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.

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University of Rochester
United States
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