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Database Needs for Modeling and Simulation of Plasma Processing (1996)

Chapter: CHIP MANUFACTURER PERSPECTIVES

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Suggested Citation:"CHIP MANUFACTURER PERSPECTIVES." 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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Page 9
Suggested Citation:"CHIP MANUFACTURER PERSPECTIVES." 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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Page 10

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INDUSTRIAL PERSPECTIVES 9 combinations) will be most effective in controlling the process. The current approach involves the use of empirical correlation techniques such as response surface methodology, but these have limited validity outside the conditions under which the data were obtained. Also, model-based process control offers the opportunity to incorporate what is known about the process dynamics into the process control scheme. Figure 1.2 Coupled, comprehensive models. Databases and diagnostics are important at all levels. (Courtesy of A. Voshchenkov, Lam Research Corporation.) A set of integrated comprehensive models that are envisioned by plasma tool suppliers7 is shown in Figure 1.2. This set includes physical models to predict transport and electromagnetic phenomena; chemical models for both gas phase and surface chemistry; integrated system models to enable predicting what is happening at the wafer surface in terms of macroscopic phenomena at the tool scale; and finally empirical sensor-based models for real-time, adaptive process control. Process diagnostics play a key role in all of these models, from validation of the physical and chemical models to helping to identify and develop the appropriate sensors for process control applications. The models envisioned in Figure 1.2 are termed "comprehensive," but it is recognized that hardware and chemistry process models need not capture every detail in order to be useful. Convenient user interfaces, and the development of compatible modeling modules that can be integrated into evolving simulation codes, are the keys to exploiting current advances without limiting future developments as they become available. Databases are the subject of other chapters in this report, and as illustrated in Figure 1.2, they play an important role in all of the subsets of the comprehensive model. CHIP MANUFACTURER PERSPECTIVES The semiconductor industry has established the necessity of plasma processing for both deposition and etching of materials. These applications include highly anisotropic etching of deep trenches in silicon, highly selective etching of polysilicon gates on very thin gate oxides, and blanket photoresist removal. Plasma deposition has been applied to metals, to barrier layers between films that might otherwise interdiffuse and/or react, and to insulators such as silicon dioxide and silicon nitride. In addition, plasmas are often used to clean surfaces of debris and other unwanted materials. From the point of view of the chip manufacturer, the development of plasma processes has been chiefly an experiment-driven procedure, and this has carried the industry to working with submicron features.

INDUSTRIAL PERSPECTIVES 10 Advances in very large scale integration (VLSI) have brought the industry to the point that small differences in process precision can have a large economic impact. An example is apparent in the area of microprocessor manufacturing. After fabrication, microprocessors today are sorted based on the maximum speed at which they will operate. This sorting is determined primarily by the precision in etching the gate and metal wiring levels. Relatively small losses in the precision of these etching steps result in slower devices. (It should be noted that it can be difficult to separate the roles of lithography and etching in this loss of precision. Sometimes it is possible to compensate for problems in lithography with alterations in the etching step.) The sales price of a single chip can differ by hundreds of dollars between the fastest speed category and a slower one. Control of processes on the feature length scale, across the entire wafer, must be maintained over time scales that can range from seconds to many hours. During etching of a single wafer, short transients that might last on the order of seconds during the start or end-point of an etch can influence processing characteristics. In addition, variations on time scales of tens of minutes due to, for example, relatively slow changes in tool wall temperature, can be important. On even longer time scales, wall surface deposits slowly build up and must eventually be removed in a cleaning step. These are some of the major forces driving the industry to better understand and control plasma processes. The industry is looking to modeling and simulation to help gain this understanding. Another area of concern for chip manufacturers is in the so-called back end of the line (BEOL) where the metal interconnects are formed. As noted in Table 1.1, the number of these interconnect levels is increasing. At the same time, the defect density must be reduced. However, the danger of introducing device-threatening contamination and/or damage during these steps increases as the number of processing steps increases with the number of levels of metalization. Problems such as this have prompted interest in contamination-free manufacturing (CFM). Plasmas are acknowledged generators of particles, both from chamber walls and from processes occurring within the plasma. Particles become charged in the plasma and are often trapped above the wafer. An important opportunity exists for plasma modeling and simulation to contribute to better understanding and eventual control of particles in plasma process equipment. Improvements in plasma tool design and operation are needed to minimize particle nucleation, growth, and eventual deposition on the wafer. Models for plasma processes today exist largely at two levels, based on the two major length scales in the technology: the microfeature level (~ 0.1-10 µm) and the tool level (~ 1-100 cm). However, between the microfeature level and the tool level is a mid-scale level that involves patterns of features on wafers, the edge region of the wafer, and so on. This mid-scale level is on the order of 0.1 mm to 1 cm, and to date it has received less attention from the modeling and simulation community. However, issues associated with a dependence of etching characteristics on the local pattern (such as the density of lines) are of considerable practical importance to the chip manufacturer. Connections between the mid-level scale and the tool scale must be developed in order to address these concerns. In addition, many important phenomena occur on the molecular scale (~ 1-100 Å). Modeling and simulation are needed for developing processes that produce the desired uniform results. There is a clear need to minimize the time it takes to develop a process for a new pattern, minimizing the feature size and "adjacency" problems noted above. Cost is increasingly important. Tool productivity in terms of cost per operation is key to competitiveness. Reduction of the number and complexity of experiments through simulation is increasingly attractive since engineering experiments have become very costly. Achieving these efficiencies requires valid models, access to model data, and calibration techniques. In order to involve plasma process engineers in the use of plasma equipment models, it is important that such models be relatively fast and easy to use. Multidimensional simulations tend to be relatively time-consuming (a few to several tens of hours), even on fast workstations. This is probably too slow for the process engineer. In addition, user interfaces are now relatively crude. One option, therefore, is to develop less comprehensive but faster running models that are coupled to an etch profile simulator. With a convenient user interface, this combination of relatively simple models might be a useful aid to the plasma

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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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