Mask correction method for surface plasmon lithography.

Surface plasmon lithography (SPL) has emerged as an innovative approach to nano-fabrication, offering an alternative to traditional patterning methods. To enhance its pattern fidelity in manufacturing, it is essential to incorporate mask correction to reduce critical dimension (CD) errors between the intended target features and the photoresist image. Traditionally, the aerial image of SPL has been modeled and simulated using methods such as finite difference time domain (FDTD) or rigorous coupled wave analysis (RCWA). These models have allowed us to obtain aerial images of the mask patterns. However, relying solely on the aerial image proves insufficient for meeting the rigorous manufacturing standards for mask correction. In our research, we propose a comprehensive model that combines the optical model, employing the FDTD method, and the resist model, tailored to the specific surface plasmon lithography process. Test patterns were meticulously designed with a target CD of 130 nm, and the model was applied to simulate these test patterns, producing the after-development image (ADI) under predefined process conditions. Following a thorough analysis and data processing of the test patterns and ADI data, we established rule tables for the correction of both 1D line patterns and line end patterns. The simulation results unequivocally demonstrate the improved CD error performance achieved by the post-corrected patterns.

Three-dimensional plasmonic lithography imaging modeling based on the RCWA algorithm for computational lithography.

This paper reminds the principle and characteristics of plasmonic lithography, and points out the importance of establishing a fast and high precision plasmonic lithography imaging model and developing computational lithography. According to the characteristics of plasmonic lithography, the rigorous coupled-wave analysis (RCWA) algorithm is a very suitable alternative algorithm. In this paper, a three-dimensional plasmonic lithography model based on RCWA algorithm is established for computational lithography requirements. This model improves the existing RCWA algorithm, that is, deduces the formula for calculating the light field inside the structure and proposes the integration, storage and invocation of the scattering matrix to improve the computation speed. Finally, the results are compared with commercial software for the two typical patterns. The results show that the two calculation results are very close, with the root mean square error (RMSE) less than 0.04 (V/m)2. In addition, the calculation speed can be increased by more than 2 times in the first calculation, and by about 8 times by integrating, storing and invoking the scattering matrix, which creates conditions for the development of plasmonic computational lithography.

Aberration budget analysis of EUV lithography from the imaging performance of a contact layer in a 5 nm technology node.

By analyzing the impact of aberration in an extreme ultraviolet lithography projector on the imaging indicators of the test patterns for a contact layer in a 5 nm technology node, this paper establishes a mathematical aberration model based on the back propagating neutral network. On the basis of an aberration model, a method for estimating the aberration budget is proposed, which can help reduce the difficulty of achieving imaging performance thresholds in actual production. The performance of the results given by this method is verified by using a rigorous simulation. The results show that the model is highly accurate in predicting an aberration distribution that meets the requirements through an inverse sensitivity analysis and can calculate the wavefront aberration margin based on imaging indicators.

Plasmonic lithography fast imaging model based on the decomposition machine learning method.

Plasmonic lithography can make the evanescent wave at the mask be resonantly amplified by exciting surface plasmon polaritons (SPPs) and participate in imaging, which breaks through the diffraction limit in conventional lithography. It provides a reliable technical way for the study of low-cost, large-area and efficient nanolithography technology. This paper introduces the characteristics of plasmonic lithography, the similarities and the differences with traditional DUV projection lithography. By comparing and analyzing the already existed fast imaging model of mask diffraction near-field (DNF) of DUV/EUV lithography, this paper introduces the decomposition machine learning method of mask diffraction near-field into the fast imaging of plasmonic lithography. A fast imaging model of plasmonic lithography for arbitrary two-dimensional pattern is proposed for the first time. This model enables fast imaging of the input binary 0&1 matrix of the mask directly to the light intensity distribution of photoresist image (PRI). The illumination method employs the normal incidence with x polarization, the normal incidence with y polarization and the quadrupole illumination with TM polarization respectively. The error and the operating efficiency between this fast imaging model and the rigorous electromagnetic model is compared. The test results show that compared with the rigorous electromagnetic computation model, the fast imaging model can greatly improve the calculation efficiency and maintain high accuracy at the same time, which provides great conditions for the development of computational lithography such as SMO/OPC for plasmonic lithography technology.

Study on forbidden pitch in plasmonic lithography: taking 365†nm wavelength thin silver film-based superlens imaging lithography as an example.

Plasmonic lithography can make the evanescent wave at the mask be resonantly amplified by exciting surface plasmon polariton (SPP) and participate in imaging, which can break through the diffraction limit in conventional lithography. It provides a reliable technical way for the study of low-cost, large-area and efficient nanolithography technology. However, there is also a phenomenon in plasmonic lithography similar to the forbidden pitch in conventional projection lithography. In this paper, combined with the imaging model and the optical transfer function (OTF), the theoretical analysis points out the reasons for the existence of the phenomenon of forbidden pitch in plasmonic lithography. Taking the 365 nm wavelength Ag thin film-based superlens imaging lithography as an example, the positions of the forbidden pitches of the 1:1 mask, the bright-field mask and the dark-field mask are calculated separately, and the key factors affecting their positions are pointed out. Simulation is carried out through commercial software, and the correctness of theoretical analysis is verified. Finally, we summarize and give some possible suggestions for solving this problem, including exploring better illumination methods, avoiding the patterns with forbidden pitch in the design, or by adding assistant feature to the design.