http://smartech.gatech.edu/handle/1853/5986 Established in 1901, Georgia Tech's School of Chemical & Biomolecular Engineering has a distinguished history of educating students who become leaders in industrial organizations and universities. Today, the School enrolls more than 800 students, and graduated 147 students from summer 2001 through spring 2002, awarding 126 bachelor's degrees, 6 master's degrees, and 15 doctoral degrees. Search the Channel search http://smartech.gatech.edu/simple-search http://smartech.gatech.edu/handle/1853/23049 Title: Effect of substrate-polymer interactions on polymer thin film dewetting <br/> <br/>Authors: Meredith, J. Carson <br/> <br/>Description: Issued as final report http://smartech.gatech.edu/handle/1853/23043 Title: Computer simulation of mixing and blending of Leu process tanks <br/> <br/>Authors: Forney, Larry <br/> <br/>Description: Issued as final report http://smartech.gatech.edu/handle/1853/22711 Title: In situ Sensing for Chemical Vapor Deposition Based on State Estimation Theory <br/> <br/>Authors: Xiong, Rentian <br/> <br/>Abstract: Chemical vapor deposition (CVD) is an industrially important process to deposit crystalline and amorphous thin films on solid substrates. In situ sensing for CVD is necessary for process monitoring, fault detection, and process control. The challenge of in situ sensing lies in the prohibitive environment of the CVD process. Optical sensors such as the reflectometer and the ellipsometer are the most promising sensors because they can be installed outside of the deposition chamber, and are sensitive and easy to implement. However, the optical sensors do not measure film properties directly. Mathematical methods are needed to extract film properties from indirect optical measurements. Currently the most commonly used method is least squares fitting. In this project, we systematically investigated in situ reflectometry data interpretation based on state estimation theory. Optical models for light reflection on both smooth and rough surfaces were studied. The model validation results indicated that the effective medium model is better than the scalar scattering model when the surface is microscopically rough. The analysis of the observability for the sensor models indicated that the linearized observability does not always guarantee the true observability of a nonlinear system. We studied various state estimators such as batch least squares fitting (BLS), recursive least squares fitting (RLS), extended Kalman filter (EKF), and moving horizon estimation (MHE). It was shown that MHE is the general least-squares-based state estimation and BLS, RLS, and EKF are special cases of MHE. To reduce the computational requirement of MHE, a modified moving horizon estimator (mMHE) was developed which combines the advantage of the computational efficiency in RLS and the a priori estimate in MHE. State estimators were compared in simulated film growth processes, including both process model mismatch and sensor model mismatch, and reflection of both single wavelength and dual wavelength. In the case of process model mismatch and reflection on a smooth surface, there exists an optimum horizon size for both RLS and mMHE, although mMHE is less sensitive to the horizon size and performs better than RLS at all horizon sizes. The estimate with dual wavelength is more accurate than that with single wavelength indicating that estimation improves with more independent measurements. In the case of reflection on a rough surface, RLS failed to give a reasonable estimate due to the strong correlation between roughness and the extinction coefficient. However, mMHE successfully estimated the extinction coefficient and surface roughness by using the a priori estimate. MHE is much more computationally intensive than mMHE and there is no significant improvement on the estimation results. In the case of sensor model mismatch, either state estimator gave a good result, although mMHE consistently gave a better estimate, especially at a shorter horizon size. In order to test the state estimators in a real world environment, we built a cold-wall low-pressure chemical vapor deposition testbed with an in situ emissivity-correcting pyrometer. Fully automatic data-acquisition and instrument-control software was developed for the CVD testbed using LabVIEW. State estimators were compared using two experimental reflectance data sets acquired under different deposition conditions. The estimated film properties are compared with ex situ ellipsometry and AFM characterization results. In all cases, mMHE consistently yielded better estimates for processes under quite different deposition conditions. This indicated that mMHE is a useful and robust state estimator for in situ sensor data interpretation. By using the information from both the process and the sensor model, one can obtain a better estimate. A good feature of mMHE is that it provides such a versatile framework to organize all these useful information and gives a user the opportunity to interact with fitting and make wise decisions in the in situ sensor data interpretation. http://smartech.gatech.edu/handle/1853/22706 Title: Use of Evaporative Fractional Crystallization in the Pretreatment Process of Multi-Salt Single Shell Tank Hanford Nuclear Wastes <br/> <br/>Authors: Nassif, Laurent <br/> <br/>Abstract: The purpose of the work described in this thesis was to explore the use of fractional crystallization as a technology that can be used to separate medium-curie waste from the Hanford Site tank farms into a high-curie waste stream, which can be sent to a Waste Treatment and Immobilization Plant (WTP), and a low-curie waste stream, which can be sent to Bulk Vitrification. The successful semi-batch crystallization of sodium salts from two single shell tank simulant solutions (SST Early Feed, SST Late Feed) demonstrated that the recovered crystalline product met the purity requirement for exclusion of cesium, sodium recovery in the crystalline product and the requirement on the sulfate-to-sodium molar ratio in the stream to be diverted to the WTP. In this thesis, experimental apparatus, procedures and results are given on scaled-down experiments of SST Early Feed for hot-cell adaptation along with operating parameters and crystallization mechanism studies on early feed multi-solute crystallization. Moreover, guidance is given regarding future steps towards adapting the technology to multi-salt crystallization kinetic parameter estimates and modeling. Crystallization, Evaporative Fractional Crystallization, Nuclear Waste Pretreatment, Cesium Removal, Hanford, SST Early and Late feed, Multi-solute, Multi-salts, Simulant Testing