Structural and Multidisciplinary Optimization

, Volume 50, Issue 3, pp 367–382

Topology optimization for light-trapping structure in solar cells



The limitation associated with the low optical absorption remains to be the main technical barrier that constrains the efficiency of thin–film solar cells in energy conversion. Effective design of light-trapping structure is critical to increase light absorption, which is a highly complex phenomenon governed by several competing physical processes, imposing a number of challenges to topology optimization. This paper presents a general, yet systematic approach exploiting topology optimization for designing highly efficient light-trapping structures. We first demonstrate the proposed approach using genetic algorithm (GA) based non-gradient topology optimization (NGTO), which is robust for achieving highly-efficient designs of slot-waveguide based cells with both low-permittivity and high-permittivity scattering material at single wavelength or over a broad spectrum. The optimized light-trapping structure achieves a broadband absorption efficiency of 48.1 % and more than 3-fold increase over the Yablonovitch limit. The fabrication feasibility of the optimized design is also demonstrated. Next, the gradient topology optimization (GTO) approach for designing light-trapping structure is explored based on the Solid Isotropic Material with Penalization (SIMP) method. Similar designs are obtained through both GA based NGTO and SIMP based GTO, which verifies the validity of both approaches. Insights into the application of both approaches for solving the nanophotonic design problem with optimization nonlinearity are provided.


Topology optimization Light-trapping structure Nanophotonic design Genetic algorithm SIMP Solar cell 

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Shuangcheng Yu
    • 1
  • Chen Wang
    • 1
  • Cheng Sun
    • 1
  • Wei Chen
    • 1
  1. 1.Department of Mechanical EngineeringNorthwestern UniversityEvanstonUSA

Personalised recommendations