Abstract
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.
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Acknowledgements
The authors would like to thank W. Rice, R. Simonette and K.M. Beckingham for experimental advice. We are grateful to the National Science Foundation (grant no. CHE-09098097) and the Welch Foundation (grant no. C-0807) for supporting this research.
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S.G. performed the experiments. S.M.B. and R.B.W. planned the experiments. All authors analysed data and discussed the results. R.B.W. and S.M.B. constructed the vertical mapping spectrofluorometer. S.G. and R.B.W. co-wrote the paper.
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R.B.W. has an equity interest in a company that produces one of the instruments used in this study.
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Ghosh, S., Bachilo, S. & Weisman, R. Advanced sorting of single-walled carbon nanotubes by nonlinear density-gradient ultracentrifugation. Nature Nanotech 5, 443–450 (2010). https://doi.org/10.1038/nnano.2010.68
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DOI: https://doi.org/10.1038/nnano.2010.68
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