THz waves amplified 30,000x by AI-designed nano-resonator for 6G revolution

Professor Hyong-Ryeol Park, leading a team of researchers from the Department of Physics at UNIST, has unveiled a groundbreaking technology capable of amplifying terahertz (THz) electromagnetic waves by a remarkable 30,000 times. This achievement, coupled with artificial intelligence (AI) based on physical models, is poised to revolutionize the commercialization of 6G communication frequencies.

In collaboration with Professor Joon Sue Lee from the University of Tennessee and Professor Mina Yoon from the Oak Ridge National Laboratory, the research team optimized the THz nano-resonator specifically for 6G communication using advanced optimization technology.

The research findings, published in the online version of Nano Letters, showcase the integration of AI learning based on a physical theoretical model. This enables the efficient design of THz nano-resonators on personal computers, a process previously time-consuming and resource-intensive, even with supercomputers.

Conducting THz electromagnetic wave transmission experiments, the team assessed the efficiency of the newly developed nano-resonator. The results were remarkable, with the electric field generated by the THz nano-resonator surpassing general electromagnetic waves by over 30,000 times. This represents a staggering efficiency improvement of over 300% compared to previously reported THz nano-resonators.

Professor Park explained the challenges faced in applying AI-based inverse design technology to the 6G communication frequency range (0.075–0.3 THz), given its much smaller scale, approximately one-millionth the size of the wavelength. The team overcame these challenges by combining a new THz nano-resonator with an AI-based inverse design method rooted in a physical theoretical model. This innovative approach allowed device optimization in under 40 hours, even on personal computers, compared to the previously required tens of hours for a single simulation or potentially hundreds of years for a single device optimization.

Young-Taek Lee, the first author of the study and a researcher in the Department of Physics at UNIST, emphasized the versatility of the optimized nano-resonator. He highlighted its implications for ultra-precise detectors, ultra-small molecular detection sensors, and bolometer studies. Lee stated, “The methodology employed in this study is not limited to specific nanostructures but can be extended to various studies using physical theoretical models of different wavelengths or structures.”

Professor Park underscored the importance of understanding physical phenomena in conjunction with AI technology, noting that while AI may seem like a panacea, a profound comprehension of physical phenomena remains crucial.

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