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Supercomputing More Light than Heat
Supercomputing More Light than Heat
XSEDE's Maverick helps explore next generation solar cells and LEDs
Solar cells can't stand the heat. Photovoltaics lose some energy as heat in converting sunlight to electricity. The reverse holds true for lights made with light-emitting diodes (LED), which convert electricity into light. Some scientists think there might be light at the end of the tunnel in the hunt for better semiconductor materials for solar cells and LEDs, thanks to supercomputer simulations that leveraged graphics processing units to model nanocrystals of silicon.
Scientists call the heat loss in LEDs and solar cells non-radiative recombination. And they've struggled to understand the basic physics of this heat loss, especially for materials with molecules of over 20 atoms.
"The real challenge here is system size," explained Ben Levine, associate professor in the Department of Chemistry at Michigan State University. "Going from that 10-20 atom limit up to 50-100-200 atoms has been the real computation challenge here," Levine said. That's because the calculations involved scale with the size of the system to some power, sometimes four or up to six, Levine said. "Making the system ten times bigger actually requires us to perform maybe 10,000 times more operations. It's really a big change in the size of our calculations."
Levine's calculations involve a concept in molecular photochemistry called a conical intersection - points of degeneracy between the potential energy surfaces of two or more electronic states in a closed system. A perspective study published September of 2017 in the Journal of Physical Chemistry Letters found that recent computational and theoretical developments have enabled the location of defect-induced conical intersections in semiconductor nanomaterials.
"The key contribution of our work has been to show that we can understand these recombination processes in materials by looking at these conical intersections," Levine said. "We've been able to show is that the conical intersections can be associated with specific structural defects in the material."
The holy grail for materials science would be to predict non-radiative recombination behavior of a material based on its structural defects. These defects come from 'doping' semiconductors with impurities to control and modulate its electrical properties.
Looking beyond the ubiquitous silicon semiconductor, scientists are turning to silicon nanocrystals as candidate materials for the next generation of solar cells and LEDs. Silicon nanocrystals are molecular systems in the ballpark of 100 atoms with extremely tunable light emission compared to bulk silicon. And scientists are limited only by their imagination in ways to dope and create new kind of silicon nanocrystals.
"We've been doing this for about five years now," Levine explained about his conical intersection work. "The main focus of our work has been proof-of concept, showing that these are calculations that we can do; that what we find is in good agreement with experiment; and that it can give us insight into experiments that we couldn't get before," Levine said.
Levine addressed the computational challenges of his work using graphics processing unit (GPU) hardware, the kind typically designed for computer games and graphics design. GPUs excel at churning through linear algebra calculations, the same math involved in Levine's calculations that characterize the behavior of electrons in a material. "Using the graphics processing units, we've been able to accelerate our calculations by hundreds of times, which has allowed us to go from the molecular scale, where we were limited before, up to the nano-material size," Levine said.