
Rijksuniversiteit Groningen, Faculty of Science and Engineering (FSE), Zernike Institute for Advanced Materials, Physics of nanodevices
Rijksuniversiteit Groningen, Faculty of Science and Engineering (FSE), Zernike Institute for Advanced Materials, Physics of nanodevices
2 Projects, page 1 of 1
assignment_turned_in Project2023 - 9999Partners:Technische Universiteit Delft, Faculteit Technische Natuurwetenschappen, NanoScience - Kavli Institute of Nanoscience Delft, Department of Quantum Nanoscience, Kavli Institute of Nanoscience Delft, Universiteit Utrecht, Faculteit Bètawetenschappen, Departement Natuurkunde, Technische Universiteit Delft, Faculteit Technische Natuurwetenschappen, NanoScience - Kavli Institute of Nanoscience Delft, Department of Quantum Nanoscience, Technische Universiteit Delft, Faculteit Technische Natuurwetenschappen, NS/Mol.Electronics&Devices, Rijksuniversiteit Groningen +6 partnersTechnische Universiteit Delft, Faculteit Technische Natuurwetenschappen, NanoScience - Kavli Institute of Nanoscience Delft, Department of Quantum Nanoscience, Kavli Institute of Nanoscience Delft,Universiteit Utrecht, Faculteit Bètawetenschappen, Departement Natuurkunde,Technische Universiteit Delft, Faculteit Technische Natuurwetenschappen, NanoScience - Kavli Institute of Nanoscience Delft, Department of Quantum Nanoscience,Technische Universiteit Delft, Faculteit Technische Natuurwetenschappen, NS/Mol.Electronics&Devices,Rijksuniversiteit Groningen,Technische Universiteit Delft, Faculteit Technische Natuurwetenschappen, NanoScience - Kavli Institute of Nanoscience Delft,Universiteit Utrecht,Rijksuniversiteit Groningen, Faculty of Science and Engineering (FSE), Zernike Institute for Advanced Materials, Physics of nanodevices,Rijksuniversiteit Groningen, Faculty of Science and Engineering (FSE), Zernike Institute for Advanced Materials,Rijksuniversiteit Groningen, Faculty of Science and Engineering (FSE), Technische Fysica,Technische Universiteit DelftFunder: Netherlands Organisation for Scientific Research (NWO) Project Code: OCENW.XL21.XL21.058Reducing the energy consumption of information technology is one of the major challenges of the 21st century. A potential way to meet this challenge is to realize information processing based on magnons – wave-like excitations of spins in magnetic materials – and thereby avoid the heating caused by electric currents. Efficient and scalable control of magnon transport and information is a key requirement for its integration in information technology, but has thus far remained an outstanding challenge. We will address this challenge by realizing a controllable two-dimensional (2D) gas of magnons in atomically-thin ‘van der Waals’ magnets. Similar to electron transport in 2D conductors such as graphene, we expect the magnon transport in these 2D magnets to be highly tunable by voltages, strain, and proximity to auxiliary 2D materials. Moreover, the intrinsic 2D nature of the magnon gas should lead to strong magnon interactions, enabling fundamentally new phenomena such as topologically-protected and dissipationless magnon transport. To realize a controllable 2D magnon gas, we will focus on van der Waals magnets that are intralayer ferromagnets, but display both interlayer ferromagnetic and antiferromagnetic ordering, such as chromium halides and related compounds. Their magnetic order is tunable by magnetic fields, electric fields, strain, and other 2D materials, providing control over their magnon spectrum and transport properties. We will measure the transport properties of the 2D magnon gas using electrical and optical means, fabricate 2D heterostructures to tune its magnetic parameters, and realize mechanical control of magnons using suspended membranes. Building on these developments, we will create transistor-like devices to reach new regimes of topological, hydrodynamic, and dissipationless spin transport. The demonstration of controllable 2D magnon gases could have an impact comparable to the 2D electron gas that revolutionized classical and quantum electronics, paving the way for new-generation spintronic devices. Our consortium is designed to enable the breakthrough potential of two-dimensional magnon transport. It brings together researchers at different career stages with expertise in van der Waals heterostructure fabrication, magnon-transport theory, and state-of-the-art techniques to detect and control magnons in ultrathin magnets. It builds on successful collaborations and creates a new and crucial connection between the 2D-material and spintronics technologies from Groningen and the membrane and imaging technologies from Delft.
