Robust nanoscale patterns for thin film solar cells using inverse optimization of nonuniformly sampled absorption spectrum

This paper outlines several techniques for systematic and efficient optimization as well as sensitivity assessment to fabrication tolerances of surface texturing patterns in thin film amorphous silicon (a-Si) solar cells. The aim is to achieve maximum absorption enhancement. We report the joint optimization of several geometrical parameters of a three dimensional lattice of periodic square silver nanoparticles, and an absorbing thin layer of a-Si, using constraint optimization tools and numerical FDTD simulations. Global and local optimization methods, such as the Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFGS-QN) and Simulated Annealing (SA) are employed concurrently for solving the inverse near field radiation problem. The design of the silver patterned solar panel is optimized to yield maximum average enhancement in photon absorption over the solar spectrum. The optimization techniques are expedited and improved by using a novel nonuniform adaptive spectral sampling technique. Furthermore, the sensitivity of the optimally designed parameters of the solar structure is analyzed by postulating a probabilistic model for the errors introduced in the fabrication process. Monte Carlo (MC) simulations and Unscented Transform (UT) techniques are used for this purpose.