The activity origin of two-dimensional MN4-contained periodical macrocyclic structures towards electro-catalytic...

Area of Science:

• Materials Science
• Catalysis
• Computational Chemistry

Background:

• Two-dimensional metal-nitrogen-carbon (2D MN4) macrocycles are promising single-atom catalysts.
• Understanding the influence of the outer coordination environment on the inner MN4 catalytic center is crucial but limited.

Purpose of the Study:

• To computationally unravel the origin of electro-catalytic activity for hydrogen evolution reaction (HER) in 2D MN4/PMCs.
• To identify superior HER electrocatalysts among various 2D MN4/PMCs.
• To establish a universal descriptor for predicting HER catalytic activity.

Main Methods:

• Density Functional Theory (DFT) calculations were employed to evaluate catalytic activity.
• Machine Learning (ML) algorithms were utilized to develop predictive models.
• Hydrogen adsorption free energy (ΔG_H*) was used as the primary indicator for HER activity.

Main Results:

• IrPpor and RhPPpz were identified as superior HER electrocatalysts via DFT calculations.
• A universal descriptor (Φ) was generated by ML, correlating with charge on the metal center (q) and d-band center (ε_d).
• Descriptor Φ was found to be reversely proportional to ΔG_H*, indicating its predictive power.

Conclusions:

• The outer framework of 2D MN4/PMCs significantly influences the catalytic activity of the central MN4 site.
• The developed descriptor Φ provides insights into the design principles for efficient HER electrocatalysts.
• This work offers a computational approach to accelerate the discovery of advanced single-atom catalysts.