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过程-形态缩放关系量化了毛细管致密化纳米纤维阵列中的自组织。

Process-morphology scaling relations quantify self-organization in capillary densified nanofiber arrays.

作者信息

Kaiser Ashley L, Stein Itai Y, Cui Kehang, Wardle Brian L

机构信息

Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

出版信息

Phys Chem Chem Phys. 2018 Feb 7;20(6):3876-3881. doi: 10.1039/c7cp06869g.

Abstract

Capillary-mediated densification is an inexpensive and versatile approach to tune the application-specific properties and packing morphology of bulk nanofiber (NF) arrays, such as aligned carbon nanotubes. While NF length governs elasto-capillary self-assembly, the geometry of cellular patterns formed by capillary densified NFs cannot be precisely predicted by existing theories. This originates from the recently quantified orders of magnitude lower than expected NF array effective axial elastic modulus (E), and here we show via parametric experimentation and modeling that E determines the width, area, and wall thickness of the resulting cellular pattern. Both experiments and models show that further tuning of the cellular pattern is possible by altering the NF-substrate adhesion strength, which could enable the broad use of this facile approach to predictably pattern NF arrays for high value applications.

摘要

毛细管介导的致密化是一种廉价且通用的方法,可用于调节块状纳米纤维(NF)阵列(如排列的碳纳米管)的特定应用性能和堆积形态。虽然NF长度控制着弹性毛细管自组装,但现有理论无法精确预测由毛细管致密化的NF形成的细胞图案的几何形状。这源于最近量化的比预期低几个数量级的NF阵列有效轴向弹性模量(E),在此我们通过参数实验和建模表明,E决定了所得细胞图案的宽度、面积和壁厚。实验和模型均表明,通过改变NF与基底的粘附强度可以进一步调节细胞图案,这可能使这种简便方法能够广泛用于可预测地为高价值应用对NF阵列进行图案化。

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