With the growing complexity of I-line and DUV (Deep Ultraviolet) photolithography processes, defect monitoring and yield improvement is becoming more critical and challenging. In addition to product wafer scans, reliable unpatterned wafer scans, with their advantage of much quicker feedback time for tool qualification and/or process monitoring must be developed and implemented. Especially with the more wide spread use of the newer chemically amplified resists, a high sensitivity, easy to review and trouble-shoot monitor is essential. A laser scanning unpatterned wafer defect detection tool was used to scan developed unpatterned photoresist coated wafers. Defect recipe creation for detecting these defects involved using the method of "signal to noise" to set the tool to find real defects. The conventional method of applying latex spheres of a known size for a calibration media was not used since it is not at all representative of the way real process defects scatter light. A novel, non-destructive unpatterned wafer review method was used to actually review the defects using darkfield microscopy, and to determine real defects (signal) from false calls (noise). From this work we were able to detect defect process signatures and defects that were related to the develop dispense configuration. Darkfield microscopy revealed the defects were indeed developer related since they appeared as liquid spot type defects and/or residue. Subsequent use of this method has been established as an excellent troubleshooting method to finding and fixing photo defect issues. The methods and results of this work will be discussed.

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Conventionally, plasma ash followed by a wet clean has been used to strip implanted photoresists on all semiconductor technology process flows and nodes. This paper describes the theory and implementation of an All Wet Strip (AWS) process at various post implant levels in the process flow, thus eliminating the need for a plasma treatment. Plasma treatment post implants have shown to add product yield limiting defects most likely eliminated by an All Wet Strip (AWS) process; successfully contributing to cycle time, capacity, cost and yield improvement for semiconductor chips. AWS involves the use of a sulfuric acid and hydrogen peroxide mixture for stripping implanted photo resists, the effectiveness of which has a dependency on the ion implant dose, energy and photo resist type. The paper describes the unique challenges that were overcome to bring the concept from an experimental stage to actual implementation, the process integration plus device sensitivities involved in ramping a process, in a volume 300mm semiconductor wafer fab for complex technologies.

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