SBIR Phase I: An Artificial Intelligence System to Accelerate Semiconductor Production using Physics-embedded Lithographic Foundation Model

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是加快下一代半导体芯片的广泛采用，这是推动跨行业和社会技术创新的主要因素。随着技术的快速发展，半导体制造中转向极紫外光刻（EUV）系统大大增加了设计和制造的复杂性，导致过高的成本和扼杀创新。该项目旨在通过将领先的人工智能集成到这些复杂的过程中来缓解设计和制造瓶颈。这项创新旨在显著提高效率，降低成本，加快新芯片设计的上市时间，克服当前下一代工艺节点的限制。重要的是，该提案旨在加强国内半导体能力，这是维持美国国家安全、全球竞争力和技术领先地位的关键因素。这个小企业创新研究第一阶段项目的重点是在快速发展的半导体技术中推进最先进的人工智能模拟光刻技术。随着技术的发展和工艺精度的提高，微小的设计和制造偏差，如3D掩模效应和随机变化，不能再被忽视。解决这一日益出现的技术挑战需要一个快速而精确的仿真工具，这对于优化产量、产量和上市时间至关重要，以保持在市场上的竞争力。拟议的工作将创建光刻基础模型（LFM），这是一个将物理深入集成到其框架中的系统，可以理解极紫外光刻过程的复杂动力学。将物理建模嵌入到LFM的技术方法可以在任何过程条件的排列中实现严格的准确性。再加上领先的硬件软件优化，LFM承诺以极高的精度进行实时模拟。LFM的多功能性和模块化使各种工艺的应用成为可能，包括工艺仿真、布局校正和可制造性优化。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to expedite the wide adoption of next-generation semiconductor chips, which is a major factor in driving technological innovation across industries and societies. As technologies rapidly evolve, shifting to extreme ultraviolet lithography (EUV) systems in semiconductor manufacturing has significantly increased design and manufacturing complexities, leading to prohibitively high costs and stifling innovation. This project aims to alleviate the design and manufacturing bottlenecks by integrating leading-edge artificial intelligence into these complex processes. This innovation aims to significantly boost efficiency, reduce costs, and accelerate time-to-market for new chip designs, overcoming current limitations in next-generation process nodes. Importantly, this proposal is poised to strengthen domestic semiconductor capabilities, a crucial element for maintaining U.S. national security, global competitiveness, and technological leadership.This Small Business Innovation Research Phase I project is focused on advancing state-of-the-art artificial intelligence for simulating photolithography in rapidly emerging semiconductor technologies. As technology evolves and process precisions improve, minor design and manufacturing deviations, such as the 3D mask effect and stochastic variations, can no longer be neglected. Addressing this arising technical challenge requires a swift and precise simulation tool, essential for optimizing yield, throughput, and time-to-market, to maintain competitiveness in this market. The proposed work will create the Lithography Foundation Model (LFM), a system with physics integrated deeply into its framework that understands the intricate dynamics of extreme ultraviolet lithography processes. The technical approach of embedding physical modeling into LFM enables rigorous accuracy across any permutations of process conditions. Coupled with leading-edge hardware-software optimization, LFM promises real-time simulations with exceptional precision. The versatility and modularity of LFM enables applications for various processes, including process simulation, layout correction, and manufacturability optimization.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.