The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Magneto-fluorescent core-shell supernanoparticles
Open accessAbstract
Magneto-fluorescent particles have been recognized as an emerging class of materials that exhibit great potential in advanced applications. However, synthesizing such magneto-fluorescent nanomaterials that simultaneously exhibit uniform and tunable sizes, high magnetic content loading, maximized fluorophore coverage at the surface and a versatile surface functionality has proven challenging. Here we report a simple approach for co-assembling magnetic nanoparticles with fluorescent quantum dots to form colloidal magneto-fluorescent supernanoparticles. Importantly, these supernanoparticles exhibit a superstructure consisting of a close-packed magnetic nanoparticle ‘core’, which is fully surrounded by a ‘shell’ of fluorescent quantum dots. A thin layer of silica coating provides high colloidal stability and biocompatibility, and a versatile surface functionality. We demonstrate that after surface pegylation, these silica-coated magneto-fluorescent supernanoparticles can be magnetically manipulated inside living cells while being optically tracked. Moreover, our silica-coated magneto-fluorescent supernanoparticles can also serve as an in vivo multi-photon and magnetic resonance dual-modal imaging probe. Magneto-fluorescent nanoparticles hold promise for bioimaging applications, but synthesizing uniform particles with tunable sizes remains challenging. Chen et al. propose an approach for co-assembling magnetic particles with fluorescent quantum dots, leading to well-defined core-shell structures.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Ultra-large-scale syntheses of monodisperse nanocrystals
Park, J., An, K., Hwang, Y., Park, J.-G., Noh, H.-J., Kim, J.-Y., Park, J.-H., Hwang, N.-M., & Hyeon, T. (2004) · Nature Materials · doi:10.1038/nmat1251 · Cited by 4,076
Cited by
Supraparticles: Functionality from Uniform Structural Motifs
Wintzheimer, S., Granath, T., Oppmann, M., Kister, T., Thai, T., Kraus, T., Vogel, N., & Mandel, K. (2018) · ACS Nano · doi:10.1021/acsnano.8b00873 · Cited by 253
Metadata
- Authors
- Chen, O., Riedemann, L., Etoc, F., Herrmann, H., Coppey, M., Barch, M., Farrar, C. T., Zhao, J., Bruns, O. T., Wei, H., Guo, P., Cui, J., Jensen, R., Chen, Y., Harris, D. K., Cordero, J. M., Wang, Z., Jasanoff, A., Fukumura, D., Reimer, R., Dahan, M., Jain, R. K., & Bawendi, M. G.
- Venue
- Nature Communications
- Published
- 2014-10-09
- Volume
- 5
- Issue
- 1
- Pages
- 5093-5093
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W2049385711
- Cited by
- 287
- References
- 1
- FWCI
- 11.76
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
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.