Predictive modeling yields promising ‘spin’ on semiconductors for quantum technologies

UW Madison News

Semiconductors have traditionally relied on electron for the on/off switches to record and process information. The next iteration of computing, including low-power devices and quantum computers, is shifting to “spintronics,” will rely on new types of semiconductors that use a fundamental property of electrons called spin instead of electric charge. Yuan Ping, an associate professor at the University of Wisconsin-Madison, led a study exploring halide perovskites, a class of semiconductors for spintronics. The team explores the spin decay mechanisms related to the symmetry and composition of these materials to enhance spintronic characteristics. The research team developes and applies a predictive computational platform that allows for rational design of new materials. The study indicates the potential of halide perovskites for spintronics, offering a low-cost, room-temperature, and commercially viable option.

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