Advances in imaging tool adjustment optimization methodologies and capabilities, including impact upon imaging performance budget components

摘要

As the design rules and the actual sizes of the patterns being printed continue to shrink well below half the wavelength of light being utilized, the budgets associated with all variations in imaging likewise continue to squeeze to tighter required tolerances. In this environment, the control and adjustment of the imaging has continued to increase in importance. Building upon previous work in the field of lens adjustment and optimization, additional methods have been developed and implemented which enable more specialized adjustment towards the optimization of given priorities associated with a given patterning step. Specifically, it is fast becoming typical to leverage all available degrees of adjustment freedom uniquely for each critical layer identified in a given process. Various optimization goals are discussed, with procedures and results presented for each. Examples of these include: 1. optimization of a single machine towards the best possible ultimate CD uniformity performance while staying within a specified range of allowed residual distortion; 2. optimization of ultimate distortion magnitude, while staying within a budgeted level of imaging/CD uniformity performance; 3.optimization of specific aberrations while maintaining all others within budgeted levels of allowed magnitude. The motivations driving each of these sorts of optimizations will be discussed, as well as limitations that may exist from various sources, including metrology, process variation and it effects, and the imaging tool. The impact such optimization capability can have on the defined CD budget will also be discussed, towards the goal of qualifying and, where possible, quantifying the overall improvement possible through application of these optimization techniques. These sorts of improvements and their documentation can allow for feedback into the device design process, leveraging the reduced level of variation resulting from such optimizations.