How Supercomputers Will Yield a Golden Age of Materials Science

Advanced computers + simplified quantum mechanics equations = a new paradigm for creating new materials.

With supercomputers and the equations of quantum mechanics, scientists are designing new materials atom by atom, before ever running an experiment

Materials science, the process of engineering matter into new and useful forms, has come a long way since the days of Edison. Quantum mechanics has given scientists a deep understanding of the behavior of matter and, consequently, a greater ability to guide investigation with theory rather than guesswork. Materials development remains a painstakingly long and costly process, however. Companies invest billions designing novel materials, but successes are few and far between. Researchers think of new ideas based on intuition and experience; synthesizing and testing those ideas involve a tremendous amount of trial and error. It can take months to evaluate a single new material, and most often the outcome is negative. ..., it takes an average of 15 to 20 years for even a successful material to move from lab testing to commercial application.

The exponential growth of computer-processing power, combined with work done in the 1960s and 1970s by Walter Kohn and the late John Pople, who developed simplified but accurate solutions to the equations of quantum mechanics, has made it possible to design new materials from scratch using supercomputers and first-principle physics. The technique is called high-throughput computational materials design, and the idea is simple: use supercomputers to virtually study hundreds or thousands of chemical compounds at a time, quickly and efficiently looking for the best building blocks for a new material, be it a battery electrode, a metal alloy or a new type of semiconductor. [emphasis mine]

The first step in high-throughput materials design, then, is to virtually “grow” new materials by crunching thousands of quantum-mechanical calculations. A supercomputer arranges virtual atoms into hundreds or thousands of virtual crystal structures. Next, we calculate the properties of those virtual compounds. What do the crystal structures look like? How stiff are they? How do they absorb light? What happens when you deform them? Are they insulators or metals? We command the computer to screen for compounds with specific desirable properties, and before long, promising compounds rise to the top.

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