EPFL researchers have sent and stored data using charge-free magnetic waves

The discovery could solve the dilemma of energy-hungry computing technology in the age of big data.


A major issue is traditional computing architecture, which separates processors and memory. The signal conversions involved in moving data between different components slow down computation and waste energy. This inefficiency is known as the memory wall or Von Neumann bottleneck.

There is a challenging quest for novel approaches to overcome this so-called von Neumann bottleneck. Magnons are the quanta of spin waves. Their angular momentum enables power-efficient computation without charge flow.

Magnons are the quanta of spin waves. Because they interact with magnetic fields, magnons can be used to encode, and transport data without electron flows, which involve energy loss through heating (known as Joule heating) of the conductor used.

Researchers at EPFL have successfully sent and stored data using charge-free magnetic waves rather than conventional electron flows, thanks to a breakthrough in the field of magnonics. The problem of energy-hungry computing technologies in the big data era may now be resolved thanks to the finding.

While doing other experiments on a commercial wafer of the ferrimagnetic insulator yttrium iron garnet (YIG) with nanomagnetic strips on its surface, LMGN Ph.D. student Korbinian Baumgaertl was inspired to develop precisely engineered YIG-nanomagnet devices. With the Center of MicroNanoTechnology‘s support, Baumgaertl could excite spin waves in the YIG at specific gigahertz frequencies using radiofrequency signals and – crucially – reverse the magnetization of the surface nanomagnets.

Dirk Grundler, head of the Lab of Nanoscale Magnetic Materials and Magnonics (LMGN) in the School of Engineering, explains“The two possible orientations of these nanomagnets represent magnetic states 0 and 1, which allows digital information to be encoded and stored.”

“Theoretically, the magnonics approach could process data in the terahertz range of the electromagnetic spectrum (for comparison, current computers function in the slower gigahertz range). However, they still need to demonstrate this experimentally.”

“The promise of this technology for more sustainable computing is huge. With this publication, we are hoping to reinforce interest in wave-based computation and attract more young researchers to the growing field of magnonics.”

Journal Reference:

  1. Baumgaertl, K., Grundler, D. Reversal of nanomagnets by propagating magnons in ferrimagnetic yttrium iron garnet enabling nonvolatile magnon memory. Nat Commun 14, 1490 (2023). DOI: 10.1038/s41467-023-37078-8
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