This talk will focus on the digital design of periodic and quasi-random nanostructures based on evolutionary algorithms and concurrent design methodologies. First, we will describe a machine-learning approach to design flat optics based on subwavelength plasmonic building blocks. Our lattice evolution algorithm can achieve desired optical responses by tuning the arrangement of the phase units on a discrete square lattice. Second, we will describe the concurrent deign of quasi-random silicon nanostructures that can manipulate light over a broad range of wavelengths and collection angles. We will discuss how wrinkle lithography provides a feasible method to realize quasi-random structures and how rapid optimization is possible for broadband light trapping. For both classes of nanostructures, we will describe prospects for scaling their production.

Evolutionary and concurrent design of photonic nanostructures

255th National Meeting (2018)

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