(729a) Simulation and Control of Plasma-Enhanced Chemical Vapor Deposition (PECVD) Process for the Manufacturing of Silicon Thin Film Solar Cells
AIChE Annual Meeting
Thursday, November 20, 2014 - 3:15pm to 3:33pm
Solar energy is currently one of the most promising clean and sustainable energy sources, and plasma enhanced chemical vapor deposition (PECVD) is an emerging deposition technique used for the manufacturing of silicon thin film solar cells which are the most widely used solar cell systems. In a PECVD process, the silane and hydrogen gases are activated by collisions with plasma ions, and those activated species are transported to the substrate where thin film growth through surface reactions occur. Furthermore, the key benefit of using PECVD is in the low operational temperature allowing the deposition of temperature sensitive films and relatively high deposition rate reducing the processing time . However, the widespread application of PECVD is limited by the significant nonuniformity in the deposition rate along the spatial coordinate, particularly for a large-scale chamber. This effect leads to the production of thin film solar cells with low conversion efficiency due to undesired surface morphology characterized by aggregate surface roughness and slope. Motivated by this, the modeling of a PECVD process has been necessitated in an effort to control the surface morphology of thin films to desired constraints for enhanced solar cell conversion efficiency.
This work focuses on the simulation of a silicon thin film deposition process through PECVD and the design of a model predictive control scheme to improve solar cell performance. A sinusoidal grated wafer is used to achieve surface roughness within the range of the visible light spectrum, which is desired for optimal light trapping . Initially, a kinetic Monte Carlo (kMC) model is presented based on the solid-on-solid assumption to simulate the thin film growth process which consists of 4 microscopic processes associated with silyl radicals including physisorption, chemisorption, surface diffusion, and H-abstraction . The kMC simulation is regarded as a representation of a real PECVD process, and the system parameters used in the simulation are identified through the calibration of the simulation results with experimental data. Then, a reduced-order model is introduced to predict the dominant system dynamics of the silicon thin film growth computed by the kMC simulation, and is used for the design of a model predictive controller (MPC) . Finally, the closed-loop simulation results show that the production of the silicon thin film with a desired surface morphology that leads to improved light trapping efficiency is achieved by regulating the spatially distributed deposition rate through the proposed MPC scheme.
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