Computational Discovery and Optimization of Organic Photovoltaic Materials.
Doing chemistry by computer takes scientist into ‘the k space’
So Hirata, a computational chemist at the University of Illinois at Urbana-Champaign, is bringing his talent for computational innovation to the vital work of creating cheap and efficient materials to generate electricity from sunlight. Hirata is creating advanced computational algorithms—sets of mathematical instructions for carrying out a procedure or solving a problem—to theoretically predict the optical and electronic properties of a class of advanced polymer materials used to transform the way energy is generated or used more efficiently. “When we said ‘polymers’ we used to imagine plastic bags, pipes and fabrics,” Hirata said. “For these conventional applications the important properties are mechanical, chemical and thermal. But today polymer chemistry has a much broader application, including solar cells, light emitting diodes, batteries, sensors and transistors.” For these optoelectronic applications, he added, the most important properties are quantum mechanical. Specifically, researchers want to know precisely how the electrons in the atoms composing the polymer molecules will behave in these devices. Hirata has chosen to bite off a very big piece of the scientific pie – polymers are one of the largest and most important classes of molecules that are vital as the base materials of future energy technologies and modern industry in general. To develop highly accurate and general computational methods that can predict key information about their properties and functions – information that can be relied upon as gospel by legions of synthetic and analytical chemists—is a risky endeavor with no guarantee of success. That is why his project is being funded by Research Corporation for Science Advancement (RCSA). The nation’s second-oldest foundation, RCSA supports early-career scientists with innovative, potentially game-changing ideas, said RCSA President and CEO James M. Gentile. Currently most computational research on polymers is done with what’s called Density Functional Theory (DFT). It is a quantum mechanical modeling tool used in physics and chemistry to explore how electrons behave in “an averaged way.” While still the most practically useful tool today, Hirata noted, DFT is “fundamentally limited” in its ability to predict the very properties of polymers that make them useful as advanced materials. He said a new class of computational methods that go beyond DFT must be developed for polymers that are simultaneously accurate and efficient. His solution to meeting these two conflicting demands involves applying new algorithms he and his associates are developing to dramatically speed up the accurate, but normally prohibitively expensive computational methods and to make them applicable to polymers. The algorithms are called “k-space downsampling.” The “k space” is the flip side of the “real space” we live in. These two spaces are related to each other by the mathematical relationship called a Fourier transform and also by the physical theorem known as Heisenberg’s uncertainty principle. The motion of electrons can be described in the real space or its converse, the k space. While the basic variables of electrons in the real space are their positions, those in the k space are the “k,” the letter physicists have reserved for an electron’s momentum. Hirata and his colleagues believe they have figured out new, better ways to describe complex dynamical motion of electrons in the k space. The k-space algorithms derived from these new insights can help scientists achieve unprecedented accuracy and reliability in the computational predictions of the properties and functions of polymers, bringing a new way of material design and optimization based on computing. RCSA is supporting Hirata’s work under its Scialog® Awards program. “Scialog” comes from “science” and “dialog.” Besides funding highly innovative ideas, the program also brings researchers together once a year to further the innovation process. “Scialog fellows come to the annual conference to focus on the next research steps they might want to take beyond commonly accepted paradigms in a given field of knowledge,” Gentile said. They come up with new ideas and new approaches to fundamental research through open, nonjudgmental discussions – the nonjudgmental aspect is relatively rare in the highly critical world of science, Gentile added. The annual scientific discussions are held at Biosphere2 north of Tucson, Arizona. The massive glass and steel Biosphere2 structure – bigger than two football fields - was built between 1987 and 1991 at a cost of more than $2 million. It was designed to study the interaction of humans and plants in the world’s largest sealed environment. Two “missions” involving humans in the Biosphere were ended prematurely, prompting the media and the general public to view the endeavor as a “failed” experiment. But Gentile said there are really no failed experiments in science, merely experiments that do not confirm their hypothesis. “These so-called failures often yield important information that points us to new and useful insights.” He said RCSA chose Biosphere2 as its base for the Scialog program for just that reason. “In science it’s important to take risks, and risk-taking, by its very nature, involves the possibility of failure. But we can’t learn new things and develop new paradigms without taking those risks.” Gentile added that many important insights have come out of Bisophere2, despite its public reputation. “Most people don’t know that our current understanding about the plight of coral reefs in a warming world due to increasing levels of atmospheric carbon dioxide came from Biosphere2, and not from some research lab on the seacoast.” Biosphere2, home to numerous ongoing environmental and climate-related studies, is currently administered by the University of Arizona’s College of Science. The National Science Foundation and the University of Arizona co-sponsor the annual Scialog conferences with RCSA.