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

该补助金为研究提供资金，以便开发一个完全三维的多物理场相场模型和相关实验，以了解无针静电纺丝的电流体动力学过程。基于自由液体表面喷射的无针静电纺丝是一种新型的低成本、自上而下的纳米制造技术，其能够连续、可规模化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、金属氧化物等的纳米纤维，用于过滤、生物医学工程、能量转换和储存、纳米复合材料、所开发的计算模型用公式表示了静电纺丝系统的广义自由能，该系统能够统一地处理该过程的多物理场、多相现象，包括多射流引发、射流拉伸、相分离、干燥，相场模型克服了数值计算中难以跟踪多次喷射和成孔后液面瞬时轮廓的困难。高效的半隐式谱算法将用于快速，鲁棒的数值模拟。该模型将确定用于无针静电纺丝的几个关键参数，并通过控制实验进行验证。如果成功，结果将为无针静电纺丝奠定坚实的理论基础，预测计算模型将为无针静电纺丝和其他电流体动力学相关设备（例如，电喷雾）用于可靠、高效、大规模生产。研究结果将有助于计算机辅助静电纺丝工程（CAEE）在教育、研究和工业应用中的应用。这项研究为研究生和本科生，特别是包括美国原住民学生和女学生在内的未被代表的少数民族提供了各种机会，让他们参与尖端的纳米技术和计算材料科学。这项研究将展示给K-12学生和学生在区域美洲原住民部落学院。研究结果将用于更新相关的本科和研究生课程材料，并在北达科他州州立大学开发一个新的交叉上市课程。

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.