As the technology node gets smaller and smaller, the benefit from Sub-Resolution Assist Features (SRAF) becomes significant in EUV lithography which makes SRAFs a must-have tool for next generation beyond 7nm technology. When considering EUV specific effects, the metrics that need to be accounted for include Image Log-Slope (ILS), Process Variability (PV Band), common Depth of Focus (cDOF), and Image Shift (ImS) through focus. When these critical factors are accounted for during the EUV mask generation the optimization become much more complicated and challenging and necessitates the need for SRAFs beyond 7nm. SRAF helps enhance not only the PV Band, but more importantly helps boost the ILS, which is one of the key factors for improving stochastic effect in EUV. However, ILS is just one of the important image quality metric that we should focus on. For metal layers, Image Shift is another key factor which can have a big impact on overlay. ImS at the nominal condition could be compensated by Optical Proximity Correction (OPC), but image shift through focus can hardly be tuned by the main feature correction. The image shift through focus can be mitigated by SRAF insertion. Strong 3D mask effects can cause best focuses of different patterns to be far apart in EUV, which can cause an unusable cDOF even when the individual depth of focus values of all the patterns are not bad. SRAFs can be inserted to improve the individual depth of focus and align the best focuses together to help enhance the common process window. When taking account of various different EUV specific metrics mentioned above, then the most critical question for the next generation beyond 7nm is “How to define the cost function for mask optimization with SRAFs?” (Figure 1, EUV mask optimization flow for next generation beyond 7nm). In this study the image quality metrics including ILS, PVBand, cDOF, and ImS are evaluated. For each optimization schema using different cost functions, we examine the cost function metric and its impact on the other image quality metrics. We also present the potential trade-offs together with the analysis. Furthermore, multiple cross cost functions are defined for SRAF optimization and the results are analyzed accordingly. Both contact and metal layer patterns representing next generation beyond 7nm design rules are investigated. In our testing, symmetric standard sources from ASML NXE3400 is examined and the results are compared and analyzed.
As the EUV lithography is extending beyond 7nm technology, design to mask strategy becomes more complex. New challenges including advanced OPC and ILT in mask optimization, curvilinear masks, shrinking Mask Rule Checking (MRC), Sub-Resolution Assist Features (SRAF) generation and formation, and other complex mask geometries drive the needs to study this synergy from different stages of the flow from Optical Proximity Correction (OPC), Mask Process Correction (MPC), fracturing, to mask writing and inspection. In this study, different OPC and SRAF mask formations including curvilinear masks, controlled Manhattanized approximations of curvilinear masks, and conventional masks are generated. We illustrate whether curvilinear masks have any demonstrable lithographic benefits. A quantitative comparison of how the Manhattanization impacts mask formation. The image quality metrics such as Image Log Slope (ILS), Process Viability (PV) Band, and Depth of Focus (DOF) from various OPC mask flavors including different MRC settings and different mask forms are compared and discussed. The mask manufacturability study is conducted to identify any major challenges and approaches to minimize, including assessing the value and need for native curvilinear write tool support on a MultiBeam Mask Writer (MBMW) or a single beam Vector Shaped Beam (VSB) mask writer.
The next-generation beyond 7-nm node potentially requires the implementation of subresolution assist features (SRAF) with extreme ultraviolet (EUV) lithography. This paper aims at providing a clear SRAF strategy for the next-generation beyond 7-nm node designs through a series of experiments. Various factors are considered, including stochastic effects, three-dimensional (3-D) mask effects, through-slit effects, aberrations, and pixelated source mask optimization (SMO) sources. We consider process variability bands with a variety of process conditions, including focus/dose/mask bias changes and also the normalized image log-slope/image log-slope as our objective functions, to determine what the best SRAF solution is for a set of test patterns. Inverse lithography technology is implemented to optimize both the main feature (MF) mask and SRAF placement, in particular, asymmetric SRAF placement to balance the 3-D mask effects. SRAF can potentially mitigate image shift through-focus, i.e., nontelecentricity, caused by EUV 3-D shadowing effect. This shadowing effect is pattern-dependent and contributes to the overlay variation. As we approach the next-generation beyond 7-nm node, this image shift can be more significant relative to the overlay budget, hence, we further investigate the impact of SRAF placement to the image shift. Moreover, the center of focus shift due to the large 3-D mask absorber thickness can be potentially mitigated by SRAF implementation. The common process window is significantly impacted by both the center of focus shift and the individual depth of focus and is evaluated using both metal and contact layer test cases. We study the source impact to SRAF insertion by experimenting with both a symmetric source (standard source) and an asymmetric source (SMO source). Finally, we understand the importance of using full flare map and full through-slit model (including aberration variation through-slit) in the MF correction. Furthermore, we evaluate the need of using full models in SRAF insertion. This is a necessary step to determine the strategy of SRAF implementation for the next-generation beyond 7-nm node.
