Extensible modelling framework for nanostructured III-V solar cells

• Main Authors: Fuhrer, M. F., Adams, J. G. J., Barnham, K. W. J., Browne, B. C., Chan, N. L. A., Farrell, D. J., Hirst, L., Kan-Hua Lee, Ekins-Daukes, N. J., Ogura, A., Yoshida, K., Okada, Y.
• Format: Conference Proceeding
• Language: English
• Subjects: Computational modeling; Materials; Nanostructures; Photonic band gap; Photovoltaic cells; Photovoltaic systems
• ISSN: 0160-8371
• DOI: 10.1109/PVSC.2011.6186484

The use of nanostructures has been shown to provide practical performance enhancements to high-efficiency III-V based solar cells by permitting sub-bandgap tuneable absorption. Nanostructures present a fertile ground for new solar cell technologies, and an improved understanding of fundamental processes may even lead to functional intermediate band and hot-carrier devices. As the fundamental processes occurring in nanostructured solar cells are complex and not easily observable, the study of such devices often requires the analysis of data derived from experimental characterisation techniques using computer models. Models exist for many individual aspects of these nanostructured solar cells, but as yet no comprehensive modelling solution exists. We report on our progress to produce an extendable abstract modelling framework written in the high-level programming language Python. The framework is intended for deployment both as back-end to a variety of interfaces for specialised modelling purposes, and as a library of methods and classes for use at source-code level, allowing adaptation to a wide variety of research problems. Significant code abstraction, such as sequestering complex materials parameterisation behind a simple material object allows simple scripts to do complex work. Modules underway cover several device simulation tiers, including fundamental processes such as quantum well and dot absorption and recombination, as well as device level simulations such as spatial bias mapping using equivalent circuits and multijunction IV characteristics. These simulations correlate with and derive experimental data from characterisation techniques including spatially and temporally resolved electro- and photoluminescence spectroscopy, fourier-transform infrared spectroscopy, and others.