The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Recent advances in colloidal photonic crystal sensors: Materials, structures and analysis methods
Abstract
Abstract Colloidal photonic crystal (PC) sensors have been well developed due to their unique advantages in preparation and functionalization, and have been applied into diverse sensing systems. Recently, many breakthroughs about new-type colloidal PC sensors with fast respond speed, high sensitivity and excellent selectivity have been achieved. In this review, we summarize the recent advances of colloidal PC sensors from aspects of materials, structures, and analysis methods, to exhibit the diverse developing strategies. Firstly, an overview of colloidal PC sensors composed of new responsive materials is presented. Next, the unique structures are systematically summarized according to their scale increasing from nanoscale to macroscale, including the colloidal nanoparticles with novel structures and morphologies, the micro-sized PC units, and the integrated PC devices. Then, two series of new analysis methods, cross-reactive analysis based on PC sensors and time/spatial resolved reflection spectra analysis, are highlighted and discussed in details because they can greatly improve the selectivity of recognitions. Finally, a summary and some perspectives on several development directions in this attractive research field are presented.
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Cites
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Cited by
Cai, Z., Li, Z., Ravaine, S., He, M., Song, Y., Yin, Y., Zheng, H., Teng, J., & Zhang, A. (2021) · Chemical Society Reviews · doi:10.1039/d0cs00706d · Cited by 542
Self-citationRecent advances in the design of colorimetric sensors for environmental monitoring
Liu, B., Zhuang, J., & Wei, G. (2020) · Environmental Science: Nano · doi:10.1039/d0en00449a · Cited by 482
Colloidal Self-Assembly Approaches to Smart Nanostructured Materials
Li, Z., Fan, Q., & Yin, Y. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00482 · Cited by 468
Metadata
- Authors
- Hou, J., Li, M., & Song, Y.
- Venue
- Nano Today
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 22
- Pages
- 132-144
- ISSN
- 1748-0132 (ISSN-L)
- OpenAlex
- W2889222561
- Cited by
- 221
- References
- 5
- FWCI
- 9.81
- Type
- journal article
- Language
- en
- Open access
- closed
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