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    Quality Control and Waste Reduction in Ultra-High-Purity Gas Delivery Systems

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    Author
    Wu, Junsheng
    Issue Date
    2019
    Keywords
    adsorption
    cryogenic
    high-purity gases
    impurity drift
    moisture
    Advisor
    Shadman, Farhang
    
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    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    Today is the data age; tremendous amount of data is generated, stored, transferred, and computed every second. As the consequence of the rapidly growing data age, the semiconductor industry continues advancing, marching at the pace of Moore’s law. The number of transistors doubling every two years on a chip indicates the unique feature of semiconductor industry. It makes great challenges for the semiconductor devices and the associated production processes as the scaling-down continues. In order to meet the stringent processes requirements, the demands for UHP (ultra-high-purity) gases also increase. Ultra-high-purity (UHP) gases are widely used in semiconductor industry. They are also known as electronic specialty gases (ESGs) or electronic bulk gases when used in the processing of electronic materials. The ultra-high-purity is often defined in terms of impurity level or concentration less than 100 ppb for any volatile molecules, like moisture, which is almost the most common impurity and particulate concentration of size lager than 0.3 micrometer at less than 1 part per liter of gas under normal conditions. Most semiconductor processes are very sensitive to impurities in UHP bulk and processes gases, and a stable and well-controlled purity level is usually required at the POU (point of use) tools. Moisture, which is selected as the key impurity compound in our research, is one of the most common and difficult-to-handle impurities, due to its strong adsorption on various kinds of surfaces. It is very difficult to control moisture level variations at the POU because of two major factors: 1) Drift due to moisture preferential accumulation in the liquid phase in the source tank; 2) Changes due to adsorption / desorption on pipes and flow control devices, as well as variations in flow rate and pipes surrounding temperature. To resolve these two major issues, mathematical process models for cryogenic tanks and gas delivery pipes were developed. Thermodynamic behaviors for vapor and liquid phase impurity in the tank were studied in the tank model to predict the concentration of impurity coming out of the cryogenic tank. Traditional dispersion model was applied to simulate the impurity behaviors in the gas delivery pipes, and to predict the impurity concentration at the pipe outlet (or the POU). Tank-in-series model was introduced to represent the pipe and to mitigate impurity level variations at the POU. Two-tank system was used in the point of source instead of conventional single tank system, of which one was the fully new tank, the other was the partially used tank. By changing the mixing function, which is defined as the ratio of flow rate from the partially used tank to the overall flow rate coming from the two tanks, the mixed concentration as well as the concentration at the POU can be stabilized and well-controlled. Besides, two-tanks system brings in a lot of savings in liquid content in the cryogenic tanks. An associate control system was also designed. This system consists of two cryogenic tanks, two mass flow controllers (MFC), a gas delivery system, a real-time sensor for on-line measurement of impurities, and the auxiliary electronics for running the process simulator, data acquisition, and MFCs programing and control. The flow streams from the two tanks are controlled by two MFCs, then mixed and transported to the POU through a transport pipeline. The impurity level at the POU is monitored by an online sensor. The process simulator provides input to the MFC controller unit that adjusts the flow out of each MFC. Overall, the set-up provides a dynamic flow-mixing scheme run by the output from the process simulator. The system properties, operating conditions and purity requirements are all inputs to the process simulator. By controlling the mixing function, the concentration at the POU can be well controlled. In this dissertation, Chapter 1 is the introduction to the UHP gases and the semiconductor development trends. The experimental instruments as well as the technology used in the project are also included. Their operation principles are described in detail in Chapter 2. Chapter 3 analyzes the impurity drift and variations in UHP gas delivery systems. Chapter 4 provides the solution to the impurity level variations issue at the POU. Chapter 5 is the recommendations and future work.
    Type
    text
    Electronic Dissertation
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Chemical Engineering
    Degree Grantor
    University of Arizona
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