Georgia Tech Engineers Simulate Solar Cell Work Using Supercomputers

Published June 22, 2020

By Kimberly Mann Bruch, SDSC Communications

Solar energy has become a popular renewable source of electricity around the world with silicon serving as the primary source due to its efficiency and stability. Because of silicon’s relatively high cost, hybrid organic-inorganic perovskites (HOIPs) have emerged as a lower-cost – and highly efficient – option for solar power, according to a recent study by Georgia Institute of Technology (Georgia Tech) researchers.

The name perovskite refers not only to a specific mineral (CaTiO₃) found in Russia’s Ural Mountains, but also to any compound that shares its structure. A search for stable, efficient, and environmentally safe perovskites has created an active avenue in current materials research, with the new Georgia Tech findings relying on simulations done on Comet at the San Diego Supercomputer Center (SDSC) and Stampede2 at the Texas Advanced Computing Center (TACC).

However, the presence of lead in the most promising perovskite candidates, methylammonium and formamidinium lead halides, has raised concerns. Moreover, these materials have shown to be unstable under certain environmental conditions.

The Georgia Tech researchers worked with colleagues at the Hanoi University of Science and Technology in Vietnam to create simulations that identified four lead-free perovskites as promising candidates for solar cell materials. Two of them have already been synthesized and the other two are recommended for further investigations.

“This research relied on large-scale computations – a first step in our overall plan, which begins with showing simulations of this chemical space of HOIPs,” said Huan Tran, a Georgia Tech materials science and engineering professor and co-author of Lead-free HOIPs for Solar Applications, which was published earlier this year in The Journal of Chemical Physics.

Allocations on Comet and Stampede2 were provided via the National Science Foundation’s Extreme Science and Engineering Discovery Environment (XSEDE) program. “Next, we will use these simulations to collaborate with experimental experts who can synthesize and test the predicted HOIPs – no personal computer can handle this level of computations. Hence the XSEDE supercomputers are a critically important aspect of our project.”

Tran and co-author Vu Ngoc Tuoc, a theoretical physics professor at the Hanoi University of Science and Technology, relied heavily upon Comet and Stampede2 for the large-scale computations that allowed them to conduct their research at a much higher level of detail.

They also relied on the SDSC and TACC support staff to help when needed. “The technical support provided by both groups was simply excellent as they helped us solve our problems very efficiently and promptly,” said Tran. “In the coming era of materials informatics, computational materials data is the most important infrastructure, and I find that Comet, Stampede2, and other XSEDE facilities provide the ideal platform for boosting the development of these areas.”

This research was supported by Vingroup Innovation Foundation under project VINIF.2019.DA03, and XSEDE (TG-DMR170031). The structures of the HOIPs reported in this work are available in the supplementary material and at http://godeepdata.org/.

About SDSC

The San Diego Supercomputer Center (SDSC) is a leader and pioneer in high-performance and data-intensive computing, providing cyberinfrastructure resources, services, and expertise to the national research community, academia, and industry. Located on the UC San Diego campus, SDSC supports hundreds of multidisciplinary programs spanning a wide variety of domains, from astrophysics and earth sciences to disease research and drug discovery. In late 2020 SDSC will launch its newest National Science Foundation-funded supercomputer, Expanse. At over twice the performance of Comet, Expanse supports SDSC’s theme of ‘Computing without Boundaries’ with a data-centric architecture, public cloud integration, and state-of-the art GPUs for incorporating experimental facilities and edge computing.