Krishna Muralidharan’s research is geared towards creating novel paradigms for
optimizing energy utilization via the development of high-efficiency,
environmentally-benign, energy storage and energy conversion systems.
His specific focus is on developing advanced thermal management systems
for applications in compressed air energy storage units, thermoelectrics
and thermal interface devices.
important focus of his research is the development of computational
methodologies capable of modeling, predicting and furthering the
fundamental understanding of the structure-property relations of materials.
He has been instrumental in developing the Environmental Dependent
Dynamic Charge (EDD-Q) suite of interatomic potentials, the dynamic
Compound Wavelet Matrix (dCWM) method for multiscale simulations, as well
as contributing his expertise to the PUPIL computational framework.