A review of plasmonic wave generation: Materials, AI-based design approaches, and applications

Plasmonics, the study of collective oscillations of electrons at metal-dielectric interfaces, has become an emerging and fast-growing field that enables manipulation of electromagnetic waves at sub-wavelength scales. The ability to precisely design and control plasmonic modes is credited to developments in material engineering, precision fabrication, and computational modelling, which have redefined technologies for energy harvesting, medicine, communication, and defences. This review covers different plasmonic materials, including noble metals, semiconductors, graphene-based materials, and hybrid nanostructures, together with metamaterials used for plasmonic wave manipulation. The performance limitations of conventional metals, such as high energy losses and limited tunability, can be tackled using metamaterials through tailored electromagnetic responses and enhanced control of plasmonic wave propagation, confinement, and dispersion. Comparative discussions on plasmonic performance and material characteristics are also presented. In addition, deep learning and machine learning approaches for the design and optimization of plasmonic and metamaterial systems are discussed. The fundamentals, material developments, metamaterial-assisted plasmonic engineering, and AI-enabled approaches that shape the future of plasmonic technologies and applications are emphasized in this review.