The continual increasing demands upon Plasma Etching systems to self-clean and continue Plasma Etching with minimal downtime allows for the examination of SiCN, SiO2 and SiN defectivity based upon Surface Scanning Inspection Systems (SSIS) wafer scan results. Historically all Surface Scanning Inspection System wafer scanning recipes have been based upon Polystyrene Spheres wafer deposition for each film stack and the subsequent creation of light scattering sizing response curves. This paper explores the feasibility of the elimination of Polystyrene Latex Sphere (PSL) and/or process particle deposition on both filmed and bare Silicon wafers prior to Surface Scanning Inspection System recipe creation. The study will explore the theoretical maximal Surface Scanning Inspection System sensitivity based on PSL recipe creation in conjunction with the maximal sensitivity derived from Bidirectional Reflectance Distribution Function (BRDF) maximal sensitivity modeling recipe creation. The surface roughness (Root Mean Square) of plasma etched wafers varies dependent upon the process film stack. Decrease of the root mean square value of the wafer sample surface equates to higher surface scanning inspection system sensitivity. Maximal sensitivity SSIS scan results from bare and filmed wafers inspected with recipes created based upon Polystyrene/Particle Deposition and recipes created based upon BRDF modeling will be overlaid against each other to determine maximal sensitivity and capture rate for each type of recipe that was created with differing recipe creation modes. A statistically valid sample of defects from each Surface Scanning Inspection system recipe creation mode and each bare wafer/filmed substrate will be reviewed post SSIS System processing on a Defect Review Scanning Electron Microscope (DRSEM). Native defects, Polystyrene Latex Spheres will be collected from each statistically valid defect bin category/size. The data collected from the DRSEM will be utilized to determine the maximum sensitivity capture rate for each recipe creation mode. Emphasis will be placed upon the sizing accuracy of PSL versus BRDF modeling results based upon automated DRSEM defect sizing. An examination the scattering response for both Mie and Rayleigh will be explored in relationship to the reported sizing variance of the SSIS to make a determination of the absolute sizing accuracy of the recipes there were generated based upon BRDF modeling. This paper explores both the commercial and technical considerations of the elimination of PSL deposition as a precursor to SSIS recipe creation. Successful integration of BRDF modeling into the technical aspect of SSIS recipe creation process has the potential to dramatically reduce the recipe creation timeline and vetting period. Integration of BRDF modeling has the potential to greatly reduce the overhead operation costs for High Volume Manufacturing sites by eliminating the associated costs of third party PSL deposition.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.