Heterogeneous Wireless Sensing and Modeling of Chemical-Mechanical Interactions in Chemical Mechanical Planarization Process for Microelectronic Applications

Oklahoma State University, Stillwater OK

Investigators

Abstract

The objective of this research project is to address the following issues involved in the predictive modeling and real-time monitoring of chemical mechanical planarization/polishing (CMP) process used in the finishing of semiconductor chips: the interaction of chemical and mechanical phenomena at the silicon wafer-pad interface, the effect of machine vibrations, forces, temperature profiles, and acoustic emission signals, and the modeling of nonlinear stochastic process-machine interactions that capture the dynamic relationships between the wafer-pad interactions and the response of the sensor signals. Both experimental and analytical investigations will be undertaken to address these issues. A production machine will be instrumented with an array of heterogeneous sensors, including force, temperature, vibration, and acoustic emission (both wired and wireless). A sensor fusion approach will be used to monitor various stages of the process. The complex relationships connecting machine-specific and material-specific parameters with performance variables, namely, removal rate and planarity will be delineated by the application of a suite of statistical analysis methods applied to the experimental data. The mechanical and chemical interactions at the wafer-pad interface at various temperatures will be determined by developing a thermal model using Jaeger's classical heat source theory, Gibbs free-energy minimization, and molecular dynamics modeling. Productivity gains in the finishing of semiconductor devices depend on advances in chemical mechanical planarization/polishing. Wafer sizes, device density, feature dimensions, surface quality, and defect structure are posing serious challenges to the science and technology of chemical mechanical planarization/polishing . This investigation, if successful, will yield deeper insights into various chemo-mechanical interactions and will integrate a heterogeneous sensor network for improving productivity and integrated circuit quality.