  Potentials that could accurately describe the irradiation damage processes
are highly desired to figure out the atomic-level response of various
newly-discovered materials under irradiation environments. In this work, we
introduce a deep-learning interatomic potential for monolayer MoS2 by combining
all-electron calculations, an active-learning sampling method and a hybrid
deep-learning model. This potential could not only give an overall good
performance on the predictions of near-equilibrium material properties
including lattice constants, elastic coefficients, energy stress curves, phonon
spectra, defect formation energy and displacement threshold, but also reproduce
the ab initial irradiation damage processes with high quality. Further
irradiation simulations indicate that one single highenergy ion could generate
a large nanopore with a diameter of more than 2 nm, or a series of multiple
nanopores, which is qualitatively verified by the subsequent 500 keV Au+ ion
irradiation experiments. This work provides a promising and feasible approach
to simulate irradiation effects in enormous newly-discovered materials with
unprecedented accuracy.
