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We evaluate diffraction-based overlay (DBO) metrology using two test wafers. The test wafers have different film stacks designed to test the quality of DBO data under a range of film conditions. We present DBO results using traditional empirical approach (eDBO). eDBO relies on linear response of the reflectance with respect to the overlay displacement within a small range. It requires specially designed targets that consist of multiple pads with programmed shifts. It offers convenience of quick recipe setup since there is no need to establish a model. We measure five DBO targets designed with different pitches and programmed shifts. The correlations of five eDBO targets and the correlation of eDBO to image-based overlay are excellent. The targets of 800nm and 600nm pitches have better dynamic precision than targets of 400nm pitch, which agrees with simulated results on signal/noise ratio. 3σ of less than 0.1nm is achieved for both wafers using the best configured targets. We further investigate the linearity assumption of eDBO algorithm. Simulation results indicate that as the pitch of DBO targets gets smaller, the nonlinearity error, i.e., the error in the overlay measurement results caused by deviation from ideal linear response, becomes bigger. We propose a nonlinearity correction (NLC) by including higher order terms in the optical response. The new algorithm with NLC improves measurement consistency for DBO targets of same pitch but different programmed shift, due to improved accuracy. The results from targets with different pitches, however, are improved marginally, indicating the presence of other error sources.

The extension of optical lithography to 2Xnm and beyond is often challenged by overlay control. With reduced overlay measurement error budget in the sub-nm range, conventional Total Measurement Uncertainty (TMU) data is no longer sufficient. Also there is no sufficient criterion in overlay accuracy. In recent years, numerous authors have reported new method of the accuracy of the overlay metrology: Through focus and through color. Still quantifying uncertainty in overlay measurement is most difficult work in overlay metrology. According to the ITRS roadmap, total overlay budget is getting tighter than former device node as a design rule shrink on each device node. Conventionally, the total overlay budget is defined as the square root of square sum of the following contributions: the scanner overlay performance, wafer process, metrology and mask registration. All components have been supplying sufficiently performance tool to each device nodes, delivering new scanner, new metrology tools, and new mask e-beam writers. Especially the scanner overlay performance was drastically decreased from 9nm in 8x node to 2.5nm in 3x node. The scanner overlay seems to reach the limitation the overlay performance after 3x nod. The importance of the wafer process overlay as a contribution of total wafer overlay became more important. In fact, the wafer process overlay was decreased by 3nm between DRAM 8x node and DRAM 3x node. We develop an analytical algorithm for overlay accuracy. And a concept of nondestructive method is proposed in this paper. For on product layer we discovered the layer has overlay inaccuracy. Also we use find out source of the overlay error though the new technique.In this paper, authors suggest an analytical algorithm for overlay accuracy. And a concept of non-destructive method is proposed in this paper. For on product layers, we discovered it has overlay inaccuracy. Also we use find out source of the overlay error though the new technique. Furthermore total overlay error data is decomposed into two parts: the systematic error and the random error. And we tried to show both error components characteristic, systematic error has a good correlation with residual error by scanner condition, whereas, random error has a good correlation with residual error as going process steps. Furthermore, we demonstrate the practical using case with proposed method that shows the working of the high order method through systematic error. Our results show that to characterize an overlay data that is suitable for use in advanced technology nodes requires much more than just evaluating the conventional metrology metrics of TIS and TMU.