Improving the predictive accuracy of fundamental plasma science
Abstract: Plasmas are found in a wide variety of natural and industrial settings. As such, the number of ‘free parameters’ available is vast. Research making use of a ‘standardized' plasma system, the Gaseous Electronics Conference Reference Cell,[1] has shown that subtle differences in two nominally identical systems can result in very difference results. For example, small impurities in the gas, such as different levels of H2O desorbing from chamber walls, can significantly shift the plasma potential. In fact, in the semiconductor industry, great efforts are taken to ‘season’ plasma chambers such that there is higher repeatability in process results. (In other words, billions of dollars are riding on repeatability, where the science of the process is not fully understood.) In this talk we will examine how one can disentangle the myriad physical and chemical processes that occur in many plasma systems, with the ultimate goal of improving the predictive accuracy of plasma simulations and disentangling the science behind plasma technology. The ultimate goal is to allow highly accurate predictive capability such that simulations can be used to economically develop new and useful technologies.
[1] J. K. Olthoff and K. E. Greenberg The Gaseous Electronics Conference RF Reference Cell—An Introduction, J. Res. Natl. Inst. Stand. Technol. 100, 327 (1995)
Bio: Prof Goeckner has been a faculty member of the University of Texas at Dallas since 1999. He is currently a professor in 5 departments, Physics, Electrical, Mechanical, Material Science and Science Education. Prior to joining UT Dallas, he worked in the Ginzton Research Center at Varian Associates - one of the original semiconductor related firms in the Bay Area. He received his PhD in Physics from the University of Iowa in 1990 and two bachelor degrees from Southern Illinois University, Mathematics (1982) and Physics (1983). He works in the broad area of Plasma Science, having been involved in a multitude of experimental and computational studies in the field.