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Cited by 284

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Coupling carbon nanomaterials with photochromic molecules for the generation of optically responsive materials

Open access
Zhang, Xiaoyan, Hou, Lili, Samorì, Paolo·2016·Nature Communications

Abstract

Multifunctional carbon-based nanomaterials offer routes towards the realization of smart and high-performing (opto)electronic (nano)devices, sensors and logic gates. Meanwhile photochromic molecules exhibit reversible transformation between two forms, induced by the absorption of electromagnetic radiation. By combining carbon-based nanomaterials with photochromic molecules, one can achieve reversible changes in geometrical structure, electronic properties and nanoscale mechanics triggering by light. This thus enables a reversible modulation of numerous physical and chemical properties of the carbon-based nanomaterials towards the fabrication of cognitive devices. This review examines the state of the art with respect to these responsive materials, and seeks to identify future directions for investigation.

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Metadata

Authors
Zhang, X., Hou, L., & Samorì, P.
Venue
Nature Communications
Published
2016-04-12
Volume
7
Issue
1
Pages
11118-11118
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2340910556
Cited by
284
References
48
FWCI
16.30
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Coupling carbon nanomaterials with photochromic molecules for the generation of optically responsive materials. https://app.cochat.ai/papers/10.1038/ncomms11118
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Zhang, X., Hou, L., & Samorì, P. (2016). Coupling carbon nanomaterials with photochromic molecules for the generation of optically responsive materials. Nature Communications. https://doi.org/10.1038/ncomms11118

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.