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Wireless antennas learn thanks to Artificial Intelligence

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Wireless antennas learn thanks to Artificial Intelligence

Body scanners and antennas for wireless communications thanks to artificial intelligence, are able to learn and reprogram if some components break: this could be possible thanks to new materials that operate with light. This is indicated by an experiment published in the journal Nature Communications and coordinated by Vincenzo Galdi, of the University of Sannio, and by Tie Jun Cui, of the Chinese Southeast University. The research group also includes Giuseppe Castaldi, from the University of Sannio, in Benevento.

The materials at the base of the experiment belong to the family of so-called metamaterials, which are aggregates of artificial molecules whose electromagnetic properties can be adapted and modified by manipulating their nanostructures.

The researchers used them to obtain an antenna prototype, programmable like a software, that works in microwaves, but the device can be miniaturized to work even with light. The antenna has shown that it can not only send information in different directions and operate at multiple frequencies, as do mobile phones, but to do it more effectively, that is, managing to transport more information and more quickly.

To achieve this, the material developed by the researchers was crucial, made up of metal squares arranged on a plastic material: “which are associated with a bit ‘1’ or ‘0’ and can be programmed, as is done with a software “, he told ANSA Galdi. But the novelty does not consist in this, because the programmable metamaterials had already been obtained in 2014 by the Cui group. The novelty, observed Galdi, is that the new material can be programmed over time: “ie the bits can be reconfigured and passed from 1 to 0 more than a million times in a second” and this mechanism allows a series of interesting applications . For example, more effective wireless communication antennas, because it can transmit more information,

Thanks to the ability to be programmed, these materials, in the future, could also be equipped with Artificial Intelligence: “in this way – noted Galdi – could react to changes in the environment, learn based on what is happening around, and reconfigure” .

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