability of the Direct Seawater Electrolysis for Sustainable Green Hydrogen Production DOI Creative Commons
Dazhi Yao, Chun Liu, Yanzhao Zhang

et al.

Materials Today Catalysis, Journal Year: 2025, Volume and Issue: unknown, P. 100089 - 100089

Published: Feb. 1, 2025

Language: Английский

Citations

1
New insights into the long-range interaction mechanism of nitrogen reduction DOI

Yumeng Cheng,

Wei Chen, Cheng He

et al.

Journal of Energy Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

Citations

0
Rational Design of Carbon‐Based Electrocatalysts for H2O2 Production by Machine Learning and Structural Engineering DOI
Rong Ma, Gao‐Feng Han, Li Feng

et al.

Advanced Energy Materials, Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Abstract Electrochemical synthesis of hydrogen peroxide (H 2 O ) via two‐electron oxygen reduction reaction (2e − ORR) represents an economically viable alternative to conventional anthraquinone processes. While noble metal catalysts have dominated this field, carbon‐based materials are emerging as promising alternatives due their low cost, abundant reserves, and tunable properties. This mini‐review summarizes recent advances in computational methods, particularly the integration density functional theory (DFT) with machine learning (ML), accelerate rational design electrocatalysts by enabling rapid screening structure‐training predictions. Meanwhile, optimization strategies systematically investigated, focusing on four key aspects: atomic‐level heterochromatic doping, defect engineering, microenvironment control, morphological design. Despite significant progress achieving high selectivity activity, challenges remain scaling these for industrial applications. Moving H will require multidisciplinary efforts combining advanced situ characterization techniques, modeling, process engineering develop robust suitable diverse operating conditions.

Language: Английский

Citations

0