EM, magnetics tool aims to offer 'universal solver' for RF communications

September 14, 2018 //By Rich Pell
EM, magnetics tool aims to offer 'universal solver' for RF communications
Researchers at the UCLA Samueli School of Engineering (Los Angeles, CA) have developed a way to model how magnetic materials interact with incoming radio signals that carry data.

The new computational tool accurately predicts these interactions down to the nanometer scales required to build state-of-the-art communications technologies. As a result, say the researchers, it enables engineers to design new classes of radio frequency-based components that are able to transport large amounts of data more rapidly, and with less noise interference.

When an electromagnetic (EM) signal such as a radio wave passes through a magnetic material, the material acts like a "gatekeeper" – letting in signals that are desired, but keeping out others. Such materials can also amplify the signal, or dampen the speed and strength of the signal.

These gatekeeper-like effects – called “wave-material interactions” – have been used by engineers to make devices used in communications technologies for decades, say the researchers. For example, such devices include circulators that send signals in specific directions and frequency-selective limiters that reduce noise by suppressing the strength of unwanted signals.

However, say the researchers, current design tools are not comprehensive and precise enough to capture the complete picture of magnetism in dynamic systems, such as implantable devices, and also have limits in the design of consumer electronics.

"Our new computational tool addresses these problems by giving electronics designers a clear path toward figuring out how potential materials would be best used in communications devices," says Yuanxun "Ethan" Wang, a professor of electrical and computer engineering who led the research. "Plug in the characteristics of the wave and the magnetic material, and users can easily model nanoscale effects quickly and accurately. To our knowledge, this set of models is the first to incorporate all the critical physics necessary to predict dynamic behavior."

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