Researchers at the USC Viterbi School of Engineering have created a graphene-based memory device which promises to increase data upload speed, extend smartphone battery life, and reduce data corruption. The team did this through a concept called the ferroelectric tunneling junction (FTJ).

This new memory device is part of a family known as non-volatile memory devices, meaning they can be unplugged and still retain their data, much like cell phone memory and USB flash drives. Unlike current FTJ devices, this device is comprised of asymmetric metal and semi-metallic graphene materials.

By taking these materials and building them into a novel structure, the team reported that it was possible to exceed the performance of all previously demonstrated FTJs while offering promising prospects for integration with silicon electronics.

“This breakthrough will have a significant impact on future electronics for the U.S. Army, enabling man-portable electronic systems with improved size, weight and power,” said Dr. Joe Qiu, program manager for solid-state electronics and electromagnetics at ARO, which sponsored this project.

Furthermore, the unique ability of these materials to approach atomic-scale thickness can eventually lead to even faster and more energy-efficient FTJ memory down the line. “These materials allow us to build devices that can potentially be scaled to atomic-scale thickness,” Wang said. “This means the voltage required to read, write, and erase data can be drastically reduced which in turn can make the memory electronics much more energy efficient.”

Wang and his fellow researchers hope that with time, their device can be scaled up and may become a replacement not just for the non-volatile memory that we see in cell phones and USB sticks, but also volatile memory like D-RAM storage devices commonly found in computers. In addition, the device may also be engineered to hold multi-bit data states within a single cell, and with its robust endurance and retention, it has promising potential for applications in in-memory computing and other computing hardware.

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