This
study aims to investigate the effect of prestretching on a
graphene’s ballistic limit velocity under impact loading, which
is the maximum impact velocity that graphenes can withstand without
being penetrated by a bullet. Molecular dynamics simulations and machine
learning were employed to analyze the ballistic limit velocity of
graphenes under various prestretching conditions. A machine learning
model was developed by integrating a partial solution into the loss
function to expedite the determination of the ballistic limit velocity.
The physical mechanisms of the prestretching effect under impact loading
were explained based on the stiffness theory of corrugated plates.
The study revealed that uniaxial stretching is superior to equibiaxial
stretching in inducing the prestretching effect. The machine learning
model effectively predicted the ballistic limit velocity of graphene
at different tensions and bullet sizes. When the bullet radius is
small, the ballistic limit velocity exhibits significant fluctuations
with increasing tension, whereas it decreases monotonically with increasing
tension when the bullet radius is large. Although the positive effects
of prestretching diminish with an increase in the number of graphene
layers, prestretching significantly reduces the interlayer spacing
of the graphene Whipple structure. These results provide valuable
insights into the application of graphene in engineering, particularly
in enhancing its ballistic performance. The findings suggest that
prestretching can be an effective engineering manipulation to improve
the impact resistance of graphene-based materials, which can be crucial
for designing more effective protective materials and devices.