Sbir phase II: physics-guided AI platform for accelerating extreme ultraviolet (EUV) mask design

Exigent Solutions, Inc. received a $1,168,940 Cooperative Agreement from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships program (CFDA 47.084), effective September 1, 2025, through August 31, 2027. The award funds an Small Business Innovation Research (SBIR) Phase II project to develop a physics-guided artificial intelligence (AI) platform designed to accelerate Extreme Ultraviolet (EUV) mask design and optimization for semiconductor manufacturing. The platform integrates high-fidelity EUV lithography simulation, process adaptation, and multi-objective layout optimization into a scalable neural network architecture that embeds fundamental optical and materials physics. The solution enables manufacturers to deliver manufacturable mask layouts in hours rather than weeks by exploring billions of potential design adjustments simultaneously to improve pattern fidelity, yield, and production economics.

The broader impact of this technology centers on strengthening domestic semiconductor manufacturing capacity during a period of global supply-chain realignment. By reducing design-to-manufacturing cycles, lowering production costs, and minimizing waste, the platform supports faster delivery of high-performance electronics critical to cloud computing, artificial intelligence applications, and national infrastructure. The project aligns with federal initiatives to expand onshore chipmaking while fostering a skilled workforce at the intersection of machine learning and semiconductor engineering through internships and training programs, ultimately promoting technological sovereignty and economic competitiveness.

Abstract

The broader impact/commercial potential of this small business innovation research (sbir) phase II project is to strengthen domestic semiconductor manufacturing capacity at a time of global supply-chain realignment and unprecedented demand for advanced chips. By providing an intelligent software platform that shortens design-to-manufacturing cycles, the project supports faster delivery of high-performance, energy-efficient electronics that underpin cloud computing, artificial intelligence (AI), and critical infrastructure. The approach reduces waste, lowers production costs, and helps keep cutting-edge semiconductor fabrication in the united states, aligning with recent national initiatives to expand on-shore chipmaking and create high-skill jobs. In addition to enabling smaller, more capable devices for consumers and industry, the technology nurtures a new workforce at the intersection of machine learning and semiconductor engineering through internships and workforce trainings. Collectively, these outcomes promote economic growth, technological sovereignty, and increased access to computation resources by maximizing utilization of fabrication assets. The proposed project tackles the escalating complexity and turnaround delays in extreme ultraviolet (EUV) mask design by advancing a physics-guided AI platform that fuses high-fidelity EUV lithography simulation, process adaptation, and multi-objective layout optimization into a coherent, scalable service. Instead of relying on traditional rule-based models or hardware-specific software, the framework embeds fundamental optical and materials physics inside a scalable neural network architecture. An integrated optimization engine explores billions of potential design adjustments to simultaneously improve pattern fidelity, yield, and production economics, delivering manufacturable mask layouts in hours rather than weeks. Modular interfaces and modern application programming interfaces (apis) allow rapid integration with existing electronic-design-automation flows, with optimized models to support advanced simulation capabilities to edge devices. Through these innovations, the project seeks to establish a new computational foundation for future lithography nodes, paving the way for faster, lower-cost entry of next-generation chipsets. 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.- subawards are not planned for this award.