Tailoring unique neural-network-type carbon nanofibers inserted in CoP/NC polyhedra for robust hydrogen evolution...

Area of Science:

• Materials Science
• Electrochemistry
• Catalysis

Background:

• Three-dimensional (3D) catalysts are crucial for advancing the hydrogen evolution reaction (HER).
• Significant challenges persist in developing innovative structures and enhancing the performance of HER catalysts.

Purpose of the Study:

• To design and synthesize a unique 3D cross-linked neural network-like cobalt phosphide (CoP)-based composite catalyst.
• To evaluate the catalytic activity and stability of the novel material for the hydrogen evolution reaction.

Main Methods:

• Fabrication of a 3D catalyst (3-D CNF@CoP/NC) using bacterial cellulose (BC)-wired ZIF-67 polyhedra.
• Utilized high-temperature carbonization and subsequent phosphorization.
• Characterized the catalyst's structure and electrochemical performance in acidic and alkaline media.

Main Results:

• The integrated catalyst exhibits a neural network-like structure with CoP/NC polyhedra as 'neurons' and carbon nanofibers (CNFs) as 'axons'.
• Achieved low overpotentials of 64.5 mV (0.5 M H2SO4) and 105.6 mV (1 M KOH) at 10 mA cm-2.
• Demonstrated excellent stability with negligible current change after 80 hours of chronoamperometric measurement and 4000 CV cycles.

Conclusions:

• The developed 3D CNF@CoP/NC catalyst offers high performance for the hydrogen evolution reaction.
• The study presents a novel approach for engineering 3D interconnected hierarchical porous networks for efficient catalysis.
• This work paves the way for advanced catalysts with ultrafast charge transfer and mass transport properties.