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 t m = 5 y 8 y 7 y 5 y 4 y 6 y 3 y 2 y 0 y 1 j = 8 y LB UB H min f(x) x Motivation • Models can be helpful in finding best process, but they are not completely accurate • Models should be used to design the next experiment. 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. Motivation Interpreting optical sensor data is a major hurdle to real-time control of thin films. Conclusions • Moving horizon estimation combines models with knowledge of uncertainties. • MHE is more robust than the current approach based on fitting an optical model. Martha Grover, Associate Professor School of Chemical & Biomolecular Engineering Georgia Institute of Technology Atlanta, GA USA Areas of expertise: systems engineering, materials processing Systems engineering: Process modeling Experimental design Sensing and estimation Applications in materials processing: Chemical vapor deposition Supercritical processing of metal nanoparticles Hyperbranched and crosslinking polymers Polymer nanoparticles Pharmaceutical crystallization 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” 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 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.

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

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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

m = 5

y7y5

j = 8y

min

f(x)

Motivation• Models can be helpful in finding best process, but they are not completely accurate• Models should be used to design the next experiment.

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.

MotivationInterpreting optical sensor data is a major hurdle to real-time control of thin films.

Conclusions• Moving horizon estimation combines models with knowledge of uncertainties.• MHE is more robust than the current approach based on fitting an optical model.

Martha Grover, Associate ProfessorSchool of Chemical & Biomolecular Engineering

Georgia Institute of TechnologyAtlanta, GA USA

Areas of expertise: systems engineering, materials processing

Systems engineering: Process modeling Experimental design Sensing and estimationApplications in materials processing:Chemical vapor depositionSupercritical processing of metal nanoparticles

Hyperbranched and crosslinking polymers

Polymer nanoparticlesPharmaceutical crystallization

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”

Research facilities availableIn 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

Research programWe 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.