ADVANCED MATERIALS & PROCESSES | NOVEMBER/DECEMBER 2023 5 MEET MOLYBDENENE: GRAPHENE’S METALLIC COUSIN Scientists at Forschungszentrum Jülich, Germany, along with colleagues from the Indian Institute of Technology in Patna and the Australian University of Newcastle, created a new 2D material that exhibits a metallic character. Named molybdenene, it consists of just one atomic layer of molybdenum atoms. In addition to graphene, other 2D relatives such as phosphorene and germanene have been introduced in recent years. All have impressive properties, but molybdenene features some unusual benefits. “Many 2D materials are sensitive to heat, but molybdenene is not. Moreover, this is the first metallic 2D material where freestanding layers could be prepared,” says Prof. Ilia Valov of Forschungszentrum Jülich. The researchers created the new 2D material using a microwave, in which they heated a mixture of molybdenum sulfide and graphene to incandescence at a temperature of around 3000°C. In a reaction driven by the microwave electric field, finely branched hair structures called whiskers were formed, in which the tapered molybdenum layers RESEARCH TRACKS can be found. The scientists have already observed a range of useful properties and expect that the material has further exotic electronic properties, similar to graphene, due to its 2D structure. Because of its metallic character, it also has freely moving electrons. These accumulate on the two sides of the molybdenene, which makes the material an interesting candidate as a catalyst as well. The international team has already developed a practical application for molybdenene. Due to its stability and excellent electrical and thermal conductivity, it is well suited for use as a measuring tip for atomic force microscopy and surface-enhanced Raman spectroscopy. www.fz-juelich.de. BETTER BATTERIES VIA COMPUTER VISION Researchers from the DOE’s SLAC National Accelerator Laboratory, Stanford University, the Massachusetts Institute of Technology, and Toyota Lithium ions flowing in and out of battery electrode nanoparticles during battery cycling. The false colors show the charge status of each particle and reveal how uneven the process within a single particle can be. Courtesy of Cube3D. Research Institute are using machine learning to re-analyze x-ray movies of lithium ions flowing in and out of battery electrode nanoparticles during battery cycling. More specifically, the team is using a type of machine learning called computer vision to study each pixel of those movies in order to discover physical and chemical details of battery cycling that could not be seen before. The new method suggests a way to make the billions of lithium iron phosphate (LFP) nanoparticles in one type of lithium-ion battery electrode store and release charge more efficiently, say scientists. In this latest study, professors William Chueh of Stanford and Martin Bazant of MIT used computer vision to mine more detailed information from 62 of the nanoscale x-ray movies they made in 2016 of LFP particles charging or discharging. Each still image from those movies contains roughly 490 pixels, giving them roughly 180,000 pixels of information to work with. The most significant finding of the research—that variations in the thickness of an LFP particle’s carbon coating directly control the rate at which lithium ions flow in and out— could lead to more efficient battery charging and discharging. www6.slac. stanford.edu. High-resolution electron microscope image of molybdenene. Courtesy of Nature Nanotechnology.
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