Department of Chemistry and R.E. Smalley Institute for Nanoscale Science and Technology, Rice University, Houston, Texas 77005, USA.
Nat Nanotechnol. 2010 Jun;5(6):443-50. doi: 10.1038/nnano.2010.68. Epub 2010 May 9.
Existing methods for growing single-walled carbon nanotubes produce samples with a range of structures and electronic properties, but many potential applications require pure nanotube samples. Density-gradient ultracentrifugation has recently emerged as a technique for sorting as-grown mixtures of single-walled nanotubes into their distinct (n,m) structural forms, but to date this approach has been limited to samples containing only a small number of nanotube structures, and has often required repeated density-gradient ultracentrifugation processing. Here, we report that the use of tailored nonlinear density gradients can significantly improve density-gradient ultracentrifugation separations. We show that highly polydisperse samples of single-walled nanotubes grown by the HiPco method are readily sorted in a single step to give fractions enriched in any of ten different (n,m) species. Furthermore, minor variants of the method allow separation of the mirror-image isomers (enantiomers) of seven (n,m) species. Optimization of this approach was aided by the development of instrumentation that spectroscopically maps nanotube contents inside undisturbed centrifuge tubes.
现有的单壁碳纳米管生长方法会产生具有一系列结构和电子特性的样品，但许多潜在应用需要纯纳米管样品。密度梯度超速离心最近已成为一种将生长的单壁纳米管混合物按其独特的（n，m）结构形式进行分类的技术，但迄今为止，这种方法仅限于仅包含少量纳米管结构的样品，并且通常需要重复进行密度梯度超速离心处理。在这里，我们报告说，使用定制的非线性密度梯度可以显著改善密度梯度超速离心分离。我们表明，通过 HiPco 方法生长的高度多分散单壁纳米管样品可以很容易地在一步中进行分类，从而得到十种不同（n，m）物种中任何一种的富集分数。此外，该方法的变体还可以分离七种（n，m）物种的镜像异构体（对映异构体）。通过开发一种可以在不干扰离心管的情况下对管内纳米管含量进行光谱映射的仪器，优化了这种方法。
