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

FuSe：用于定向自组装的精确序列特定嵌段共聚物 - 用于图案质量、缩放和制造的光刻材料的协同设计

• 批准号: 2329133
• 负责人: Paul Nealey
• 金额: $ 192.5万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-11-01 至 2026-10-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2329133&HistoricalAwards=false
• 关键词: FuSe; Precise; Sequence; Specific; Block

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.

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. 光刻或图案是半导体制造的促成技术。 最近，用于最高分辨率光刻的光已从193纳米仪表的波长变为更伟大的极端超紫罗兰（EUV）光，波长为13.5纳米米。 这种破坏性的进步使在较小的维度上具有图案，以制造更强大，更快的半导体设备。 该项目将利用材料和过程共同设计的概念，通过称为EUV加上定向自组装（DSA）的策略来增强EUV光刻过程。 在此处开发的生物学和医学科学中开发的工具将用于合成含有BCP的多肽，以高精度和EUV加上DSA应用的增强材料特性的均匀性。 结合具有图案科学和美国半导体制造竞争力的进步，实习计划将在洁净室操作中为大学洁净室的2年社区大学生提供动手培训，以使他们成为职业，作为高级半导体制造技术人员的职业。半导体制造的图案。 研究小组将通过称为EUV加上定向自组装（DSA）的策略（DSA）来利用材料和过程共同设计的概念。 为EUV加上DSA设计BCP的问题是需要一个综合的材料平台：1）了解高chi低N系统的基本新物理学，2）工程师在每个目标分辨率上工程师多次优化的相协方差为不同的BCP化学属性，3）确保商业化的强大材料供应链。 将采用A块（B随机-C）结构从表面和界面特性中解脱热力学特性（CHI，CHI），并允许优化或设计过的相互变化特性，例如BCP层状周期（分辨率）（分辨率）（分辨率），嵌段表面能量（嵌段表面能量）（直到膜到膜的范围内范围内的范围内），较高的范围（较高的范围），较高的范围（直线），较低的范围（较低）。 该研究的重点是基于多肽的BCP的发展。重要的是，基于多肽的块共聚物为B-R-C块中的工程序列特异性提供了机会，以共同设计钥匙EUV加上DSA性能，表面能，块之间接口的宽度和模式传递。 高chi和低N系统不遵守传统的BCP理论和缩放定律，并且将发现和利用多肽系统的新物理学，以优化光刻应用的材料。 多肽平台非常适合机器学习方法，以优化属性并了解这些系统的新物理。使用固相合成在数量中制造的零分散性的序列和组成特异性BCP将实现实验，理论和计算的前所未有的整合，包括机器学习以理解和利用构图的紧急行为。这项奖项反映了NSF的法定任务，并通过使用基金会的智能效果和广泛的范围进行了评估。