SNM: Modulation of Surface Topography for Scalable Contact Printing

SNM：可扩展接触印刷的表面形貌调制

• 批准号: 1530540
• 负责人: Mitchell Anthamatten
• 金额: $ 149.12万
• 依托单位: University of Rochester
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-15 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1530540&HistoricalAwards=false
• 关键词: SNM; Modulation; Surface; Topography; Scalable

With this award, a team of researchers at the University of Rochester will develop a scalable and versatile contact printing process to broadly benefit nanomanufacturing of high-resolution displays, photonics, sensors, and devices. Compared to conventional nanofabrication processes, nanoscale-printing potentially requires less energy, relies on inexpensive processing tools and generate less waste. A multidisciplinary team will mold responsive shape-memory polymers into patterned surfaces and relate interfacial adhesion to surface microstructure, bulk mechanical properties, and contact load and temperature history. By optimizing the surface's ability to switch adhesion, research could also enable transformative technologies including flow-switchable micro-fluidics, switchable medical adhesives, cell culture and tissue growth templates, and simplified demanufacture of intricate devices to recover materials for recycle or reuse. With an improved understanding of how shape-memory controls material transfer, investigators will optimize printing parameters to obtain robust transfer of inorganic and organic thin films on a large scale. To conclude the project, researchers will team with an industrial partner (eMagin) to apply shape-memory contact printing by manufacturing working organic light emitting diode microdisplays. Undergraduates, including students from underrepresented groups, will take part in intense, modular research experiences that are designed to cycle through the entire scientific loop. An innovative pedagogical approach to engineering education will be explored by integrating research activities into university courses including a team-taught course on nanomanufacturing. Project activities will enhance manufacturing skills of students entering the workforce by providing them multidisciplinary educational experiences in chemical engineering, mechanical engineering, materials science, and chemistry.This technical goal of this project is to develop a scalable nanomanufacturing platform for cost effective, high-resolution additive printing of patterned organic and inorganic thin films. Current elastomer-based contact printing primarily relies on rate modulation to control adhesion and fracture at the stamp-substrate interface. However, rate modulation must be optimized for each ink-substrate-stamp system, and it remains challenging to adapt such processes to meso- and nanoscale patterns. In this project, researchers will utilize responsive shape-memory polymer networks that are molded into patterned surfaces to enable switchable topography and adhesion for precise pick-up and delivery of small portions of materials down to sub-100 nm dimensions. The stamp's mechanical properties and surface structures will be designed to undergo heat-triggered topographical changes, thereby imparting a change to the surface's adhesive properties. Research aims are: (1) to identify shape-memory polymers with switchable mechanical properties and tunable surface energies for use as contact-printing stamps; (2) to use patterned shape-memory stamps with well-defined features and arrays of features to perform, model, and optimize topographical switching, interfacial adhesion and material transfer, (3) to conduct physical, chemical, and mechanical characterization of features and surfaces that have experienced thermomechanical stresses, and (4) to demonstrate additive contact printing of thin films into clean, defect-free and high resolution organic light emitting diode arrays. Unlike other patterning methods, shape-memory contact printing makes efficient use of printed material, is scalable to large-area and flexible substrates, and is not limited in resolution by light diffraction or material diffusion. A central premise is that the manufacturing pathway must be accurate and reliable over time, with no intractable barriers to large-area adoption of the technology. Researchers will address issues that could limit the method's scalability including stamp cycling and durability, cleanliness, and alignment.

有了这个奖项，罗切斯特大学的一个研究小组将开发一种可扩展的多功能接触印刷工艺，以广泛受益于高分辨率显示器，光子学，传感器和设备的纳米制造。与传统的纳米纤维工艺相比，纳米尺度印刷可能需要更少的能源，依赖于廉价的加工工具，产生更少的废物。一个多学科团队将把响应性形状记忆聚合物模塑成图案化表面，并将界面粘附力与表面微观结构、本体力学性能以及接触载荷和温度历史联系起来。通过优化表面切换粘附的能力，研究还可以实现变革性技术，包括流动可切换的微流体，可切换的医用粘合剂，细胞培养和组织生长模板，以及简化复杂设备的拆卸，以回收材料进行回收或再利用。随着对形状记忆如何控制材料转移的进一步了解，研究人员将优化印刷参数，以获得大规模无机和有机薄膜的稳健转移。为了完成该项目，研究人员将与工业合作伙伴（eMagin）合作，通过制造工作有机发光二极管微显示器来应用形状记忆接触印刷。本科生，包括来自代表性不足群体的学生，将参加密集的模块化研究体验，这些体验旨在循环整个科学循环。一个创新的教学方法，工程教育将探索通过整合研究活动到大学课程，包括团队授课的纳米制造课程。项目活动将通过为学生提供化学工程、机械工程、材料科学和化学等多学科的教育经验来提高他们进入劳动力市场的制造技能。该项目的技术目标是开发一个可扩展的纳米制造平台，用于具有成本效益的、高分辨率的图案化有机和无机薄膜的增材打印。 目前基于压模的接触印刷主要依赖于速率调制来控制压模-基底界面处的粘附和断裂。然而，速率调制必须针对每个油墨-基底-印模系统进行优化，并且使这样的过程适应介观和纳米尺度图案仍然具有挑战性。在这个项目中，研究人员将利用响应的形状记忆聚合物网络，这些网络被模制到图案化的表面中，以实现可切换的拓扑结构和粘附力，从而精确拾取和递送小部分材料，尺寸可达100 nm以下。印模的机械性能和表面结构将被设计成经受热触发的形貌变化，从而赋予表面的粘合性能变化。研究目的是：（1）鉴定具有可切换的机械性能和可调的表面能的形状记忆聚合物以用作接触印刷印模;（2）使用具有明确定义的特征和特征阵列的图案化形状记忆印模来执行、建模和优化形貌切换、界面粘附和材料转移，（3）进行物理、化学，和经历热机械应力的特征和表面的机械表征，以及（4）证明将薄膜添加接触印刷成清洁、无缺陷和高分辨率的有机发光二极管阵列。与其他图案化方法不同，形状记忆接触印刷有效地利用了印刷材料，可扩展到大面积和柔性基板，并且不受光衍射或材料扩散的分辨率限制。一个核心前提是，随着时间的推移，制造路径必须准确可靠，没有难以克服的障碍，大面积采用该技术。研究人员将解决可能限制该方法可扩展性的问题，包括邮票循环和耐用性，清洁度和对齐。