CDS&E: Elucidating and Controlling the Spectral, Spatial and Temporal Responses of Plasmonic Nanostructures based on a Data-Driven Approach

点击翻译按钮获取中文摘要

NONTECHNICAL SUMMARYPlasmonic nanostructures are tiny particles made of noble metals, such as gold and silver. They can concentrate light into extremely small dimensions and significantly enhance the light intensity. The unique properties of plasmonic nanostructures have produced many applications, including solar energy harvesting, biomedical sensing, diagnostics and therapy. The objective of this project is to establish a framework based on deep learning, a subset of artificial intelligence, to elucidate and control the physical properties of plasmonic nanostructures by fusing theory, computation, deep learning algorithms, and experiments. Recent work has demonstrated that deep learning can discover the highly complicated and non-intuitive relationships between photonic structures and their properties through extensive data, overcoming the limitations of conventional analytical and numerical methods. To further advance this emergent field, the PI will enhance the capability of deep learning models by considering more degrees of freedom, such as electric and magnetic field distributions, time-dependent responses, and multi-physics processes in plasmonic nanostructures. The predictions of the deep learning models will be directly validated by experiments, which will provide important feedback and additional data to improve the model capability.This award also supports a comprehensive education plan that will include innovative activities at the Grade 7-12, undergraduate, and graduate levels. Special efforts will be made to attract and educate students from underrepresented ethnic/racial and gender groups, and broaden their knowledge in photonics, materials science, applied physics, and artificial intelligence. Part of the research findings will be used to develop new course materials to introduce the latest development in the fields to the students at Northeastern University. The PI will also create a new outreach activity, in which local high-school students will learn about optical properties of plasmonic nanostructures.TECHNICAL SUMMARYThis award supports computational and experimental research aimed at effectively harnessing light-matter interactions in the spectral, spatial, and temporal domains by leveraging advanced deep learning techniques and using plasmonic nanostructures as the platform. The project consists of three research thrusts: (1) developing a general approach to model the spatial distribution of the electric and magnetic fields of complex plasmonic nanostructures with high efficiency, accuracy and fidelity, which is critical to engineer nonlinear optical effects at user-defined wavelengths; (2) investigating the hot-electron-induced temporal responses and the resulting transient multi-physics processes of plasmonic nanostructures by integrating deep learning, Fourier transform and governing equations; and (3) fabricating plasmonic nanostructures with canonical and freeform shapes, and experimentally characterizing them using advanced microscopy and spectroscopy techniques. The data-centric framework enabled by deep learning will help to uncover the physics behind plasmonic nanostructures and other photonic designs. It will provide deep insights into a series of fundamental problems, such as topology, symmetry, and non-equilibrium dynamics, with fine spatial and temporal resolution.This award also supports a comprehensive education plan that will include innovative activities at the Grade 7-12, undergraduate, and graduate levels. Special efforts will be made to attract and educate students from underrepresented ethnic/racial and gender groups, and broaden their knowledge in photonics, materials science, applied physics, and artificial intelligence. Part of the research findings will be used to develop new course materials to introduce the latest development in the fields to the students at Northeastern University. The PI will also create a new outreach activity, in which local high-school students will learn about optical properties of plasmonic nanostructures.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.