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Extreme ultraviolet lithography is regarded as the most attractive technology to achieve 7 nm node and below. A new high-numerical-aperture anamorphic objective lens is designed to extend the single exposure resolution limit. However, the polarization aberrations (PAs) induced by the multilayer coatings on mirrors cause pattern distortions that cannot be neglected. In this paper, a source, mask, and process parameter co-optimization method is developed to compensate for the pattern distortions caused by PAs and increase the process window (PW). We first present an asymmetric source represented by the superposition of Zernike polynomials to reduce the pattern placement error (PPE). Then, a weighted cost function that incorporates the influences of PAs is innovated. Finally, a gradient-based statistical optimization method is adopted to minimize the cost function by optimizing the lithography system parameters alternately. Simulations at the 7 nm node of the 1D mask pattern indicate that for the system with a PA of marginal field, compared with our earlier work, the critical dimension error and PPE of the proposed method are reduced by 75.0% and 82.4%, respectively, and the PW is increased by 97.4%.
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http://dx.doi.org/10.1364/AO.58.003718 | DOI Listing |
IEEE Trans Biomed Circuits Syst
August 2025
Brain-computer interfaces rely on precise decoding of neural signals, where spike sorting is a critical step to extract individual neuronal activities from complex neural data. This works presents a spiking neural network (SNN) framework for efficient spike sorting, named SIFT-RSNN. In the SIFT-RSNN, raw neural signals are encoded into spike trains using a threshold-based temporal encoding strategy, then a sparse-integrated filtering module refines misfiring spikes, enhancing data sparsity for pattern learning.
View Article and Find Full Text PDFSensors (Basel)
July 2025
Beijing Research Institute of Telemetry, China Aerospace Science and Technology Corporation, Beijing 100094, China.
High-precision time-frequency systems are essential for low Earth orbit (LEO) navigation satellites to achieve real-time (RT) centimeter-level positioning services. However, subject to stringent size, power, and cost constraints, LEO satellites are typically equipped with oven-controlled crystal oscillators (OCXOs) as the system clock. The inherent long-term stability of OCXOs leads to rapid clock error accumulation, severely degrading positioning accuracy.
View Article and Find Full Text PDFAchieving a large lithography process window (PW) via computational lithography is a crucial prerequisite for ensuring adequate product yield in advanced-node integrated-circuit manufacturing technologies. However, as the critical dimensions of patterns continue to shrink, a chip-level qualified common process window (CPW) necessitates multiple rounds of highly time-consuming iterations of source mask co-optimization (SMO). To ensure a sufficient CPW for yield improvement while reducing the iterations of SMO, this paper presents what we believe to be a novel mask optimization (MO) approach aimed at attaining the maximum effective CPW in every iteration.
View Article and Find Full Text PDFSource and mask co-optimization (SMO) is an important technique to improve the image fidelity and process window of the advanced lithography process. Modern SMO methods adopt pixelated representations of source and mask to improve the degrees of optimization freedom, but those approaches are computationally intensive and time consuming. To our knowledge, this paper is the first to develop an efficient SMO method based on the advanced hypergraph deep learning framework.
View Article and Find Full Text PDFSci Rep
July 2025
School of Integrated Circuits, Xidian University, Xi'an, 710071, China.
Thermal and power integrity management remains a fundamental challenge in 2.5-dimensional (2.5D) integrated microsystem design.
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