To design and analyze chemical vapor deposition (CVD) reactors, computer models are regularly utilized. The foremost aim of this thesis research is to understand how thin film uniformity can be controlled in a CVD reactor. A complete understanding of chemical reactions that take place both in gas phase and at the deposition surface is required to predict thin film properties such as growth rate and composition precisely, however, deposition rates and surface topography can be determined by the arrival flux of reactants in a mass-transfer limited regime. In order to understand experimental thickness and roughness uniformity, a predictive model has been developed to study the fluid dynamic effect on thin film growth in a horizontal type reactor using velocity, temperature, pressure and viscosity as tunable parameters upon which velocity profiles within a CVD reactor have been evaluated using computational fluid dynamic (CFD) calculations. Through this predictive model, it is shown that fluid velocity is the major variable contributing to transverse roll cell formation compared to temperature and pressure gradients present during thin film deposition in a meso-scale CVD reactor. These results provide a physical insight regarding improved reactor operation conditions that influence uniformity.

Today, plasma-enhanced chemical vapor deposition (PECVD) remains the dominant processing method for the manufacture of silicon thin films due to inexpensive production and low operating temperatures. Nonetheless, thickness non-uniformity continues to prevent the deposition of high quality thin film layers across large wafer substrates; thickness deviations up to 20% are typical for 200 mm and above wafers. Regardless of industry, be it solar cell production or microelectronic devices, the demand for densely packed die with high quality creates a need for improved modeling and operational strategies. Over the past two decades, a number of research groups have built microscopic models for thin film growth, as well as macroscopic reactor models to approximate the gas phase reaction and transport phenomena present within PECVD systems. Unfortunately, many of the proposed modeling and simulation techniques have been overly simplified in order to reduce computational demands, or fail to capture both the macro- and microscopic domains simultaneously. In order to address persistent issues related to thickness non-uniformity in silicon processing, advanced multiscale models are needed. Motivated by these considerations, novel reactor modeling and operational control strategies are developed in this dissertation. Specifically, a macroscopic reactor scale model is presented which captures the creation of a radio frequency (RF) plasma, transport throughout the reactor domain, and thirty-four dominant plasma-phase reactions. In Chapters 2 and 3, the gas-phase dynamics are approximated using a first principles-based model, whereas the latter half of this dissertation relies on a computational fluid dynamics approach. At the microscopic scale, the complex particle interactions that define the growth of a-Si:H thin film layers are tracked using a hybrid kinetic Monte Carlo algorithm. These scales are linked via a dynamic boundary condition which is updated at the completion of each time step. A computationally efficient parallel programming scheme allows for significantly shortened computational times and solutions to previously infeasible system sizes. Transient batch deposition cycles using the aforementioned multiscale model provide new insight into the operation of PECVD systems; spatial non-uniformity in the concentration of SiH3 and H above the substrate surface is recognized as the primary mechanism responsible for non-uniform thin film product thicknesses. Two key modes are identified to address the aforementioned non-uniformity: (1) run-to-run control of the wafer substrate temperature through the adaptation of an exponentially-weighted moving average algorithm, and (2) the design of new CVD geometries which minimize spatial variations in the concentration of deposition species. These efforts have resulted in optimized PECVD showerhead designs and spatial temperature profiles which limit the thin film thickness non-uniformity to within 1% of the product specification.

Presents an extensive, comprehensive study of chemical vapor deposition (CVD). Understanding CVD requires knowledge of fluid mechanics, plasma physics, chemical thermodynamics, and kinetics as well as homogenous and heterogeneous chemical reactions. This text presents these aspects of CVD in an integrated fashion, and also reviews films for use in integrated circuit technology.

Computational fluid dynamics (CFD) modeling is used to simulate chemical vapor deposition (CVD) of silicon carbide (SiC), a wide-band gap semiconductor with a high breakdown field. The effects on SiC CVD of precursor concentration, flow rate, temperature, pressure, heat transfer and reactor geometry are investigated. Also demonstrates the possibilty of doping SiC with solid source vanadium during CVD growth of SiC epitaxial layers.

This work describes the development of a mathematical model of ahigh-pressure chemical vapor deposition (HPCVD) reactor and nonlinearfeedback methodologies for control of the growth of thin films in thisreactor. Precise control of the film thickness and composition is highlydesirable, making real-time control of the deposition process veryimportant. The source vapor species transport is modeled by the standardgas dynamics partial differential equations, with species decomposition reactions, reduced down to a small number of ordinary differential equationsthrough use of the proper orthogonal decomposition technique. This systemis coupled with a reduced order model of the reactions on the surfaceinvolved in the source vapor decomposition and film deposition on thesubstrate wafer. Also modeled is the real-time observation technique usedto obtain a partial measurement of the deposition process. The utilization of reduced order models greatly simplifies the mathematical formulation of the physical process so it can be solved quickly enough to beused for real-time model-based feedback control. This control problem isfairly complicated, however, because the surface reactions render the modelnonlinear. Several control methodologies for nonlinear systems are studiedin this work to determine which performs best on test examples similar tothe HPCVD problem. One chosen method is extended to a tracking control toforce certain film growth properties to follow desired trajectories. Thenonlinear control method is used also in the development of a stateestimator which uses the nonlinear partial observation of the nonlinearsystem to create an estimate of the actual state, which the feedback controlformula then can use to guide the HPCVD system. The nonlinear trackingcontrol and estimator techniques are implemented on the HPCVD model and theresults analyzed as to the effectiveness of the reduced order model andnonlinear control.

Facilitated by the increasing importance and demand of semiconductors for the smartphoneand even the automobile industry, thermal atomic layer deposition (ALD) has gained tremendous industrial interest as it offers a way to efficiently deposit thin-films with ultra-high conformity. It is chosen largely due to its superior ability to deliver ultra-conformal dielectric thin-films with high aspect-ratio surface structures, which are encountered more and more often in the novel design of metal-oxide-semiconductor field-effect transistors (MOSFETs) in the NAND (Not-And)-type flash memory devices. Based on the traditional thermal ALD method, the plasma enhanced atomic layer deposition (PEALD) allows for lower operating temperature and speeds up the deposition process with the involvement of plasma species. Despite the popularity of these two methods, the development of their operation policies remains a complicated and expensive task, which motivates the construction of an accurate and comprehensive simulation model. A series of studies have been carried out to elucidate the mechanisms and the conceptof the PEALD process. In particular, process characterization focuses on the development of a first-principles-based three-dimensional, multiscale computational fluid dynamics (CFD) model, together with reactor geometry optimizations, of SiO2 thinfilm thermal atomic layer deposition (ALD) using bis(tertiary-butylamino)silane (BTBAS) and ozone as precursors. Also, a comprehensive multiscale computational fluid dynamics (CFD) model incorporating the plasma generation chamber is used in the deposition of HfO2 thin-films utilizing tetrakis(dimethylamido) hafnium (TDMAHf) and O2 plasma as precursors. Despite the great deal of research effort, ALD and PEALD processes have not been fullycharacterized from the view point of process control. This study aims to use previously developed multiscale CFD simulation model to design and evaluate an optimized control scheme to deal with industrially-relevant disturbances. Specifically, an integrated control scheme using a proportional-integral (PI) controller and a run-to-run (R2R) controller is proposed and evaluated to ensure the deposition of high-quality conformal thin-films. The ALD and PEALD processes under typical disturbances are simulated using the multiscale CFD model, and the integrated controllers are applied in the process domain. Using the controller parameters determined from the open-loop results, the developed integrated PI-R2R controller successfully mitigates the disturbances in the reactor with the combined effort of both controllers.