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Suggested Citation:"FINDINGS." National Research Council. 1996. Database Needs for Modeling and Simulation of Plasma Processing. Washington, DC: The National Academies Press. doi: 10.17226/5434.
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EXECUTIVE SUMMARY 1 Executive Summary The 1991 National Research Council (NRC) report Plasma Processing of Materials: Scientific Opportunities and Technological Challenges1 included a projection that worldwide semiconductor sales would double from $50 billion in 1990 to $100 billion in 1995. In fact, total sales worldwide for semiconductors passed $140 billion during 1995, nearly triple the 1990 level.2 Companies that supply plasma equipment to the semiconductor industry have experienced similar, if not greater, rates of growth. Plasmas in one form or other are used in about 30% of all semiconductor manufacturing processing steps, and about the same fraction of processing equipment is plasma- based in a typical microelectronics fabrication facility.3 An important trend accompanying this growth in the industry is the fact that the capital cost of constructing a new microelectronics fabrication facility is similarly escalating and is now on the order of $1 billion or more.4 Estimates are that over 60% of this capital cost is for processing equipment, including plasma equipment. Processing equipment design, optimization, and control therefore take on added importance, because equipment depreciation accounts for a significant part of the price of a chip. In spite of its high cost and technical importance, plasma equipment is still largely designed empirically, with little help from computer simulation. Plasma process control is rudimentary. Optimization of plasma reactor operation, including adjustments to deal with increasingly stringent controls on plant emissions, is performed predominantly by trial and error. There is now a strong and growing economic incentive to improve on the traditional methods of plasma reactor and process design, optimization, and control. An obvious strategy for both chip manufacturers and plasma equipment suppliers is to employ large-scale modeling and simulation. The major roadblock to further development of this promising strategy is the lack of a database for the many physical and chemical processes that occur in the plasma and especially at surfaces. Although a complete set of data for all gas phase and surface processes for all species present in the plasma is not necessary for many applications, the current lack of detailed information concerning the vast majority of processes and species is the major factor limiting the effectiveness of models. Given the reality of inevitably limited resources, and the often considerable investments that must be made to measure and/or compute collision cross sections, reaction rate coefficients for gas phase reactions, and surface chemical rates at surfaces exposed to plasma, some priorities must be established. These priorities are discussed below, and the report's recommendations on priorities constitute one of the main results of the study. FINDINGS 1. The integrated circuit (IC) manufacturing industry remains in its historical pattern of rapid technological change, and this pattern has begun to seriously challenge plasma equipment suppliers to continue the trend toward ever higher performance/cost ratios. Plasma processing tools are, in most cases, designed and optimized empirically. Real-rune control of plasma processes has not been adopted by the industry. Further improvements in performance by means of empirical adjustments will soon reach a point of diminishing returns, if they have not already. 2. Control of processes in plasma reactors must occur on length scales that range from tens of angstroms to tens of centimeters and time scales that range from seconds to tens of hours. Loss of control at any point in this spectrum of length and time scales can result in reduced yields of components and therefore significant economic losses. For example, precise control of transistor gate and metal wiring levels across the entire chip is necessary to manufacture microprocessors at the highest speeds. Loss of this control over etching precision produces slower microprocessors and a loss of hundreds of dollars per chip. Obviously, across-wafer control is equally important to maintain high yields and therefore high profitability.

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In spite of its high cost and technical importance, plasma equipment is still largely designed empirically, with little help from computer simulation. Plasma process control is rudimentary. Optimization of plasma reactor operation, including adjustments to deal with increasingly stringent controls on plant emissions, is performed predominantly by trial and error. There is now a strong and growing economic incentive to improve on the traditional methods of plasma reactor and process design, optimization, and control. An obvious strategy for both chip manufacturers and plasma equipment suppliers is to employ large-scale modeling and simulation. The major roadblock to further development of this promising strategy is the lack of a database for the many physical and chemical processes that occur in the plasma. The data that are currently available are often scattered throughout the scientific literature, and assessments of their reliability are usually unavailable.

Database Needs for Modeling and Simulation of Plasma Processing identifies strategies to add data to the existing database, to improve access to the database, and to assess the reliability of the available data. In addition to identifying the most important needs, this report assesses the experimental and theoretical/computational techniques that can be used, or must be developed, in order to begin to satisfy these needs.

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