Wen Lv

Level-set-based inverse lithography for mask synthesis using the conjugate gradient and an optimal time step

Inverse mask synthesis is achieved by minimizing a cost function on the difference between the output and desired patterns. Such a minimization problem can be solved by a level-set method where the boundary of the pattern is iteratively evolved. However, this evolution is time-consuming in practice and usually converges to a local minimum. The velocity of the boundary evolution and the size of the evolution step, also known as the descent direction and the step size in optimization theory, have a dramatic influence on the convergence properties. This paper focuses on developing a more efficient algorithm with faster convergence and improved performance such as smaller pattern error, lower mean edge placement error, wider defocus band, and higher normalized image log slope. These improvements are accomplished by employing the conjugate gradient of the cost function as the evolution velocity, and by introducing an optimal time step for each iteration of the boundary evolution. The latter is obtained from an...

Robust and efficient inverse mask synthesis with basis function representation

Mask optimization is essential in the resolution scaling of optical lithography due to its strong ability to overcome the optical proximity effect. However, it often demands extensive computation in solving the nonlinear optimization problem with a large number of variables. In this paper, we use a set of basis functions to represent the mask patterns, and incorporate this representation into the mask optimization at both the nominal plane and various defocus conditions. The representation coefficients are updated according to the gradient to the coefficients, which can be easily obtained from the gradient to the pixel variables. To ease the computation of the gradient, we use an adaptive method that divides the optimization into two steps, in which a small number of kernels is used as the first step, and more kernels are used for fine optimization. Simulations performed on two test patterns demonstrate that this method can improve the optimization efficiency by several times, and the optimized patterns have better manufacturability compared with regular pixel-based representation.

Convolution-variation separation method for efficient modeling of optical lithography

We propose a general method called convolution-variation separation (CVS) to enable efficient optical imaging calculations without sacrificing accuracy when simulating images for a wide range of process variations. The CVS method is derived from first principles using a series expansion, which consists of a set of predetermined basis functions weighted by a set of predetermined expansion coefficients. The basis functions are independent of the process variations and thus may be computed and stored in advance, while the expansion coefficients depend only on the process variations. Optical image simulations for defocus and aberration variations with applications in robust inverse lithography technology and lens aberration metrology have demonstrated the main concept of the CVS method.

Fast aerial image simulations for partially coherent systems by transmission cross coefficient decomposition with analytical kernels

Aerial image simulation is one of the most critical components in the model-based optical proximity correction (OPC), which has become a necessary part of resolution enhancement techniques used to improve the performance of subwavelength optical lithography. In this paper, a fast aerial image simulation method is proposed for partially coherent systems by decomposing the transmission cross coefficient (TCC) into analytical kernels. The TCC matrix is projected onto a function space whose basis is analytical circle-sampling functions (CSFs) and converted into a much smaller projected matrix. By performing singular value decomposition (SVD) to the projected matrix, its eigenvectors together with the CSFs are used to generate a set of analytical TCC kernels. The proposed method avoids directly performing SVD to the large TCC matrix, making it much more runtime efficient than the conventional SVD method. Furthermore, the grid size of the kernels can be flexibly set to any desired value in aerial image simulations, which is not realizable with the conventional SVD method. The comparison of aerial image intensity errors and edge placement errors calculated by the proposed method and the conventional SVD method has confirmed the validity of the proposed method. An OPC example is also provided to further demonstrate its efficiency.

Cascadic multigrid algorithm for robust inverse mask synthesis in optical lithography

Abstract. Robust inverse mask synthesis is computationally intensive, and its turnaround time continues to rise hand-in-hand with the ever-shrinking integrated circuit feature size. We report the development of a cascadic multigrid (CMG) algorithm for robust inverse mask synthesis, which starts from a relatively coarse mask grid and refines it iteratively in stages, so as to achieve significant speedup without compromising numerical accuracy. Since the CMG algorithm entails frequent changes of the computational grid size, we need to intentionally introduce an analytical circle-sampling technique for modeling the forward lithography imaging and employ an edge distance error as metric to guide mask synthesis. These two techniques work nicely with variable grid sizes and are well suited for our CMG algorithm. As a result, our algorithm achieves more than four times speedup over conventional methods that synthesize a mask on a fixed fine grid. Numerical results are presented to demonstrate the validity and efficiency of the proposed method.

