Researchers have revealed an adaptive response with a ferroelectric device, which responds to light pulses in a way that resembles the plasticity of neural networks. This behavior could find application in energy-efficient microelectronics.
"Today's supercomputers and data centers demand many megawatts of power," said Haidan Wen, a physicist at the U.S. Department of Energy (DOE) Argonne National Laboratory. "One challenge is to find materials for more energy-efficient microelectronics. A promising candidate is a ferroelectric material that can be used for artificial neural networks as a component in energy-efficient microelectronics."
Ferroelectric materials can be found in different kinds of information processing devices, such as computer memory, transistors, sensors and actuators. Argonne researchers report surprising adaptive behavior in a ferroelectric material that can evolve step-by-step to a desired end, depending on the number of photons from light pulses striking the material. Working alongside Argonne researchers were scientists from Rice University, Pennsylvania State University and DOE's Lawrence Berkeley National Laboratory.
The paper is published in the journal Advanced Materials.
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