261177 Control of Transparent Conducting Oxide Surface Morphology for Improved Light Trapping Using Wafer Grating and Model Predictive Control

Thursday, November 1, 2012: 3:15 PM
326 (Convention Center )
Jianqiao Huang1, Gerassimos Orkoulas2 and Panagiotis D. Christofides1, (1)Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA, (2)Chemical Engineering, University of California, Los Angeles, Los Angeles, CA

Thin-film silicon solar cells are currently among the most important and widely used solar cell systems and their share of the overall solar cell market is steadily increasing. Transparent Conducting Oxide (TCO) layers are an important component of thin film solar cell system. It has been demonstrated by many researches that the surface morphology, which is characterized by aggregate surface roughness and slope, has a crucial influence on the light trapping process and the conversion efficiency of thin film solar cell systems. Thus, it is very important to control the TCO surface morphology properties at desired values during the deposition process to improve the performance of thin film solar cells. This work focuses on the design of a feedback control system using both wafer grating and a model predictive controller to shape the surface morphology for improve solar cell performance. Specifically, a sinusoidal grated wafer is used for TCO thin film deposition process and a spatially distributed deposition rate profile is used to precisely control the TCO surface morphology during the deposition process. In this work, an Edwards-Wilkinson (EW) type equation is used to predict the process dynamics and the analytical solution of EW equation is derived as the basis of controller design. The model parameters of EW equations are identified by fitting the closed-form equation to open loop simulation data obtained from large-lattice kinetic Monte Carlo simulations. Finally, the controller is applied to a large scale kinetic Monte Carlo model of a TCO deposition process and the results demonstrate that the controller successfully regulates the surface morphology to desired values that lead to improved light trapping and solar cell performance.

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