Mask-filtering-based inverse lithography

Abstract. We propose a new regularization framework for inverse lithography that regularizes masks directly by applying a mask filtering technique to improve computational efficiency and to enhance mask manufacturability. This technique is different from the conventional regularization method that regularizes a mask by incorporating various penalty functions to the cost function. We design a specific mask filter for this purpose. Moreover, we introduce a metric called edge distance error (EDE) to guide mask synthesis and establish the correlation between pattern error and edge placement error (EPE) via EDE. We prove that EDE has the same dimension as EPE and has a continuous expression as pattern error. Simulation results demonstrating the validity and efficiency of the proposed method are presented.

Illumination source optimization in optical lithography via derivative-free optimization

Illumination source optimization (SO) in optical lithography is generally performed under a simulation model that does not consider critical effects such as the vectorial nature of light and mask topography. When a numerical aperture becomes large and the critical dimension reaches subwavelength, the prediction of this model generally fails; therefore, the previous works based on this model become inaccurate. In order to correctly compute SO, we first propose a new source pattern representation method that has moderate parameter variations but remains complete in solution space. Then we develop a derivative-free optimization (DFO) method to optimize these parameters under a rigorous simulation model. Unlike gradient-based techniques, DFO methods do not require a closed-form formulation of the model and are independent of the form of cost function.

Pixel-based inverse lithography using a mask filtering technique

In this paper, we propose a new regularization framework that regularizes mask directly by applying a mask filtering technique to improve computational efficiency and enhance mask manufacturability for pixel-based Inverse Lithography Technique (ILT). Generally, the synthesized mask by pixel-based ILT is a grey-level image, and possesses small, unwanted block objects, such as isolated holes, protrusions, and jagged edges, which are unreachable in the real manufacturing process. The proposed method filters (or regularizes) mask directly to guarantee manufacturability of the synthesized mask pattern; this technique is different from the conventional regularization method that regularizes mask by incorporating various penalty functions to a cost function. A tailored mask filter is developed in this special ILT case. In addition, we introduce a new metric, edge distance error which has the same dimension nanometer as edge placement error and has a continuous expression as pattern error, to guide mask synthesis. Simulation results demonstrating the validity and efficiency of the proposed method are presented.

Ant colony algorithm for layout decomposition in double/multiple patterning lithography

Double or multiple patterning (DP/MP) lithography is an alternative for the sub-20 nm node and beyond. In MP, it is essential to solve a minimal patterning number to decompose the dense features. While in DP, it is required to remove odd conflict cycles with minimal stitch number. In this work, we apply an ant colony algorithm to address these two issues, respectively.

Sparse nonlinear inverse imaging for shot count reduction in inverse lithography.

Inverse lithography technique (ILT) is significant to reduce the feature size of ArF optical lithography due to its strong ability to overcome the optical proximity effect. A critical issue for inverse lithography is the complex curvilinear patterns produced, which are very costly to write due to the large number of shots needed with the current variable shape beam (VSB) writers. In this paper, we devise an inverse lithography method to reduce the shot count by incorporating a model-based fracturing (MBF) in the optimization. The MBF is formulated as a sparse nonlinear inverse imaging problem based on representing the mask as a linear combination of shots followed by a threshold function. The problem is approached with a Gauss-Newton algorithm, which is adapted to promote sparsity of the solution, corresponding to the reduction of the shot count. Simulations of inverse lithography are performed on several test cases, and results demonstrate reduced shot count of the resulting mask.