A method for doping a two-dimensional material based on cluster ion implantation, including selecting a two-dimensional material sample to place same on a substrate; determining the selected implantation parameters by Monte Carlo particle tracing algorithm on the two-dimensional material sample; replacing the two-dimensional material sample, and placing a two-dimensional material thin film, wherein the thickness of the two-dimensional material thin film is 10 nm; selecting a determined implantation parameter to form a cluster beam and acting on a two-dimensional material thin film; changing the implantation parameters to form different cluster beams and acting on the two-dimensional material thin film; performing annealing on the two-dimensional material thin film implanted with cluster ions to repair the damage caused by implantation. The method is applicable to two-dimensional semiconductor materials by using ion clusters for implantation such that damage to the crystal lattice by the ion implantation is reduced.

In one embodiment, the disclosure relates to using artificial intelligence (AI) to implement automatic beam current density distribution tuning by obtaining measurements from stationary beam current measurement devices synchronously with the motion of a scanned ion beam to predict the beam tuning settings which will produce a desired beam current density profile. An exemplary method according to the disclosed embodiments include the steps of generating an ion beam as a function of an ion source; scanning the spot ion beam; obtaining signals from a plurality of stationary sensors; synchronizing the beam current measurements with the scanning of the beam to produce an input waveform; predicting the beam tuning controls that will produce the desired beam current density profile; and applying the predicted settings to the beam control system and validating that the beam current density profile matches the desired profile within a specified limit.