Superior mechanical properties of natural, hierarchical materials have motivated research in developing synthetic materials with biomimetic structures. Carbon nanotubes (CNTs) are a promising synthetic analog to structural biomolecules like collagen, because individual CNTs boast exceptional mechanical properties (100-GPa strength, 1-TPa stiffness), form packed bundles analogous to collagen microfibrils, and can be assembled into more complex 1D (fiber, yarn), 2D (sheet) [1, 2], and 3D (foam, scaffold) [3] structures. The hierarchical organization of these CNT materials is reminiscent of that of collagen fibers in diverse tissues like tendons and ligaments (1D), skin (2D), and vitreous (3D).
Unfortunately, despite advances in design and processing of bioinspired CNT materials, their macroscale properties have fallen short from those of both individual CNT building blocks as well as their biological counterparts, likely due to inefficient load transfer between hierarchical levels. Drawing structure-property relationships across length scales for hierarchical CNT materials is critical to guide the rational design of their multiscale organization toward resolving these shortcomings, but probing structural characteristics across orders-of-magnitude differences in length scale is challenging.
To address this need, we have developed advanced metrology to map size and order in hierarchically organized, 1D nanostructures spanning four orders of magnitude in length scale - atomic, nano, meso, micro. Using a suite of novel soft and hard X-ray scattering beamlines at the Advanced Light Source (ALS) and Linac Coherent Light Source (LCLS), we quantitatively mapped structural characteristics in self-aligned, anisotropic CNT forests grown by chemical vapor deposition, both spatially within the CNT material and across several length scales (0.1-1000 nm).
Furthermore, we developed a unified analytical model to quantitatively describe the structural hierarchy of aligned CNTs and to extract key structural parameters via curve-fitting of our X-ray scattering data. From the bottom up, our model parameters define the graphitic lattice and wall number (atomic), CNT diameter (nano), CNT bundling and spacing (meso), regular corrugations (micro), and number density (macro), and comparison with electron microscopy reveals good agreement for forests with a wide range of characteristics (e.g., 1-11 walls, 1.5-15 nm diameter, 1010-1012 cm-2 density). Finally, we offer insights into how our methodology and results can inform existing mechanical models and advance hierarchical CNT materials design to match not only the structure but also the properties of biological materials.