Data science helps engineers discover new materials for solar cells and LEDs

Engineers at the University of California at San Diego have developed a high-throughput computing method to design new materials for next-generation solar cells and LEDs. Their approach generated 13 new candidate materials for solar cells and 23 new candidates for LEDs. Calculations predicted that these materials, called hybrid halide semiconductors, would be stable and have excellent optoelectronic properties.

The team released its findings on May 22, 2019 in the newspaper Energy and environmental science.

Hybrid halide semiconductors are materials consisting of an inorganic structure in which organic cations are housed. They have unique properties that are not found in organic or inorganic materials.

A subclass of these materials, called hybrid halide perovskites, has attracted a lot of attention as promising materials for solar cells and next-generation LED devices because of their exceptional optoelectronic properties and their cost. inexpensive manufacturing. However, hybrid perovskites are not very stable and contain lead, making them unsuitable for commercial devices.

In search of alternatives to perovskites, a team of researchers led by Kesong Yang, professor of nanoengineering at the Faculty of Engineering at the University of San Diego Jacobs, used computer tools, techniques of digging and filtering data to discover new halide hybrid materials, beyond stable and stable perovskites -free. "We are looking for structures in perovskite to find a new space for the design of hybrid semiconductor materials for optoelectronics." Yang said.

Yang's team began by browsing the two largest databases of quantum materials, AFLOW and The Materials Project, and analyzing all compounds whose chemical composition was similar to that of the halide perovskites. Next, they extracted 24 prototype structures to be used as models to generate hybrid organic-inorganic material structures.

Then, they performed high-throughput quantum mechanics calculations on prototype structures to form a complete repository of quantum materials containing 4,507 hypothetical hybrid halide compounds. Using efficient data extraction and filtering algorithms, Yang's team quickly identified 13 candidates for solar cell materials and 23 candidates for LEDs among all hypothetical compounds.

"A high throughput study of organic-inorganic hybrid materials is not trivial," Yang said. It took several years to develop a comprehensive software framework with algorithms for data generation, data mining, and data filtering for hybrid halide materials. It also took a lot of effort for his team to make the software framework work perfectly with the software used for high-throughput calculations.

"Compared to other computer design approaches, we have explored a vast structural and chemical space to identify new semiconductor halide materials," said Yuheng Li, a Ph.D. in nanoengineering . candidate in Yang's group and the first author of the study. This work could also inspire a new wave of experimental testing to validate the predicted materials by calculation, Li said.

In the future, Yang and his team are using their broadband approach to discover new materials for solar cells and LEDs from other types of crystal structures. They are also developing new data mining modules to discover other types of functional materials for energy conversion, optoelectronic and spintronic applications.

Behind the Scenes: The Supercomputer "Comet & # 39; SDSC feeds research

Yang largely attributes the success of his project to the use of the Comet supercomputer at the San Diego Supercomputer Center (SDSC) of San Diego UC. "Our large-scale calculations in quantum mechanics have required a large number of computing resources," he explained. "Since 2016, we've got some computing time – about 3.46 million hours on Core Comet, which made the project possible."

Although Comet fueled the simulations of this study, Yang said that SDSC staff also played a crucial role in his research. Ron Hawkins, Director of Industry Relations at SDSC, and Jerry Greenberg, IT Research Specialist at the Center, made sure that adequate support was provided to Yang and his team. In particular, the researchers called on SDSC staff to compile and install Comet computer codes, funded by the National Science Foundation.