Magnetic materials can attract or repel each other based on their polar orientation — positive and negative ends attract each other, while two positives or two negatives repel. When an electromagnetic signal like a radio wave passes through such materials, a magnetic material acts like a gatekeeper, letting in the signals that are desired but keeping out others. They can also amplify the signal or dampen the speed and strength of the signals.
Engineers have used these gatekeeper-like effects, called “wave-material interactions,” to make devices used in communication technologies for decades. These include circulators that send signals in specific directions or frequency-selective limiters that reduce noise by suppressing the strength of unwanted signals. Current design tools are not comprehensive and precise enough to capture the complete picture of magnetism in dynamic systems such as super-tiny implantable devices. The tools also have limits in the design of consumer electronics.
A new computational tool addresses these problems by providing a clear path toward figuring out how potential materials would be best used in communication devices. The tool models how magnetic materials used in smartphones and other communication devices interact with incoming radio signals that carry data. It accurately predicts these interactions down to the small nanometer scales required to build state-of-the-art communication technologies.
It could enable the design of new classes of radio frequency-based components that are able to transport large amounts of data much more rapidly and with less noise that would otherwise interfere with the signal. These components could then be used in everything from smart-phones to tiny, implantable health-monitoring devices.
The computational tool is based on a method that jointly solves well-known Maxwell’s equations that describe how electricity and magnetism work, and the Landau–Lifshitz–Gilbert equation that describes how magnetization moves inside a solid object.
Next steps include improving the tool to account for multiple types of magnetic and non-magnetic materials. Eventually, these improvements could lead to it becoming a “universal solver” that would account for any kind of electromagnetic wave interacting with any kind of material.