Multi-Physics Modeling and Experimental Characterization of Needleless Electrospinning for Scalable Nanofiber Production

用于可扩展纳米纤维生产的无针静电纺丝的多物理场建模和实验表征

• 批准号: 1234297
• 负责人: Xiangfa Wu
• 金额: $ 21.83万
• 依托单位: North Dakota State University Fargo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1234297&HistoricalAwards=false
• 关键词: Multi; Physics; Modeling; Experimental; Characterization

This grant provides funding for research enabling the development of a fully three-dimensional multiphysics phase-field model and related experimentation for understanding of the electrohydrodynamic process of needleless electrospinning. Needleless electrospinning, based on free liquid-surface jetting, is a novel low-cost, top-down nanomanufacturing technique capable of continuous, scalable production of nanofibers of natural and synthetic polymers and polymer-derived carbon, ceramics, semiconductors, metals, metal oxides, etc. for broad applications in filtration, biomedical engineering, energy conversion and storage, nanocomposites, and so on. The developed computational model formulates a generalized free energy of an electrospinning system that is capable of uniformly treating the multiphysics, multiphase phenomenon of the process including multi-jet initiation, jet stretching, phase separation, drying, etc. The developed phase-field model can overcome the numerical difficulty in tracking the instantaneous profile of the liquid surface after multi-jetting and pore formation. Efficient semi-implicit spectral algorithm will be used for fast, robust numerical simulation. The model will determine several key parameters used in needleless electrospinning and be validated by controlled experimentation.If successful, the results will establish solid theoretical foundation for needleless electrospinning and the predictive computational model will generate a wealth of fundamental knowledge for design, optimization and control of needleless electrospinning and other electrohydrodynamics-related devices (e.g., electrospray) for reliable, efficient, mass production. The results will benefit the computer-aided electrospinning engineering (CAEE) in education, research and industrial applications. The research provides a variety of opportunities for graduates and undergraduates, specially unrepresented minorities including Native American students and female students, to involve in the cutting-edge nanotechnology and computational materials science. The research will be demonstrated to K-12 students and students in the regional Native American tribal colleges. The results will be used for updating the relevant undergraduate and graduate curriculum materials and the development of a new cross-listed course at North Dakota State University.

这笔赠款为能够开发全三维多物理相场模型的研究和相关实验提供资金，以了解无针电纺的电流体动力学过程。无针电纺是一种基于自由液体表面喷射的新型低成本、自上而下的纳米制造技术，能够连续、可规模地生产天然和合成聚合物以及聚合物衍生的碳、陶瓷、半导体、金属、金属氧化物等纳米纤维，在过滤、生物医学工程、能量转换和存储、纳米复合材料等方面有着广泛的应用。建立的计算模型描述了电纺系统的广义自由能，它能够统一地处理电纺过程中的多物理、多相现象，包括多射流引发、喷射拉伸、相分离、干燥等，所建立的相场模型可以克服跟踪多次喷射和成孔后液体表面瞬时轮廓的数值困难。高效的半隐式谱算法将用于快速、稳健的数值模拟。该模型将确定用于无针电纺的几个关键参数，并通过控制实验进行验证。如果成功，结果将为无针电纺奠定坚实的理论基础，预测计算模型将为无针电纺和其他与电流体力学相关的设备(如电喷雾)的设计、优化和控制提供丰富的基础知识，从而实现可靠、高效、大规模生产。研究结果将有助于计算机辅助电纺工程在教育、研究和工业应用中的应用。这项研究为毕业生和本科生，特别是没有代表性的少数族裔，包括美洲原住民学生和女性学生，提供了参与尖端纳米技术和计算材料科学的各种机会。这项研究将向K-12学生和地区性美洲原住民部落学院的学生演示。结果将用于更新相关的本科生和研究生课程材料，并在北达科他州州立大学开发一门新的交叉列出的课程。