Fabrication of metasurfaces operating in the visible via nanotechnology and artificial intelligence
This thesis investigates the potential of flat optics as a solution to the problem of bulky and expensive optical components in producing lightweight and wearable optoelectronic devices. The research addresses scalability challenges in structure fabrication, design of broadband functionalities, and increasing operational and transmission efficiency in the visible range. It focuses on the experimental part of the challenge. The study evaluates various design approaches, including inverse designs using optimization techniques as well as the use of machine learning algorithms. The thesis aims to explore a path toward high efficiency, wide bandwidth, functional response, and scalable fabrication in flat optics using semiconductor nanostructures. The results demonstrate the potential of using semiconductor nanostructures to engineer efficient, scalable, and broadband optical components for light processing via flat surfaces.
Overview
Abstract
This thesis investigates the potential of flat optics as a solution to the problem of bulky and expensive optical components in producing lightweight and wearable optoelectronic devices. The research addresses scalability challenges in structure fabrication, design of broadband functionalities, and increasing operational and transmission efficiency in the visible range. It focuses on the experimental part of the challenge. The study evaluates various design approaches, including inverse designs using optimization techniques as well as the use of machine learning algorithms. The thesis aims to explore a path toward high efficiency, wide bandwidth, functional response, and scalable fabrication in flat optics using semiconductor nanostructures. The results demonstrate the potential of using semiconductor nanostructures to engineer efficient, scalable, and broadband optical components for light processing via flat surfaces.
Brief Biography
Fedor completed his bachelor's and master's degrees at Pisa University with a thesis on THz Near-field microscopy at National Enterprise for Nano-Science and Nano-Technology (NEST) of Pisa. He participated in organizing and teaching multiple stages addressed to high school students for preparation of the math and physics Olympiads.
Fedor joined Primalight in January 2018. Fedor’s research focuses on the fabrication of nanostructures for wavefront engineering and optical neural networks