The next generation beyond 7nm node potentially requires the implementation of Sub-Resolution Assist Features (SRAF) with EUV lithography. This paper aims at providing a clear SRAF strategy for the next generation beyond 7nm node designs through a series of experiments. Various factors are considered, including: stochastic effects, 3D mask effects, through-slit effects, aberrations, and pixelated SMO sources. <p> </p>EUV has 13.5nm as its wavelength, which is much smaller than the wavelength used in ArF lithography, and this gives very different imaging challenges compared to the ArF case. Due to the small wavelength and numerical aperture (NA) of the current EUV tools, depth of focus is not as significant of a concern as in DUV. Instead, EUV lithography is severely challenged by stochastic effects, which are directly linked to the slope of the intensity curve. DUV SRAF has been shown to be a powerful tool for improving NILS/ILS, as well as DOF, and here we explore how that translates into EUV imaging. In this paper, we consider Process Variability (PV) Bands with a variety of process conditions including focus/dose/mask bias changes and also the NILS/ILS as our objective functions, to determine what the best SRAF solution is for a set of test patterns. We have full investigations on both symmetric SRAF and asymmetric SRAF. <p> </p>SRAF can potentially mitigate image shift through focus, i.e. non-telecentricity, caused by EUV 3D shadowing effect. This shadowing effect is pattern dependent and contributes to the overlay variation. As we approach the next generation beyond 7nm node, this image shift can be more significant relative to the overlay budget, hence we further investigate the impact of SRAF placement to the image shift. Moreover, the Center of Focus shift due to the large 3D mask absorber thickness can be potentially mitigated by SRAF implementation. The common process window is significantly impacted by both the center of focus shift and the individual depth of focus. We study the change by adding SRAF using both a symmetric source (standard source) and an asymmetric source (SMO source). Once SRAF is inserted for the test patterns, the common process window is plotted to compare the solutions with and without SRAF. <p> </p>Finally, we understand the importance of using full flare map and full through slit model (including aberration variation through slit) in the main feature correction, but in this paper, we will further evaluate the need of using full models in SRAF insertion. This is a necessary step to determine the strategy of SRAF implementation for the next generation beyond 7nm node.
Process window OPC (PWOPC) is widely used in advanced technology nodes as one of the most important resolution enhancement techniques (RET).<sup>1</sup> PWOPC needs to consider not only edge placement error (EPE) from nominal condition simulations, but also constraints based on process variation simulations, such as pinch and bridge related requirements based on process variation band (PVBAND). Those constraints can be challenging to meet as feature size continues to shrink in advanced nodes. <p> </p>In this paper a novel matrix retargeting based PWOPC was developed to find optimal OPC solutions by solving constraints-based matrix and applying minimal retargeting as needed.<sup>2</sup> Experiment results showed enhanced process window and reasonable performance.
In this paper advanced OPC (Optical Proximity Correction) methods, additional with assistant features, and non-obvious
methods were implemented to correct aberrations caused by aggressive illuminations in order to optimize the shape of
the finger tips. OPC model and simulations were verified using 2D verification method.
A perspective is presented on how the semiconductor integrated circuit industry has evolved and what we can expect over the next decade or two. However, this 'forecast' is given in only the broadest sense, to make it relatively independent on innovations and discoveries that are likely to strongly shape the industry over this time period. Rather, trends are examined, as well as general 'tools' that will undoubtedly be important in advancing from our present microelectronics era to our presumable future in nanoelectronics.