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Cited by 1,368

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Supramolecular Chemistry on Water-Soluble Carbon Nanotubes for Drug Loading and Delivery

Liu, Zhuang, Sun, Xiaoming, Nakayama-Ratchford, Nozomi, Dai, Hongjie·2007·ACS Nano

Abstract

We show that large surface areas exist for supramolecular chemistry on single-walled carbon nanotubes (SWNTs) prefunctionalized noncovalently or covalently by common surfactant or acid-oxidation routes. Water-soluble SWNTs with poly(ethylene glycol) (PEG) functionalization via these routes allow for surprisingly high degrees of pi-stacking of aromatic molecules, including a cancer drug (doxorubicin) with ultrahigh loading capacity, a widely used fluorescence molecule (fluorescein), and combinations of molecules. Binding of molecules to nanotubes and their release can be controlled by varying the pH. The strength of pi-stacking of aromatic molecules is dependent on nanotube diameter, leading to a method for controlling the release rate of molecules from SWNTs by using nanotube materials with suitable diameter. This work introduces the concept of "functionalization partitioning" of SWNTs, i.e., imparting multiple chemical species, such as PEG, drugs, and fluorescent tags, with different functionalities onto the surface of the same nanotube. Such chemical partitioning should open up new opportunities in chemical, biological, and medical applications of novel nanomaterials.

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Metadata

Authors
Liu, Z., Sun, X., Nakayama-Ratchford, N., & Dai, H.
Venue
ACS Nano
Published
2007-08-01
Volume
1
Issue
1
Pages
50-56
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2161105252
Cited by
1,368
References
1
FWCI
31.26
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Supramolecular Chemistry on Water-Soluble Carbon Nanotubes for Drug Loading and Delivery. https://app.cochat.ai/papers/10.1021/nn700040t
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Liu, Z., Sun, X., Nakayama-Ratchford, N., & Dai, H. (2007). Supramolecular Chemistry on Water-Soluble Carbon Nanotubes for Drug Loading and Delivery. ACS Nano. https://doi.org/10.1021/nn700040t

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.