National Academies Press: OpenBook
Suggested Citation:"REFERENCES." National Research Council. 1996. Database Needs for Modeling and Simulation of Plasma Processing. Washington, DC: The National Academies Press. doi: 10.17226/5434.
Page 21
Suggested Citation:"REFERENCES." National Research Council. 1996. Database Needs for Modeling and Simulation of Plasma Processing. Washington, DC: The National Academies Press. doi: 10.17226/5434.
Page 22

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TOOL SCALE AND FEATURE SCALE MODELS 21 flow of information in the research community will be able to gain the most commercial advantage. Individual companies will no doubt develop proprietary databases and proprietary models of their tools and processes. However, this practice should not restrict the public flow of information to and from research teams. Toward this end, it seems desirable to establish at least one data center, in which database information, including collisional process characterization data and mechanism data, would be archived, evaluated, and disseminated. FINDINGS Models of low-temperature, nonequilibrium plasmas, especially for the description of physical phenomena, have developed rapidly in the last 5 years. Computing power per unit cost continues to increase rapidly. However, few of the currently available plasma models can be used easily by process engineers. Although attempts have been made to model plasmas with realistic chemistries, the parameter space that can be addressed is limited. Only a handful of studies have been made that attempt to validate models of plasma processes with industrially relevant chemistries. Models that attempt to link the relevant length scales (from tool scale to feature scale to atomic scale) are just now emerging. Simulations can be no more accurate than the data and assumptions on which they are based. The lack of fundamental data for the most important chemical species is the single largest factor limiting the successful application of models to problems of industrial interest. CONCLUSIONS 1. The main roadblock to development of plasma models that will have industrially important uses is the lack of fundamental data on collisional, reactive processes occurring in the plasma and on walls bounding the plasma. Among the most important missing data are the identities of key chemical species and the dominant kinetic pathways that determine the concentrations and reactivities of these key species. 2. The lack of a central location to collect, analyze, and disseminate the data that are currently available, or that will be available in the future, is limiting progress in the field. REFERENCES 1. See, for example, "Special Issue on Modeling Collisional Low-Temperature Plasmas," eds. M.J. Kushner and D.B. Graves, IEEE Trans. Plasma Sci . 19(2):61 (1991), and "Special Issue on Modeling Collisional Low-Temperature Plasmas," eds. J. Wu, M. Meyyappan, and D. Economou, IEEE Trans. Plasma Sci. (August 1995). 2. A. Krishnan, Workshop on Database Needs in Plasma Processing, Washington, D.C., April 1-2, 1995. 3. M.E. Barone and D.B. Graves, J. Appl. Phys. 77:12-65 (1995).


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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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