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Research Results on Chemical Vapor Deposition of Metal Oxide Thin Films Key publications:

m = 5. j = 8. y. y 6. y 5. y 7. y 4. y 1. y 0. y 8. y 2. y 3. t. Research program

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Research Results on Chemical Vapor Deposition of Metal Oxide Thin Films Key publications:

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  1. m = 5 j = 8 y y6 y5 y7 y4 y1 y0 y8 y2 y3 t Research program We apply the systems engineering approach to materials synthesis and macromolecular structure. Mathematical models are not accurate enough for a purely model-based design. Instead, we combine mechanistic modeling together with statistics and experimentation. In the group we develop general methodology and algorithms, and then apply the techniques in a number of specific applications. Martha Grover, Associate ProfessorSchool of Chemical & Biomolecular EngineeringGeorgia Institute of TechnologyAtlanta, GA USA Research Results on Chemical Vapor Deposition of Metal Oxide Thin Films Key publications: R. Xiong and M. A. Grover, “In situ estimation of thin film growth rate, complex refractive index, and roughness during chemical vapor deposition using a modified moving horizon estimator,” Journal of Applied Physics, 103(12) 124901 (2008). P. J. Wissmann and M. A. Grover, “A new approach to batch process optimization using experimental design,” AIChE Journal, 55(2), 342-353 (2009). Research support: National Science Foundation CAREER award “A Systems Approach to Materials Processing Experimental Design for Process Optimization In Situ Optical Sensing and Robust Estimation Motivation Interpreting optical sensor data is a major hurdle to real-time control of thin films. • Motivation • Models can be helpful in finding best process, but they are not completely accurate • Models should be used to design the next experiment. f(x) UB H LB min • Research partners needed • Modeling of metal nanoparticle nucleation on surfaces • Expertise in robust process design • Experimental data with in situ optical measurements of surfaces • Other applications in materials processing that could benefit from the “systems approach” • Conclusions • Models can be used to determine which process settings could be optimal (based on statistical data analysis) • The next experiment should be performed in this region of potential optima. • Research facilities available • In Professor Grover’s lab • Chemical vapor deposition system (custom built) • Atomic force microscope (Molecular Imaging) • Shared user facilities at Georgia Tech (for fee) • Electron microscopy center • Microelectronics Research Center • Marcus Nanotechnology Research Center x • Conclusions • Moving horizon estimation combines models with knowledge of uncertainties. • MHE is more robust than the current approach based on fitting an optical model.

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