The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Selective detection of Fe3+ ions based on fluorescence MXene quantum dots via a mechanism integrating electron transfer and inner filter effect
Abstract
Fluorescence quantum dots (QDs) are promising functional nanomaterials in chemical biology and environmental applications, where an analyte-induced responsive system is beneficial for detecting numerous life-related molecules and pollutants.
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Citations
Cites
Metallic Ti3C2T x MXene Gas Sensors with Ultrahigh Signal-to-Noise Ratio
Kim, S. J., Koh, H.-J., Ren, C. E., Kwon, O., Maleski, K., Cho, S.-Y., Anasori, B., Kim, C.-K., Choi, Y.-K., Kim, J., et al. (2018) · ACS Nano · doi:10.1021/acsnano.7b07460 · Cited by 1,699
Cited by
A Review on MXene Synthesis, Stability, and Photocatalytic Applications
Murali, G., Reddy Modigunta, J. K., Park, Y. H., Lee, J.-H., Rawal, J., Lee, S.-Y., In, I., & Park, S.-J. (2022) · ACS Nano · doi:10.1021/acsnano.2c04750 · Cited by 668
Metadata
- Authors
- Zhang, Q., Sun, Y., Liu, M., & Liu, Y.
- Venue
- Nanoscale
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2020
- Volume
- 12
- Issue
- 3
- Pages
- 1826-1832
- ISSN
- 2040-3364 (ISSN-L)
- 2040-3372
- OpenAlex
- W2997083138
- Cited by
- 194
- References
- 1
- FWCI
- 11.56
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Selective detection of Fe3+ ions based on fluorescence MXene quantum dots via a mechanism integrating electron transfer and inner filter effect. https://app.cochat.ai/papers/10.1039/c9nr08794j
- The paper
- Zhang, Q., Sun, Y., Liu, M., & Liu, Y. (2020). Selective detection of Fe3+ ions based on fluorescence MXene quantum dots via a mechanism integrating electron transfer and inner filter effect. Nanoscale. https://doi.org/10.1039/c9nr08794j
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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.
