Microlens arrays play a critical role in enhancing imaging systems due to their outstanding optical performance, compact size, and lightweight nature. However, traditional fabrication methods for microlens arrays suffer from low precision, inefficiency, high costs, and a lack of adequate surface figure control. In this paper, we present a novel approach for microlens array fabrication, using a projection lithography process with mask-shifting. The method employs a 0.2× projection objective lens to enhance linewidth resolution. By employing a projection-based mask-shift filtering technique, we achieve superior surface figure accuracy while reducing the complexity of mask preparation. The experimental results for four microlenses with different aperture sizes demonstrate surface figure accuracy in the submicron range and surface roughness at the nanometer level. In addition, 3D profilometer scanning equipment was employed to measure the surface roughness of these microlens arrays, and the measurement results of these microlens arrays processed using the proposed method for their surface roughness are 18.4 nm, 29.6 nm, 34.4 nm, and 56.1 nm. Our findings indicate that this method holds great potential in microlens array fabrication, offering the ability to achieve lower linewidths and higher surface figure accuracy compared to conventional methods.

Source mask optimization (SMO) is an effective method for improving the image quality of high-node lithography. Reasonable algorithm optimization is the critical issue in SMO. A GA-APSO hybrid algorithm, combining genetic algorithm (GA) and adaptive particle swarm optimization (APSO), was proposed to inversely obtain the global optimal distribution of the pixelated source and mask in the lithographic imaging process. The computational efficiency was improved by combining the GA and PSO algorithms. Additionally, the global search and local search were balanced through adaptive strategies, leading to a closer result to the global optimal solution. To verify the performance of GA-APSO, simple symmetric patterns and complex patterns were optimized and compared with GA and APSO, respectively. The results show that the pattern errors (PEs) of the resist image optimized by GA-APSO were reduced by 40.13–52.94% and 10.28–33.31% compared to GA and APSO, respectively. The time cost of GA-APSO was reduced by 75.91–87.00% and 48.43–58.66% compared to GA and APSO, respectively. Moreover, repeated calculation showed that the GA-APSO results were relatively stable. The results demonstrate the superior performance of GA-APSO in efficiency, accuracy, and repeatability for source and mask optimization.

Inverse lithography technology (ILT) based on the gradient descent (GD) algorithm, which is a classical local optimal method, can effectively improve the lithographic imaging fidelity. However, due to the low-pass filtering effect of the lithography imaging system, GD, although able to converge quickly, is prone to fall into the local optimum for the information in the corner region of complex patterns. Considering the high-frequency information of the corner region during the optimization process, this paper proposes a resolution layering method to improve the efficiency of GD-based ILT algorithms. A corner-rounding-inspired target retargeting strategy is used to compensate for the over-optimization defect of GD for inversely optimizing the complex pattern layout. Furthermore, for ensuring the manufacturability of masks, differentiable top-hat and bottom-hat operations are employed to improve the optimization efficiency of the proposed method. To confirm the superiority of the proposed method, multiple optimization methods of ILT were compared. Numerical experiments show that the proposed method has higher optimization efficiency and effectively avoids the over-optimization.

As an effective resolution enhancement technology, source optimization (SO) is considered key for significantly improving the image quality of optical lithography at advanced nodes. To solve the problem of unsatisfactory SO performance, it is necessary to combine it with optimization algorithms. In this study, an SO method based on a hybrid genetic algorithm is proposed to achieve an acceptable source shape in the imaging process for optical lithography. To overcome the problems of local optima and the small search scope, an update strategy that uses particle swarm optimization and the tabu list method from the tabu search algorithm are utilized to enhance the optimization performance. Meanwhile, different feature patterns were employed as the input of the optimization model. These simulation results show that the proposed SO method exhibits dominant optimization performance for SO in optical lithography.

Inverse lithography technology (ILT) plays a pivotal role in advanced semiconductor manufacturing because it enables pixel-level mask modifications, significantly enhances pattern fidelity, and expands process windows. However, traditional gradient-based ILT methods often struggle with the trade-off between imaging fidelity and mask manufacturability due to coupled optimization objectives. We propose a frequency-separated dual-stage optimization framework (FD-ILT) that strategically decouples these conflicting objectives by exploiting the inherent low-pass characteristics of lithographic systems. The first stage optimizes low-frequency (LF) components using hierarchical downsampling to generate a high-fidelity continuous transmission mask. This approach reduces computational complexity while refining resolution progressively. The second stage enforces manufacturability by exclusively adjusting high-frequency (HF) features through morphological regularization and progressive binarization penalties while maintaining the mask LF to preserve imaging accuracy. Our method achieves simultaneous control of both aspects by eliminating gradient conflicts between fidelity and manufacturing constraints. The simulation results demonstrate that FD-ILT achieves superior imaging quality and manufacturability compared to conventional gradient-based ILT methods, offering a scalable solution for advanced semiconductor nodes.

The laser tracker has characteristics of high measurement accuracy and wide measurement range. Laser tracker technology, as an effectively large-scale measuring approach, plays a critical role in dynamic measurement. Currently, the static performance of laser trackers has been well studied. However, the dynamic characteristics of the laser tracker remain unclear in terms of evaluating its dynamic performance. The circular trajectory generator measurement system can quantify the dynamic performance of the laser tracker. We developed a standard circular trajectory generator using a stable servo system and then conducted an in-depth study on the dynamic performance of the laser tracker through statistical analysis. Numerous experiments have shown that if the laser tracker is set at equal spacing, the dynamic indication error is smallest when the measurement distance is 3 m, indicating that the fitted diameter at a distance of 3 m is closest to the diameter of the circular trajectory generator. If the laser tracker is set with equal sampling frequency, the dynamic indication error is smallest when the measurement distance is 5 m. When the circular trajectory generator is at low speed, the measurement spacing of sampling points of the laser tracker is fixed proportional to the number of measurement points, while at low or high speed the sampling frequency of the laser tracker is fixed proportionally to the number of measurement points. These conclusions will facilitate the application of the laser tracker in dynamic measurement.