Illuminating the Challenges in Extreme Ultraviolet Patterning Materials

While extreme ultraviolet (EUV) lithography has sustained Moore’s Law, its continued advancement toward the Angstrom era demands significant breakthroughs in patterning materials. The dominant challenge lies in achieving atomic-scale control over spatial, temporal, and chemical properties to overcome stochastics and sensitivity limitations. Addressing this challenge requires a paradigm shift in materials design, enabling precision at the molecular and atomic scales. Without the fundamental understanding of these mechanisms, and the rational design strategies such understanding enables, progress in materials will inevitably lag behind the rapid developments in optical resolution which benefit from analytic design methods and tools. In this manuscript, we share our perspective on these challenges and summarize promising research directions to unlock new knowledge in patterning materials for EUV. First, we motivate the topic by looking at the role of patterning materials in the context of EUV lithography and the new physics and chemistry arising from the use of EUV photons. Second, we address the photon and chemical stochastics challenges and their impact on image formation and material design. We then share some perspectives on promising material platforms that could enable new ways to gain insights into the radiation-driven patterning mechanisms and potentially lead to rational design of patterning functionality with precise control at the molecular scale. This includes polypeptoids offering a platform to build monodisperse, sequence-defined architectures with precise functional group placement as well as molecular layer deposition providing precise control of resist composition in the vertical direction. Recognizing that stochastics mitigation goes beyond the photoresist, we go on to discuss bottom-up materials and systems for stochastics remediation and atomically precise pattern transfer both in the form of directed self-assembly as well as area selective deposition and vapor phase infiltration. We also address multimodal characterization challenges and opportunities from the perspective of both secondary electrons as well as chemical imaging. Lastly, we describe computational methods to connect the chemical composition and molecular structure of EUV resists with the physics and chemistry of patterning processes including the use of artificial intelligence driven techniques enabling rapid testing and discovery of new photoresist designs.