Manufacturing USA: Precision Alignment of Roll-to-Roll Printing of Flexible Paper Electronics Through Modeling and Virtual Sensor-based Control

美国制造:通过建模和基于虚拟传感器的控制实现柔性纸电子产品卷对卷印刷的精确对准

基本信息

  • 批准号:
    1907250
  • 负责人:
  • 金额:
    $ 54.42万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-09-01 至 2023-08-31
  • 项目状态:
    已结题

项目摘要

Demand is increasing for advanced manufacturing technologies that can print electronics accurately and at high speed. Roll-to-Roll printing techniques that can continuously transfer a printed electronic pattern onto a flexible substrate are very promising for high-volume production of flexible electronic devices. However, there is a significant challenge to overcome, which is that multilayer printed electronics have very tight alignment tolerance requirements, and there are no reliable tools available to monitor and control the overlay registration accuracy in real-time. To overcome this challenge, this award develops precision alignment of roll-to-roll printing using modeling and virtual sensor-based control. Another challenge is the overwhelming use of plastic as the substrate, which are manufactured from petroleum-based materials and therefore are not biodegradable, making them environmentally hazardous to produce and dispose. To address these challenges, this award pursues paper substrates as recyclable and environmentally friendly alternatives to plastic for flexible electronics. This interdisciplinary project transcends the boundaries of several important fields, including advanced materials engineering, cyber-manufacturing and data analytics. The knowledge attained from this project helps catalyze new technologies in nano and micro additive printing that feed into the innovation pipelines of the Manufacturing USA Institutes. The outcomes of this research benefit next-generation ecologically-friendly flexible electronics, such as, greener disposable sensors for patient care or lower-cost embedded home electronics. Educational activities promote interdisciplinary capstone projects and increase students? hands-on learning experience in manufacturing research. This supports the nationwide effort in educating the next generation manufacturing engineers.The goal of this project is to advance the fundamental understanding of roll-to-roll (R2R) printing of functional paper electronics. The study involves understanding the mechanism for spatial variation generation and its propagation and accumulation. The knowledge on spatial error propagation is used to develop virtual sensing to achieve unprecedented control in the creation, integration and manipulation of multilayer microstructures that form the foundation of printed paper electronics. Furthermore, this project studies materials-process-control-device performance relationships in a closed loop approach. This research expedites intelligent R2R systems with high traceability, predictability and controllability for high-resolution additive printing of flexible paper electronics, enabling a host of technologies spanning sensing, biomedical devices, and renewable energy. The development of R2R printing of electronics on paper ushers in a new era of environmentally-friendly, flexible paper devices such as water quality sensors at throwaway prices.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.
对能够准确高速打印电子产品的先进制造技术的需求正在不断增加。卷对卷印刷技术可以将印刷的电子图案连续转移到柔性基板上,对于柔性电子设备的大批量生产非常有前景。然而,有一个重大挑战需要克服,即多层印刷电子产品具有非常严格的对准公差要求,并且没有可靠的工具可用于实时监控和控制重叠套准精度。为了克服这一挑战,该奖项使用建模和基于虚拟传感器的控制来开发卷对卷打印的精确对准。另一个挑战是大量使用塑料作为基材,塑料是由石油基材料制成的,因此不可生物降解,这使得它们的生产和处置对环境有害。为了应对这些挑战,该奖项致力于将纸基材作为柔性电子产品中塑料的可回收且环保的替代品。这个跨学科项目超越了几个重要领域的界限,包括先进材料工程、网络制造和数据分析。从该项目中获得的知识有助于促进纳米和微米增材印刷新技术的发展,这些技术将被纳入美国制造研究所的创新渠道。这项研究的成果有利于下一代生态友好型柔性电子产品,例如用于患者护理的更环保的一次性传感器或成本更低的嵌入式家用电子产品。教育活动促进跨学科顶点项目并增加学生人数?制造研究的实践学习经验。这支持了全国范围内教育下一代制造工程师的努力。该项目的目标是增进对功能性纸质电子产品卷对卷 (R2R) 打印的基本了解。该研究涉及了解空间变异产生及其传播和积累的机制。空间误差传播的知识用于开发虚拟传感,以实现对多层微结构的创建、集成和操作前所未有的控制,而多层微结构构成了印刷纸电子学的基础。此外,该项目以闭环方法研究材料-过程控制-设备性能关系。这项研究加速了具有高可追溯性、可预测性和可控性的智能 R2R 系统,用于柔性纸电子产品的高分辨率增材打印,从而实现了涵盖传感、生物医学设备和可再生能源的一系列技术。电子产品在纸上的 R2R 打印的发展开创了环保、柔性纸质设备(例如一次性价格的水质传感器)的新时代。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力评估进行评估,认为值得支持。优点和更广泛的影响审查标准。

项目成果

期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Spatial-Terminal Iterative Learning Control for Registration Error Elimination in High-Precision Roll-to-Roll Printing Systems
用于消除高精度卷对卷印刷系统中套准误差的空间终端迭代学习控制
Spatial-Terminal Iterative Learning Control for Registration Error Elimination in High-Precision Roll-to-Roll Printing Systems
用于消除高精度卷对卷印刷系统中套准误差的空间终端迭代学习控制
Virtual sensing and virtual metrology for spatial error monitoring of roll-to-roll manufacturing systems
用于卷对卷制造系统空间误差监控的虚拟传感和虚拟计量
  • DOI:
    10.1016/j.cirp.2019.04.108
  • 发表时间:
    2019-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jin, Xiaoning;Shui, Huanyi;Shpitalni, Moshe
  • 通讯作者:
    Shpitalni, Moshe
Large‐Scale Manufacturing of Pattern‐Integrated Paper Li‐Ion Microbatteries through Roll‐to‐Roll Flexographic Printing
通过卷对卷柔版印刷大规模制造图案集成纸锂离子微电池
  • DOI:
    10.1002/admt.202200303
  • 发表时间:
    2022-05-18
  • 期刊:
  • 影响因子:
    6.8
  • 作者:
    Ying Wang;D. Cao;Xiao Sun;Hao;T. Ji;Xiaoning Jin;J. Morse;Barbara Stewart;Hongli Zhu
  • 通讯作者:
    Hongli Zhu
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Xiaoning Jin其他文献

Chiral porous organic frameworks and their application in enantioseparation.
Natural Scene Text Detection Based on Deep Supervised Fully Convolutional Network
基于深度监督全卷积网络的自然场景文本检测
Optimal Parameters Design for Manufacturability under Unknown Feasibility Constraints
未知可行性约束下可制造性的最优参数设计
An integrated physical-based and parameter learning method for ship energy prediction under varying operating conditions
一种基于物理和参数学习的集成方法,用于不同操作条件下的船舶能量预测
Failure Detection and Remaining Life Estimation for Ion Mill Etching Process Through Deep-Learning Based Multimodal Data Fusion
通过基于深度学习的多模态数据融合进行离子磨蚀刻过程的故障检测和剩余寿命估计

Xiaoning Jin的其他文献

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{{ truncateString('Xiaoning Jin', 18)}}的其他基金

CAREER: Unifying Sensing, Machine Perception and Control for High-precision Micromanufacturing
职业:统一传感、机器感知和控制以实现高精度微制造
  • 批准号:
    1943801
  • 财政年份:
    2020
  • 资助金额:
    $ 54.42万
  • 项目类别:
    Standard Grant

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