Speeding Up Materials Design
A new computer program accurately predicts the behavior of proposed materials, which means faster development of new electronics and solar cells.
A chemical compound designed with the aid of a Harvard-created computer program has turned out to be one of the best organic electronic materials to date. This new material, an organic semiconductor, could be used to make new electronics such as colorful displays that roll up. It’s an important proof of principle for using computers to aid materials design.
Organic semiconductors could enable less expensive, lightweight electronics that can take new forms, such as flexible displays and printed solar cells. It’s hoped that the materials will also make solar power more widespread, because it should be less expensive to make solar cells from them than from silicon and other inorganic materials. But in the decades since chemists began working with organic semiconductors, progress has been slow, and these materials have found limited applications, such as in short-lived portable solar cells. The main challenge is that these materials just don’t conduct electrons and their positive counterparts, holes, nearly as fast as conventional semiconductors like silicon, making them much less efficient.
The new organic semiconductor, predicted using a computer modeling program developed by Harvard chemistry professor Alán Aspuru-Guzik, and then synthesized by researchers at Stanford University, conducts charge much faster than the silicon material used in most of today’s display electronics. That means it could be used to make brighter displays that provide crisper video. And the new material is sufficiently speedy to make electronics for organic light-emitting diode (OLED) displays used in cell phones and televisions or to control radio-frequency identification (RFID) tags used to track stuff.
For many years, scientists have talked about the potential of computational modeling to shorten the materials development process. When chemists develop new materials, “most work is based on intuition,” says Zhenan Bao, the Stanford professor of chemical engineering whose group made and tested the new material. Unfortunately, intuition is hit or miss—a new molecule that seems promising may not do what researchers expect it to. By prescreening potential materials using Aspuru-Guzik’s computer program, chemists can focus the months or years needed to synthesize and test new compounds on those that seem most promising.
Computational screening has been a great success in some areas, including energy storage. Gerbrand Ceder, a professor at MIT, has computationally predicted faster-charging battery materials that are currently being commercialized by the company A123 Systems. Until recently, computational methods hadn’t been applied to making better organic semiconductors, which pose a different set of challenges, says Aspuru-Guzik. But now theoretical chemists have generated enough foundational knowledge, and experimentalists enough data, to make successful predictive models.
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