Efficient Numerical Methods for Stochastic Modeling of Optical Absorption in Solar Cells
Abstract
The objective of this research is to study computationally the optical absorption in GaAs-based quantum dot solar cells designed in ARL with the Maxwell electromagnetic theory to understand the following physical process: ¥ Enhancement of light trapping and electromagnetic field enhancement with meta-surfaces with possible random meta-atom scatterers, placed on the top side of the solar cells to produce maximal light absorption. The following issues will be investigated: ¥ Optical absorption limit and its relation to the correlation of random pattern. ¥ Optical absorption of different meta-surface patterns and optimization. Specifically, the following research on numerical methods will be conducted to solve the time dependent and time harmonic Maxwell equations under uncertainties: ¥ Efficient stochastic algorithms, including sampling high dimensional random spaces of the meta-surface configurations based on Karhunen-Lo�ve expansions for random meta-surfaces with special non-overlapping geometric constrains for the meta-atoms, gPC (generalized polynomial chaos) methods for solving the Maxwell equations for random meta-surfaces, and searching for the design parameters to achieve optimal optical absorptions. ¥ Frequency domain methods, gPC based stochastic volume integral equation for the time harmonic Maxwell equations for light absorption by rough meta-surfaces. ¥ Time domain methods, gPC based stochastic well-conditioned discontinuous Galerkin methods and NŽdŽlec finite elements for time dependent electromagnetic fields with arbitrary polarization and incident angles. The PI and one postdoctoral researcher and graduate students will be involved in this project. One summer month and 0.5 academic months per year are requested for the PI, and a postdoctoral support of 8 months per year is also requested.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 11, 2018
- Source ID
- W911NF1710368
Entities
People
- Wei Cai
Organizations
- Army Contracting Command
- Southern Methodist University
- United States Army