Development of Advanced Signal Processing Algorithms for On-Line Temperature Profile Measurement in Semiconductor Manufacturing

本研究是针对开发，实施和演示的先进的基于模型的信号处理算法的快速热处理（RTP）的晶片温度分布的实时测量，RTP集群工具是战略上重要的亚微米半导体制造，因为减少热预算的趋势和收紧大直径硅晶片的工艺控制要求。 尽管RTP模块具有显著的优点，但用于各种化学气相沉积应用的RTP模块的商业版本不可用。 在这个项目中，研究人员正在开发先进的基于模型的信号处理算法，当与声学测温和声学/高温计方法相结合时，可以以快速的采集速率和最少数量的传感器准确地测量晶片温度分布。 这需要算法的开发，实施和验证使用真实的数据从商业RTP工具在UT-奥斯汀和SEMATECH。

This research is directed towards the development, implementation, and demonstration of advanced model-based signal processing algorithms for real-time measurement of wafer temperature profile in Rapid Thermal Processing (RTP), RTP cluster tools are strategically important for submicron semiconductor manufacturing because of trends towards reduced thermal budget and tightened process control requirements on large diameter silicon wafers. Despite its significant advantages, commercial versions of RTP modules for various chemical vapor deposition applications are not available. In this project, the investigators are developing advanced model- based signal processing algorithms, which when coupled with the acoustic thermometry and acoustic/pyrometer approaches, accurately measure the wafer temperature profile at fast acquisition rates and with a minimum number of sensors. This entails algorithm development, implementation, and validation using real data from commercial RTP tools at UT-Austin and SEMATECH.