  Graphene's intrinsically corrugated and wrinkled topology fundamentally
influences its electronic, mechanical, and chemical properties. Experimental
techniques allow the manipulation of pristine graphene and the controlled
production of defects which allows to control the atomic out-of-plane
fluctuations and, thus, tune graphene's properties. Here, we perform large
scale machine learning-driven molecular dynamics simulations to understand the
impact of defects on the structure of graphene. We find that defects cause
significantly higher corrugation leading to a strongly wrinkled surface. The
magnitude of this structural transformation strongly depends on the defect
concentration and specific type of defect. Analysing the atomic neighborhood of
the defects reveals that the extent of these morphological changes depends on
the preferred geometrical orientation and the interactions between defects.
While our work highlights that defects can strongly affect graphene's
morphology, it also emphasises the differences between distinct types by
linking the global structure to the local environment of the defects.
