UTEP Awarded $1.3M from DoE to Develop Materials Simulation Software

A pair of University of Texas at El Paso physics professors recently received a $1.3 million grant from the U.S. Department of Energy’s (DOE) Office of Science.

The grant for Tunna Baruah, Ph.D., and Rajendra Zope, Ph.D., both associate professors in the Department of Physics, is part of a nearly $5 million award that is divided among several universities to design computational models that can test the effectiveness of a variety of materials. A key portion of the software design will occur at UTEP.

Robert Kirken, Ph.D., dean of UTEP’s College of Science, said the grant is validation of the important work being done by the Department of Physics.

“Our computational physics is being recognized by one of the toughest agencies to get funded by,” Kirken said. “This is a grant that was awarded based on the merits of the science, competing against the best programs in the country. Our receipt of $1.3 million, basically a quarter of the total amount, is due to the fact that Dr. Baruah’s group is providing key research for that program.”

When completed, the software will be able to run a simulation model to predict how efficient a given material would be for various applications, including being able to store a charge, energy or data. It also would predict how materials would be able to absorb pollutants and other materials. This could result in major cost savings, as these materials would no longer have to be manufactured and tested.

“At the core of the project is this – you can screen materials pretty quickly, computationally,” Baruah said.

Zope added that any advancement in the method to use existing computational resources to more accurately predict system properties and system behaviors will be transformative.

“The method requires approximation,” Zope said. “You can’t do the exact quantum mechanical calculation for any system that has more than one electron. So, one has to use approximations. This project is about overcoming the limitations of those approximations. Any improvement in the theory, in terms of its predictive capability, is going to make a huge impact on the way these approaches are currently used.”