Features in forbidden pitch have limited exposure latitude and depth of focus in lithography exposure. This paper provides an analysis of forbidden pitch in extreme ultraviolet lithography (EUVL) from the perspective of rigorous simulation and source mask optimization (SMO). In the stage of rigorous simulation, S-litho is used to analyze the normalized image log slope (NILS) of test patterns from different critical layer in 5nm node. Then the process windows of these test patterns are simulated and compared by the lithography simulator Proteus WorkBench. From the result analysis, the forbidden pitches of critical layer in 5nm node are summarized. In addition, the strategy of mitigating the negative effect of forbidden pitch is proposed with the help of computational lithography.
In EUV lithography, the short wavelength and residual mirror surface roughness increase the flare levels across the slit. As a key research point, the flares of different exposure fields are carefully discussed by numerical simulation. To ensure the effectiveness and practicability of our simulations, the test patterns are generated according to the general design rules for 7nm technology node. The NILS, process variation band (PVB) and MEEFs from mask optimizations and source mask optimizations (SMO) results are compared. From the comparisons, the constant flare has a greater influence on NILS and PVB than that on MEEF. In contrast, the flare map caused more reduction on the MEEF values.
An EUV source optimization technique using compressive sensing is introduced in this paper. The pixelated source pattern is sparsely represented in a set of certain basis functions. Blue noise sampling method is used to select sampling points around the margins of the target layout for imaging fidelity evaluation. Based on the compressive sensing theory, the EUV SO is formulated as an l1-norm inverse reconstruction problem and solved by the linearized Bregman algorithm. Different types of sparse bases are also experimented in this paper to investigate their impact on the SO results. These bases include the 2D-DCT basis, spatial basis, Zernike basis, and Haar wavelet basis. Simulations show that ℓthe Haar wavelet basis results in the best imaging fidelity among the four types of bases.
It is of tremendous impact with multilayer defects, which are caused by particles, substrate pits or scratches, in EUV lithography for the high volume manufacturing. Multilayer defects suppress the productivity and utilization rate of the mask blank. In this paper, we did a thorough investigation by conducting imaging simulations on dense and semi-dense patterns including lines and contact holes. The impact of isolated multilayer defects on the imaging of 22nm half-pitch dense line/contact and 33nm half-pitch semi-dense line has been studied, and the CD errors are calculated. The CD error, caused by the planar defect which is smoothed out during the multilayer deposition process, is found to be within ±10% of target values. This CD error can be compensated by adjusting the exposure dose or local pattern size. In contrast, the non-planar defect, which is not being smoothed in the multilayer surfaces, would lead to severe damages to the lithography performance.
Background: As semiconductor technologies continue to shrink, the growth in the number of process variables and combined effects tighten the overall process window, which leads to a more serious yield loss. Yield cannot be totally guaranteed by design rule check and verifications of optical proximity correction, due to complex process variations. The joint effects from unreasonable designs and unstable control of critical dimensions and overlay mainly contribute to the formation of bridging defects in critical interconnect layers. Aim: Our paper puts forward a model to detect the potential bridging region and predicts the corresponding failure probability under a litho-etch-litho-etch process. Approach: The proposed model is based on input error sources from variations of lithography and etch processes. In this scheme, bridging is expected when the minimum space of simulated postetch contours within a specific range is smaller than a user-defined bridging threshold. Gaussian distribution characteristics of line edge roughness (LER) and overlay are considered in the proposed model. Moreover, the proposed model provides meaningful guidelines for bridging prediction with the use of process variation bands. Results: The experiment results indicate consistency and validity of theoretical derivation of the proposed model. The concrete impacts of LER and overlay on the model have been quantitatively analyzed as well. Conclusions: According to the predicted probabilities, the model can early discover potential bridging defects quantitatively by considering the statistical properties of process variations with very few calculations and can give a ranking of failure severity as a decision foundation for design rule optimization.
With the continuous shrinking of critical dimension, it may require more time and effort to reduce or remove the lithography defects in the development process. Therefore, defect reduction has become one of the most important technical challenges in device mass production. With the purpose of finding an optimizing recipe, we can simulate group parameters, including nitrogen gas dispensation and wafer-rotation speed. From previous studies, we have established a model based on viscous fluid dynamics and have calculated the removing force distribution across the 300-mm-diameter wafer for the defect residual. In this model, we assumed that the defects mostly are polymer residual; once the removing force reached a certain threshold level (1 × 10 − 14 N), the defect with a “centered-ring-like” signature could be removed. For illustration, several groups of optimal parameter under postdeveloping rinse process conditions are given. The numerical simulations represent several recipes in the development process. We find that we can reproduce a group of the total force curves. From the simulation, we could find that we can get the minimally required strength from the three parameters for defect removal. We have done some experiments to validate the simulation results. The experimental data are almost in agreement with the simulation data. Therefore, the above simulation results have verified the effectiveness and validity of the proposed optimization methodology, and it also has shown that the trend of parameters provided by the optimized method has the potential to be an efficient candidate for reducing or removing lithography defects in the development process.
The oblique incidence of the illumination system in EUV lithography combined with relative thick absorber layer of EUV mask introduces many unique distortions on the image transfer between mask and wafer, most of these distortions are non-linear thus makes the enhancement of resolution more difficult. This paper focus on analysing the impacts of the absorber layer thickness, multilayer thickness and the light source morphology on the image. And improve the EUV lithography and imaging quality by co-optimization of these three parameters. Besides, the intrinsic features and rules of the impacts of absorber thickness on the imaging properties is revealed. And the different behaviour of 1D dense pattern and isolation pattern during the co-optimization is analysed and elucidated. This study provides a potential new direction for resolution enhancement technology.
The oblique illumination in EUVL system combined with relative thick absorber layer of EUV mask introduces many new challenges for mask simulation, like asymmetric phase deformation, shadowing effects , secondary scattering. Besides, these effects result in the ineffectiveness of the Hopkins approach and require new method for mask diffraction computation. A 3D RCWA algorithm is implemented to perform rigorous computation of lights diffracted by the EUV masks. Several examples are designed, analyzed and presented in this paper. Furthermore, a fast version of the rigorous 3D algorithm is implemented by properly decomposing the 3D model into multiple simpler ones, thus the computational time is reduced.