Magnetic fields created by skyrmions in two-dimensional sheet of material composed of iron, germanium and tellurium. (credit: Argonne Lab)
Scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory are investigating the possibility that tiny magnetic whirlpools called “skyrmions,” which are magnetic vortices as tiny as billionths of a meter, could transform memory storage in future high performance computers.
Skyrmions, the Argonne researchers say, show characteristics that could overcome the shortcomings of microscopic bar magnets, whose magnetic fields each can store one bit of memory as a zero or a one — the language of computers.
Why skyrmions? “We estimate the skyrmion energy efficiency could be 100 to 1000 times better than current memory in the high performance computers used in research,” said Arthur McCray, a Northwestern University graduate student working in Argonne’s Materials Science Division (MSD).
Energy efficiency is essential to the next generation of microelectronics. Today’s microelectronics already account for a notable fraction of the world’s energy use and could consume nearly 25 percent within the decade. More energy-efficient electronics must be found.
“We have a way to go before skyrmions find their way into any future computer memory with low power,” said Charudatta Phatak, a materials scientist and group leader in the MSD. “Nonetheless, this kind of radical new way of thinking about microelectronics is key to next generation devices.”
Skyrmions, unlike bar magnets, have potential for computrs because, in the words of McCray, “The bar magnets in computer memory are like shoelaces tied with a single knot; it takes almost no energy to undo them.” This means that any bar magnets malfunctioning due to some disruption will affect the others.
“By contrast, skyrmions are like shoelaces tied with a double knot,” McCray said. “No matter how hard you pull on a strand, the shoelaces remain tied.” The skyrmions are thus extremely stable to any disruption.
Another important feature is that scientists can control their behavior by changing the temperature or applying an electric current.
Scientists have much to learn about skyrmion behavior under different conditions. To study them, the Argonne-led team developed an artificial intelligence (AI) program that works with a high-power electron microscope at the Center for Nanoscale Materials (CNM), a DOE Office of Science user facility at Argonne. The microscope can visualize skyrmions in samples at very low temperatures.
The team’s magnetic material is a mixture of iron, germanium and tellurium. In structure, this material is like a stack of paper with many sheets. A stack of such sheets contains many skyrmions, and a single sheet can be peeled from the top and analyzed at facilities like CNM.
“The CNM electron microscope coupled with a form of AI called machine learning enabled us to visualize skyrmion sheets and their behavior at different temperatures,” said Yue Li, a postdoctoral appointee in MSD.
“Our most intriguing finding was that the skyrmions are arranged in a highly ordered pattern at minus 60 degrees Fahrenheit and above,” said Phatak. “But as we cool the sample the skyrmion arrangement changes.” Like bubbles in beer foam, some skyrmions became larger, some smaller, some merge and some vanish.
Change of skyrmion groupings from highly ordered to disordered with temperature from -92 F (204 kelvin) to -272 F (104 kelvin). Bright dots indicate order. (credit Argonne National Lab)
At minus 270, the layer reached a state of nearly complete disorder, but order came back when the temperature returned to minus 60. This order-disorder transition with temperature change could be exploited in future microelectronics for memory storage.
This research was supported by the DOE Office of Basic Energy Sciences. The team’s machine learning program was run on supercomputing resources at the Argonne Leadership Computing Facility, a DOE Office of Science user facility.
This research appeared in Nano Letters. In addition to Phatak, Li, and McCray, Argonne authors include Amanda K. Petford-Long, Daniel P. Phelan and Xuedan Ma. Other authors include Rabindra Basnet, Krishna Pandey and Jin Hu from the University of Arkansas.
source: Joseph Harmon, Integrated Communications Manager, Argonne
