Plasmonics for sustainable technologies and green energy: from advancing materials to machine-learning assisted designs (Plenary Presentation)

The recent advent of robust, refractory (having a high melting point and chemical stability at temperatures above 2000°C) photonic materials such as plasmonic ceramics, specifically, transition metal nitrides (TMNs), MXenes and transparent conducting oxides (TCOs) is currently driving the development of durable, compact, chip-compatible devices for sustainable energy, harsh-environment sensing, defense and intelligence, information technology, aerospace, chemical and oil & gas industries. These materials offer high-temperature and chemical stability, great tailorability of their optical properties, strong plasmonic behavior, optical nonlinearities, and high photothermal conversion efficiencies. This lecture will discuss advanced machine-learning-assisted photonic designs, materials optimization, and fabrication approaches for the development of efficient thermophotovoltaic (TPV) systems, lightsail spacecrafts, and high-T sensors utilizing TMN metasurfaces. We also explore the potential of TMNs (titanium nitride, zirconium nitride) and TCOs for switchable photonics, high-harmonic-based XUV generation, refractory metasurfaces for energy conversion, high-power applications, photodynamic therapy and photochemistry/photocatalysis. The development of environmentally-friendly, large-scale fabrication techniques will be discussed, and the emphasis will be put on novel machine-learning-driven design frameworks that leverage the emerging quantum solvers for meta-device optimization and bridge the areas of materials engineering, photonic design, and quantum technologies.