Modulation of Hydrogen Evolution Reaction Performance of MXenes by Doped Transition Metals: Comprehensive Exploration of High-Throughput Computing and Machine Learning

Due
to the unique properties of MXenes, the doping of transition
metals can modulate their catalytic properties and make them potential
materials for hydrogen evolution reaction (HER). Nevertheless, the
extensive combinatorial space poses a challenge for rapid screening
of catalysts. To address this issue, we conducted high-throughput
calculations on a series of transition metal atom-doped Ti3CNO2 and Zr2HfCNO2. Furthermore,
the local structure and the corresponding electronic structure changes
are analyzed, focusing on their influence on the HER properties. Furthermore,
site identification features were introduced to train a multisite
prediction model with a final model accuracy of R2 = 0.97 and predicted the trend of hydrogen adsorption
Gibbs free energy (ΔGH*) across a range of MXenes
structures, which were doped with TM atoms. The results show that
Nb, Sc, Rh, W, Ti, and V doping resulted in |ΔGH*| < 0.2 eV for more than 38 M′2M″CNO2, respectively, and they are effective dopant atoms for enhancing
the catalytic ability of M′2M″CNO2. This study not only demonstrates the potential of doped TM atoms
in enhancing the performance of MXenes HER but also highlights the
importance of multisite prediction models in the rapid identification
and development of efficient HER catalysts.