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Material Chemistry of Two-Dimensional Inorganic Nanosheets in Cancer Theranostics

Open access
Yang, Bowen, Chen, Yu, Shi, Jianlin·2018·Chem

Abstract

Summary Recent advances in two-dimensional (2D) chemistry have led to the rapid development of research on the emerging 2D inorganic nanomaterials in various fields, such as condensed matter physics, material science, chemistry, biology, and nanotechnology. As a special cross-disciplinary research frontier, 2D inorganic nanosheets for oncological applications, which are capable of accomplishing desirable theranostic performance, have attracted great attention from the scientific community in recent years. In this review, we summarize the underlying fundamental principles for the material chemistry of the 2D inorganic family in cancer theranostics and nano-enabled amalgamation of material chemistry and oncology on the basis of the recent progress in theranostic platforms based on 2D inorganic nanosheets. Moreover, current challenges and perspectives on the development of 2D inorganic nanosheets for further clinical translations are also discussed. It is expected that this emerging 2D inorganic family will play a vital role in next-generation cancer theranostics.

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Metadata

Authors
Yang, B., Chen, Y., & Shi, J.
Venue
Chem
Publisher
Elsevier BV
Published
2018-06
Volume
4
Issue
6
Pages
1284-1313
ISSN
2451-9294 (ISSN-L)
OpenAlex
W2789892162
Cited by
170
References
2
FWCI
9.72
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Material Chemistry of Two-Dimensional Inorganic Nanosheets in Cancer Theranostics. https://app.cochat.ai/papers/10.1016/j.chempr.2018.02.012
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Yang, B., Chen, Y., & Shi, J. (2018). Material Chemistry of Two-Dimensional Inorganic Nanosheets in Cancer Theranostics. Chem. https://doi.org/10.1016/j.chempr.2018.02.012

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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.