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A Parallel Detecting, Spectroscopic Ellipsometer for Intelligent Process Control of Continuously Deposited CIGS Films

Published online by Cambridge University Press:  10 February 2011

L. J. Simpson
Affiliation:
ITN Energy Systems, Inc., 12401 W. 49th Ave., Wheat Ridge, CO 80033
B. S. Joshi
Affiliation:
ITN Energy Systems, Inc., 12401 W. 49th Ave., Wheat Ridge, CO 80033
L. A. Gonzales
Affiliation:
ITN Energy Systems, Inc., 12401 W. 49th Ave., Wheat Ridge, CO 80033
J. Verley
Affiliation:
Physics Department, Colorado School of Mines, Golden CO 80401
T. E. Furtak
Affiliation:
Physics Department, Colorado School of Mines, Golden CO 80401
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Abstract

Advanced materials processing involves active control of fabrication and real-time monitoring of the final product. Sensors must be an integral part of the overall material processing system. ITN Energy Systems, Inc. and the Colorado School of Mines have developed a Parallel Detection, Spectroscopic Ellipsometer (PDSE) sensor for in-situ, real-time characterization and process control of multi-layered vapor deposited films. By measuring changes in the polarization state of reflecting light as a function of wavelength (250 to 5000 nm), the PDSE sensor determines the complex reflectance and/or the ellipsometric amplitude and phase. The PDSE provides cost-effective in-line sensing for film process control through detection of critical product variables that directly relate to film performance including: film thickness, optical excitation states, impurity concentrations, conductivity/resistance, intermixing at interfaces, microstructure, surface roughness, void fraction, defects, and grain size. The PDSE sensor is an optical probe with no moving parts that can measure the optical properties of thin films in as little as 3 msec with sensitivity to films less than a monolayer in thickness. We will use this PDSE system to provide real time process control of vapor deposited CuInGaSe2 (CIGS) films on a continuous flexible substrate. Initial results from CIGS films indicate that the PDSE has the sensitivity and accuracy to provide intelligent process control. The remaining challenge is to develop interpretive algorithms; the amount and quality of information required will determine their complexity. In addition, with the inception of in-situ, real-time monitoring, we hope to enable minimal data analysis approaches1 that provide extremely useful information with minimum interpretive algorithm development.

Type
Research Article
Copyright
Copyright © Materials Research Society 2000

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References

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