Transition
Metal and N Doping on AlP Monolayers for
Bifunctional Oxygen Electrocatalysts: Density Functional Theory Study
Assisted by Machine Learning Description
It
is vital to search for highly efficient bifunctional oxygen
evolution/reduction reaction (OER/ORR) electrocatalysts for sustainable
and renewable clean energy. Herein, we propose a single transition-metal
(TM)-based defective AlP system to validate bifunctional oxygen electrocatalysis
by using the density functional theory (DFT) method. We found that
the catalytic activity is enhanced by substituting two P atoms with
two N atoms in the Al vacancy of the TM-anchored AlP monolayer. Specifically,
the overpotential of OER(ORR) in Co- and Ni-based defective AlP systems
is found to be 0.38 (0.25 V) and 0.23 V (0.39 V), respectively, showing
excellent bifunctional catalytic performance. The results are further
presented by establishing the volcano plots and contour maps according
to the scaling relation of the Gibbs free-energy change of *OH, *O,
and *OOH intermediates. The d-band center and the product of the number
of d-orbital electrons and electronegativity of the TM atom are the
ideal descriptors for this system. To investigate the activity origin
of the OER/ORR process, we performed the machine learning (ML) algorithm.
The result indicates that the number of TM-d electrons (Ne), the radius of TM atoms (rd), and the charge transfer of TM atoms (Qe) are the three primary descriptors characterizing the adsorption
behavior. Our results can provide a theoretical guidance for designing
highly efficient bifunctional electrocatalysts and pave a way for
the DFT–ML hybrid method in catalysis research.