@Article{CiCP-25-5,
author = {},
title = {Computational Optimal Design of Random Rough Surfaces in Thin-Film Solar Cells},
journal = {Communications in Computational Physics},
year = {2019},
volume = {25},
number = {5},
pages = {1591--1612},
abstract = {<p style="text-align: justify;">Random rough textures can increase the absorbing efficiency of solar cells
by trapping the optical light and increasing the optical path of photons. In this paper,
we are concerned with optimal design of random rough surfaces in thin-film solar
cells. We formulate the design problem as a random PDE constrained optimization
problem and employ gradient-based methods for solving the problem numerically. To
evaluate the gradient of the objective function, the Monte-Carlo method is used for
sampling the probability space and the adjoint state method is employed to calculate
the gradient at each sample. Numerical examples are shown to test the efficiency of the
proposed algorithm. It is demonstrated that optimally obtained random textures yield
an enormous absorption enhancement and a higher photon absorptance than that of
existing random textures.</p>},
issn = {1991-7120},
doi = {https://doi.org/10.4208/cicp.OA-2018-0013},
url = {https://global-sci.com/article/79934/computational-optimal-design-of-random-rough-surfaces-in-thin-film-solar-cells}
}