一个双阶段的Unet框架,用于分分辨率辅助功能预测.
Mu Lin1, Le Ma2,3, Lisong Dong2,3
1Key Laboratory of Photoelectronic Imaging Technology and System of Ministry of Education of China, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China.
Micromachines
|November 27, 2025
概括
这项研究引入了一种新的两阶段Unet框架,用于预测分辨率辅助特征 (SRAF) 参数,提高光刻精度. 该方法通过显著减少图案和边缘放置错误来提高图像保真度.
科学领域:
- 半导体制造业 半导体制造业
- 摄影石刻法 (photolithography) 是一种摄影方式.
- 计算机成像成像技术
背景情况:
- 亚分辨率辅助功能 (SRAFs) 对于在先进的光刻中增强对比度和过程窗口至关重要.
- 现有的SRAF方法 (基于模型,基于规则和端到端的学习) 在适应性,计算成本或精确的几何参数提取方面存在局限性.
研究的目的:
- 开发一种有效的基于学习的方法,用于精确的SRAF参数预测,特别是曼哈顿SRAFs.
- 为了提高SRAF图案生成在石版画的准确性和效率.
主要方法:
- 提出了一个两阶段的UNET框架,用于预测SRAF多边形的中心坐标和维度.
- 集成了自适应式混合注意力机制,以增强功能集成和预测准确性.
- 为了稳定和更快的培训,采用了热身等号化学习率策略.
主要成果:
- 拟议的方法准确且快速估计SRAF参数.
- 实现了从25776.44降至15203.33的平均模式误差 (PE) 和从5.8367降至3.5283的边缘位置误差 (EPE) 的显著降低.
- 与传统的神经网络相比,该方法在预测SRAF模式方面表现优异.
结论:
- 具有自适应混合注意力机制的两阶段Unet框架为SRAF参数预测提供了有效的解决方案.
- 这种方法显著提高了石版系统的图像保真度.
- 该方法克服了以前的SRAF技术的局限性,提供了更高的准确性和效率.
相关概念视频
02:27Predicting Products: SN1 vs. SN2
Nucleophilic substitution reactions of alkyl halides can proceed via an SN1 or an SN2 mechanism. While in SN2 reactions, the nucleophile attacks the substrate simultaneously as the leaving group departs, in SN1 reactions, the substrate first dissociates to give the carbocation intermediate. Various factors such as the structure of the substrate, the strength of the nucleophile, and the nature of the solvent promote one mechanism over the other.
With increased substitution on the alkyl halide,...
With increased substitution on the alkyl halide,...
02:52Predicting Products: Substitution vs. Elimination
When a nucleophile and an alkyl halide react, nucleophilic substitution and β-elimination reactions compete to generate products.
The following factors can influence the mechanisms competing against each other:
The following factors can influence the mechanisms competing against each other: