Real-time feedback control and fault detection in deep-submicron plasma etch

The drive to miniaturize device feature size has exerted tremendous pressure on research to design and produce smaller chips which are both highly reliable and cost-effective. Though the reduction of chip size is governed by Moore's law, the miniaturization itself has given rise to a whole new set of problems that are roughly inversely proportional to the reduction in chip size. Among these challenges, our research focused on a fundamental and irreversible process in chip production, the plasma etching process. Errors in this process are a source of considerable economic loss. Thus, developing a highly stable etching process that can be precisely controlled under the demands of increasing miniaturization is crucial from both the point of profitability and manufactuability.;In this research, we focused on the application of a real-time feedback control on the plasma etch to improve the etch selectivity and etch profile reproducibility. Furthermore, we developed a method for detecting sensor faults, which can significantly contribute to machine uptime. To address this concern, we employed in situ sensors, feedback control, and estimation techniques. First, we demonstrated the etch selectivity improvement in a conventional single-power-source plasma etcher. A variable resistor controlling ion energy was implemented to enhance the etch selectivity of poly-Si over SiO2 . Next, the etch profile reproducibility of a 0.1 mum alpha-Si gate structure was investigated. A Kalman-Bucy filter with a Real-Time Spectroscopic Ellipsometer was implemented to improve the accuracy of the endpoint detection of Main Etch (ME). Finally, the sensor fault detection problem was addressed. A Broadband RF sensor was used to detect and identify errors in the sensors caused by sensor drift, aging, or miscalibration. The results showed significant reduction in etch process drift and machine downtime.