FuSe: Precise Sequence Specific Block Copolymers for Directed Self-Assembly - Co-Design of Lithographic Materials for Pattern Quality, Scaling, and Manufacturing

在未来半导体(FUSE)计划的支持下，芝加哥大学的Paul Nealey和Juan de Pablo教授、康奈尔大学的Christopher Ober教授和威斯康星大学麦迪逊分校的Whitney Loo教授将在半导体制造的背景下设计、合成和研究用于大容量高分辨率图形的新材料和工艺。光刻或图案化是半导体制造的使能技术。最近，用于最高分辨率光刻的光已经从193纳米的波长改变为更高能量的13.5纳米波长的极端紫外线(EUV)光。这种颠覆性的进步使尺寸更小的图形能够制造出功能更强大、速度更快的半导体器件。该项目将利用材料和工艺共同设计的概念，通过一种称为EUV加定向自组装(DSA)的策略来增强EUV光刻工艺。在生物和医学科学中开发的工具将在这里用于合成含有BCP的多肽，以实现EUV+DSA应用的高精度和增强材料特性的一致性。随着构图科学的进步和美国半导体制造竞争力的提高，一个实习项目将在大学洁净室为两年制社区大学生提供洁净室操作方面的实践培训，以推动他们进入高水平半导体制造技术人员的职业生涯。该项目专注于设计和合成新的嵌段共聚物(BCP)材料及其在半导体制造中大容量高分辨率EUV基图形的应用。研究小组将利用材料和工艺共同设计的概念，通过一种称为EUV加定向自组装(DSA)的策略来增强EUV光刻工艺。为EUV和DSA设计BCP的一个问题是需要一个全面的材料平台，以：1)了解支配高CHI和低N系统的基本新物理，2)在每个目标分辨率下将多个优化的协变属性设计到不同的BCP化学中，以及3)确保用于商业化的强大材料供应链。A-块-(B-随机-C)结构将用于将热力学性质(CHI、CHI)与表面和界面性质分离，并允许优化或设计共变性质，例如BCP片层周期(分辨率)、块表面能(穿透膜区的垂直取向)、域间的尖锐界面(低线边缘粗糙度)和图案转移能力。本研究的重点是基于多肽的BCPs的开发。重要的是，基于多肽的嵌段共聚物提供了在B-R-C嵌段中设计序列特异性的机会，以共同设计关键的EUV和DSA特性、表面能、嵌段之间的界面宽度和图案转移。高CHI和低N体系不遵守传统的BCP理论和标度定律，多肽体系的新物理将被发现和开发，以优化材料用于光刻应用。多肽平台非常适合机器学习方法，以优化性能和了解这些系统的新物理。序列和组成使用固相合成大量制造的具有零分散性的特定BCP将实现实验、理论和计算的前所未有的集成，包括机器学习，以了解和利用紧急行为进行模式识别。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

With the support of the Future of Semiconductors (FuSe) Program, Professors Paul Nealey and Juan de Pablo at the University of Chicago, Professor Christopher Ober at Cornell University, and Professor Whitney Loo at the University of Wisconsin-Madison will design, synthesize and investigate new materials and processes for high-volume high-resolution patterning in the context of semiconductor manufacturing. Lithography or patterning is the enabling technology for semiconductor manufacturing. Recently the light used for the highest resolution lithography has changed from a wavelength of 193 nano meter to a more energetic extreme ultra-violet (EUV) light with a wavelength of 13.5 nano meter. This disruptive advance enabled patterning at smaller dimensions to manufacture ever more powerful and faster semiconductor devices. This project will capitalize on the concept of co-design of materials and processes to enhance the EUV lithographic process through a strategy known as EUV plus directed self-assembly (DSA). Tools that were developed in the biological and medical sciences will be used here to synthesize polypeptoid containing BCPs for high precision and uniformity of augmented material properties for EUV plus DSA applications. Coupled to the advancement of patterning science and US semiconductor manufacturing competitiveness, an internship program will provide hands-on training in cleanroom operations to 2-year community college students in university cleanrooms in order to propel them into careers as high-level semiconductor manufacturing technicians .The project is focused on the design and synthesis of new block copolymer (BCP) materials and their use for high-volume high-resolution EUV-based patterning for semiconductor manufacturing. The research team will capitalize on the concept of co-design of materials and processes to enhance the EUV lithographic process through a strategy known as EUV plus directed self-assembly (DSA). An issue in designing BCPs for EUV plus DSA is the need for a comprehensive materials platform to: 1) understand the fundamental new physics governing high chi low N systems, 2) engineer multiple optimized covarying attributes into different BCP chemistries at each target resolution, and 3) ensure a robust materials supply chain for commercialization. A-block-(B-random-C) architectures will be employed to decouple thermodynamic properties (chi, chiN) from surface and interfacial properties and to allow for optimized or engineered covarying properties such as BCP lamellar period (resolution), block surface energies (perpendicular orientation of through film domains), sharp interfaces between domains (low line edge roughness), and pattern transfer capabilities. The research is focused on the development of BCPs based on polypeptoids. Importantly, polypeptoid-based block copolymers provide opportunities to engineer sequence specificity in the B-r-C block to co-design key EUV plus DSA properties, surface energy, width of interfaces between blocks, and pattern transfer. High chi and low N systems do not obey traditional BCP theory and scaling laws, and new physics of the polypeptoid systems will be discovered and exploited to optimize materials for the lithographic applications. The polypeptoid platform is ideally suited for machine learning approaches to optimize properties and to understand the new physics of these systems. Sequence and composition specific BCPs with zero dispersity made in quantity using solid-phase synthesis will enable unprecedented integration of experiment, theory, and computation, including machine learning to understand and exploit emergent behavior for patterning.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.