Researchers at Argonne National Laboratory (AGL) have made a breakthrough in microelectronics by discovering how ferroelectric materials adapt their structures under light pulses.
Ferroelectric materials, known for their use in memory, sensors, and transistors, now show potential for energy-efficient computing systems. The researchers from AGL revealed that these materials can reorganize their nanostructures when exposed to light, enabling them to create a variety of domain structures. This adaptation mirrors the plasticity of neural networks, opening the door to new data processing techniques that use less energy. The advancement could lead to significant reductions in power consumption for supercomputers and data centers, making it a game-changer for industries reliant on high-performance computing, including AI, big data analytics, and cloud computing.
“Today’s supercomputers and data centers demand many megawatts of power,” explained Haidan Wen, physicist, AGL. “One challenge is to find materials for more energy-efficient microelectronics. A promising candidate is ferroelectric material that can be used for artificial neural networks as a component in energy-efficient microelectronics.” As a result, target audiences for this innovation include hardware manufacturers, data center operators, and developers of artificial intelligence technologies who seek to enhance performance while reducing energy costs.
The research was a collaborative effort between AGL, Rice University, Pennsylvania State University, and the DOE’s Lawrence Berkeley National Laboratory. By applying light pulses, the team observed the material’s nanodomains—the tiny, distinct regions within the material—rearranging themselves based on the number of photons received. This could drastically improve the efficiency of data processing in various applications.
Wen explained that earlier experiments with intense light pulses created uniform nanostructures. However, this time the researchers used multiple weaker light pulses. “This time, we hit the sample with many weak light pulses, each of which lasts a quadrillionth of a second,” Wen said. These pulses generated a family of domain structures, each unique and adaptable, depending on the light dosage.
The resulting configurations were visualized using advanced X-ray imaging at Center for Nanoscale Materials, AGL. The findings open new possibilities for adaptive networks in computing, offering the potential for faster and more energy-efficient systems. According to Stephan Hruszkewycz, physicist, AGL “The door is now wide open to many more discoveries,” leading to a future where computing is not only faster but also far more power-efficient.
