  Ab initio molecular dynamics (AIMD) based on density functional theory (DFT)
has become a workhorse for studying the structure, dynamics, and reactions in
condensed matter systems. Currently, AIMD simulations are primarily carried out
at the level of generalized gradient approximation (GGA), which is at the 2nd
rung of DFT-functionals in terms of accuracy. Hybrid DFT functionals which form
the 4th rung in the accuracy ladder, are not commonly used in AIMD simulations
as the computational cost involved is $100$ times or higher. To facilitate AIMD
simulations with hybrid functionals, we propose here an approach that could
speed up the calculations by ~30 times or more for systems with a few hundred
of atoms. We demonstrate that, by achieving this significant speed up and
making the compute time of hybrid functional based AIMD simulations at par with
that of GGA functionals, we are able to study several complex condensed matter
systems and model chemical reactions in solution with hybrid functionals that
were earlier unthinkable to be performed.
