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Nontechnical Description This project will focus on developing new materials that can be customized to control how light behaves, thereby advancing optical technologies for applications in communication, information technology, energy, and sensing. Conventional optical materials are not easily tuned or adapted, which limits their use in reconfigurable devices. This research will utilize MXenes, a family of two-dimensional structures engineered to reflect, absorb, or guide light in precise ways. By combining advanced material-making, experimental testing, and computer modeling, the team will establish a novel design framework for producing customizable materials with exceptional optical properties. The framework will also include new digital tools for predicting materials behavior and minimizing trial-and-error during development. In addition to the research, the project will offer interdisciplinary training for graduate and undergraduate students and contribute to public science education by developing open-access learning resources through nanoHUB.org. These initiatives will help prepare a new generation of researchers in the field of advanced photonic materials. Technical Description The project aims to develop optical materials that are customizable, dynamically tunable, scalable, and reconfigurable while exhibiting advanced light-matter interactions, such as plasmonic behavior, epsilon-near-zero (ENZ) response, hyperbolic dispersion, and strong nonlinear effects. Conventional photonic materials do not provide sufficient control or adaptability for emerging applications in photonics and optoelectronics. To tackle this challenge, the team will integrate synthesis, characterization, and computational modeling to understand and engineer how the composition, structure, and arrangement of MXenes impact their highly versatile optical and electronic properties. To create a predictive materials-by-design framework, the research will proceed with three objectives: (1) synthesize different MXene films and perform structural and optical characterization using tools such as ellipsometry, spectroscopy, and microscopy to generate a digital twin model, a physics-informed framework capable of predicting optical properties; (2) explore ordered and disordered hybrid MXene composites to achieve ENZ behavior and hyperbolic dispersion, using quantum emitters as probes for optical anisotropy; and (3) investigate all-optical and externally driven modulation through nonlinear optical measurements such as Z-scan and second-harmonic generation, incorporating these results into an expanded nonlinear digital twin. This combination of predictive modeling, experimental feedback, and dynamic control will enable the rational design of MXene-based materials for advanced optical applications. The outcomes will deepen understanding of structure-property relationships in 2D materials and establish scalable strategies for reconfigurable photonics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Up to $180K
2028-08-31
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