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Ying Wang
January 30, 2024

Ying Wang will use NSF CAREER award to craft new memory using 2D ferroelectricity

Written By: Jason Daley

Emerging technologies—including artificial intelligence, big data analytics and edge computing—need new generations of electronics to reach their full potential. In particular, these fields need the development of small, super-fast, energy-efficient memory devices that can manage massive amounts of data.

That’s why Ying Wang, an assistant professor of electrical and computer engineering at the University of Wisconsin–Madison, is using a National Science Foundation CAREER award to develop a memory device using 2D materials that exhibit a property known as sliding ferroelectricity.

2D materials are extremely thin crystalline materials, usually just several atoms thick. By stacking these materials together, it is possible to generate novel electrical properties. One of these properties is called sliding ferroelectricity, where the relative positioning of atomic flakes can slide, transferring charges that flip polarization. This polarization flipping process occurs with remarkable speed and efficiency, making ferroelectric materials ideal for data recording and processing.

In her project, Wang plans to comprehensively study sliding ferroelectricity to understand and control the phenomenon. The ultimate goal is to create prototype memory devices, such as ferroelectric tunnelling junctions, from atomically thin 2D sheets of boron nitride and transition metal dichalcogenides. Those materials exhibit sliding ferroelectricity when stacked at slightly offset angles.

Wang says creating the devices is easier said than done. “Developing a device from these crystals is complex, requiring not only delicate fabrication but also a comprehensive understanding of the mechanisms at play,” she explains. “For instance, the robustness of this new ferroelectric order in memory device geometry is yet to be determined. We will study the sliding ferroelectricity under various electrical and mechanical boundary conditions. With that new knowledge, we can optimize the memory performance accordingly.”

If Wang is able to create and optimize these devices, it will be possible to integrate them into various systems that use memory.

In fact, she says if the project is successful, boron nitride-based ferroelectric memory might become feasible sooner rather than later. “Boron nitride is already accessible at the wafer scale,” she says. “It’s stable at ambient temperatures and can sustain extreme environments like high temperatures. It’s very compatible with semiconductor manufacturing techniques.”

Photo of Ying Wang by Todd Brown