CASE STUDY: Computational Modeling for Semiconductor Wafer Processing
Optimizing semiconductor processing equipment is a complex task because of the large number of factors that contribute to the whole. It is first necessary to prepare and process materials and thin films, typically in a complex plasma environment. Next, manufacturers must deal with flowing and reacting gas mixtures, where it is vital to account for static or radio frequency (RF) electromagnetic fields and their couplings to the processing media. A wafer fab represents a true multi-scale problem because the reactors the wafers are placed in can be more than a meter wide, whereas molecular activity must be accounted for in the nanometer range. Further, time scales of interest can range from milliseconds to hours.
In the past, the design of chip manufacturing and processing equipment depended mostly on empirical methods due not only to the rapid pace of innovation but also to the incomplete understanding of the fundamental physical and chemical phenomena. Dedicated codes have been developed at universities, but they require users to master their specifics, and they also often use simplified geometries or analytical-approach models.
There is little doubt that computational modeling provides a better understanding of the manufacturing process and can significantly reduce overall development time and costs. Consider that even one component in a complex wafer fab can cost several thousand dollars. Without adequate modeling, finding a part that does the job exactly as required under complex chemistry environments, heat or electromagnetic field loads-and with the predicted final impact on process performance-is primarily trial and error. Not only do non-workable parts turn into expensive scrap, but it can take weeks to get such prototype parts made. With a good model, it's possible to test 10 or 20 cases in just days and thus get a new process online as quickly as possible.
Working with a HydraAt the TEL Technology Center in Albany, N.Y., our role is to develop new processes and hardware to meet future semiconductor manufacturing requirements. Working closely with process engineers, we bring the nano and macro scales together, and we have found that doing our job is simply not cost effective without modeling. Without simulation results, an equipment designer can't know where to start a development project or how to change tool components to satisfy new process or technology requirements.
However, a problem arose as we adopted a variety of simulation codes and methods for each manufacturing stage. For example, consider the use of hydrogen for the surface preparation and cleaning of silicon wafers and thin films (see Figure 1). The first area to study covers the electromagnetic (EM) interactions with the wafers and the processing materials. Previously, we studied what was going on with a commercial package dedicated to EM simulations. Next is the bulk plasma model, for which I was forced to use my own custom code. It is also necessary to develop a sheath model that examines the transport of the chemically active species during the manufacturing process, and here we typically worked with an analytical model. Finally, to look at the feature model that describes events at the molecular level, we again worked with my own code.
Finding a Single SolutionThis combination of different codes, platforms and operating systems was quite counterproductive, as were problems we experienced when moving data between these codes. In addition, a flexible simulation tool was needed to create novel technical solutions and implement new ideas in a reasonably short amount of time. I came to believe that it would be far more effective to use an all-in-one simulation package, and I embarked on a feasibility study to see to what extent I could perform plasma reactor simulations using COMSOL Multiphysics.
Future ModelingNow that I have completed the bulk-plasma and chemical-reaction model, it's time to include the full sheath and feature-level models. I hope to include even more of the phenomena that describe the process in full and will provide a self-consistent model solution. I am also reworking my first models to include other aspects and more complex geometries. COMSOL Multiphysics gives me one simulation environment for all the phenomena in my multi-scale and multi-physics systems.
For additional information regarding computational modeling, contact COMSOL, Inc., 1 New England Executive Park, Suite 350, Burlington, MA 01803; (781) 273-3322; fax (781) 273-6603; or visit www.comsol.com. TEL's website is located at www.tel.com.