more_vert assignment_turned_in ProjectFrom 2023Partners:Radboud Universiteit Nijmegen, Faculteit der Natuurwetenschappen, Wiskunde en Informatica, Institute for Molecules and Materials (IMM), FELIX Laboratory, NWO-institutenorganisatie, ASTRON - Netherlands Institute for Radio Astronomy, Technische Universiteit Eindhoven - Eindhoven University of Technology, Radboud Universiteit Nijmegen, Rijksuniversiteit Groningen +26 partnersRadboud Universiteit Nijmegen, Faculteit der Natuurwetenschappen, Wiskunde en Informatica, Institute for Molecules and Materials (IMM), FELIX Laboratory,NWO-institutenorganisatie, ASTRON - Netherlands Institute for Radio Astronomy,Technische Universiteit Eindhoven - Eindhoven University of Technology,Radboud Universiteit Nijmegen,Rijksuniversiteit Groningen,Radboud Universiteit Nijmegen,Rijksuniversiteit Groningen, Faculty of Science and Engineering (FSE), Instituut voor Kunstmatige Intelligentie,Rijksuniversiteit Groningen,TNO Delft, Optica,Radboud Universiteit Nijmegen, Faculteit der Natuurwetenschappen, Wiskunde en Informatica, Institute for Computing and Information Sciences (ICIS),Universiteit Twente,Technische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Electrical Engineering - Department of Electrical Engineering, Electro-Optical Communication (ECO),Technische Universiteit Delft, Universiteitsdienst, Dienst Elektronische en Mechanische Ontwikkeling (DEMO),Technische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Electrical Engineering - Department of Electrical Engineering, Electronic Systems (ES),Technische Universiteit Delft,Radboud Universiteit Nijmegen, Faculteit der Natuurwetenschappen, Wiskunde en Informatica, Subfaculteit Natuurkunde, Experimentele Vaste Stof Fysica,Rijksuniversiteit Groningen, Faculty of Science and Engineering (FSE), Zernike Institute for Advanced Materials,Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), MESA+ Research Institute for Nanotechnology,NWO-institutenorganisatie, AMOLF,Rijksuniversiteit Groningen, Faculty of Science and Engineering (FSE), Zernike Institute for Advanced Materials, Physics of nanodevices,Universiteit Twente,Fontys University of Applied Sciences,Universiteit Twente, Faculty of Science and Technology (TNW), Chemical Engineering, Inorganic Materials Science (IMS),TNO Delft,Technische Universiteit Delft,Technische Universiteit Eindhoven - Eindhoven University of Technology,Technische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Technische Natuurkunde - Department of Applied Physics, Physics of Nanostructures (FNA),NWO-institutenorganisatie,Saxion,Rijksuniversiteit Groningen, Faculty of Science and Engineering (FSE),Radboud Universiteit Nijmegen, Faculteit der Natuurwetenschappen, Wiskunde en Informatica, Institute for Molecules and Materials (IMM)Funder: Netherlands Organisation for Scientific Research (NWO) Project Code: NWA.1389.20.140The energy consumption of today’s Information Technology presents a key bottleneck for computer systems to go forward and has risen to unsustainable levels that seriously affect climate change. In a holistic approach between academia, industry and society, NL-ECO aims at scientific and technological breakthroughs, including demonstrators, that will dramatically reduce this energy consumption with orders of magnitude. As inspiration we have an enticing benchmark, the brain: while consuming hardly 20 Watts, it outperforms, on specific tasks such as learning and pattern recognition, multi-megawatt supercomputers.
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