| AVS 63rd International Symposium & Exhibition | |
| Plasma Science and Technology | Thursday Sessions |
| Session PS-ThA |
| Session: | Plasma Chemistry and Plasma Surface Interactions |
| Presenter: | Meghali Chopra, The University of Texas at Austin |
| Authors: | M.J. Chopra, The University of Texas at Austin R.T. Bonnecaze, The University of Texas at Austin |
| Correspondent: | Click to Email |
Creating and optimizing plasma etch recipes for microelectronic and other nanostructured devices is costly and time consuming. Fully optimized plasma etch recipes can take several months to two years to create, which slows time to market. Here we introduce a method combining physics-based global plasma models, Bayesian statistics and experimental data to rapidly develop and optimize recipes for plasma etching. The method predicts optimal process windows with two- to three-fold fewer experiments than using factorial design of experiments. We first demonstrate this method for prediction of etch rates in CCP and ICP-RIE plasma reactors. These predictions are then successfully compared to synthetic and experimental data. We next use the method to determine the anisotropic etch rates through a single material including level set modeling. Lastly, we apply the method to the etch recipe development of a high aspect ratio trench through a multi-layer stack. Our results show that we can reduce three-fold the cost and time required to develop an etch recipe.