Material-Centric Design of Advanced Electromagnetic Surfaces

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Advanced electromagnetic surfaces (AESs) have enabled the development of exciting new antennas and components for wireless communications owing to the ease with which they achieve extraordinary control of electromagnetic radiation. They are indispensable for realizing directive and adaptive antennas, which are cornerstones of future systems such as 5G. Despite advances in AES-derived antennas, their impact will not be fully realized until they simultaneously achieve greater bandwidth, reconfigurability, efficiency, and - critically - overall ease of design. The proposed research program puts forth a new material-centric design methodology for AESs that views them as materials that can be designed using material-informatic techniques. Currently, the design of AESs revolves around ad hoc, trial-and-error based design methods with lengthy design times spanning weeks or longer. The proposed approach harnesses advances in computing to augment the design of AESs using machine learning (ML). The proposed approach will build a large database of AES scatterer geometries characterized by effective material parameters, allowing techniques from material informatics to efficiently catalogue these designs. An ML-augmented design method will be trained from this data and used to quickly and accurately derive required AES scatterer geometries from a given set of specifications, cutting design times to hours or less. In the long term, the proposed research program aims to fundamentally change the way AESs are designed, and use this design paradigm to discover new AES capabilities. In the short term, the proposed research program aims to devise and implement new antenna architectures using the material-centric design approach. Three short term objectives are to: 1) devise ultra-wideband AESs operating in the millimetre-wave frequency range; 2) greatly improve the beam efficiency of AES-derived antennas, such as multi-beam satellite antennas; and 3) devise reconfigurable AESs using the proposed approach in order to achieve wideband, high efficiency, adaptive antennas. The proposed research program will have major impact on wireless communication systems and the field of AESs. AESs derived from the material-centric approach will achieve new levels of performance and functionality, thereby increasing the capacity of next-generation wireless communication systems to multi-gigabit-per-second levels. In the long run, the ML-augmented design approach will revolutionize the way AESs are designed by facilitating both their rapid synthesis and a platform for automated discovery of new AES materials. By hosting a public, ever-growing database of these materials, we also seek to drive change in their design through embracing an open approach. This fundamental new design paradigm will usher in a new generation of AES materials, discoveries, and designers for years to come.