Machine-learning-assisted discovery of boron-doped graphene with high work function as an anode material for Li/Na/K-ion batteries

for Li/Na/K-ion batteries compared with that of pristine graphene and other boron-doped graphene. Our work provides an effective way to locate possible high-WF structures in heteroatom-doped systems, which may accelerate future screening of promising adsorbents for alkali metals.