The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Application of Superhydrophobic Surface with High Adhesive Force in No Lost Transport of Superparamagnetic Microdroplet
Abstract
Due to the wide applications of magnetic nanomaterials in biology, pharmacy, and diagnostics, there is an increasing need for controlled transport of their small volumes of liquids. Here, we designed a simple, high-efficiency, and flexible method for reversibly oriented transport of superparamagnetic microdroplets with no lost volume by alternating magnetic fields. Superhydrophobic surfaces with high adhesive force played an important role, and the success of reversibly no lost transport also relied on the sensitive responsive property of the superparamagnetic microdroplet to applied magnetic fields. Such a magnetic-field-induced intelligent transport method would be especially helpful for many localized chemical or biological reactions, traced analysis, and in situ detection.
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
Perez, J. M., O'Loughin, T., Simeone, F. J., Weissleder, R., & Josephson, L. (2002) · Journal of the American Chemical Society · doi:10.1021/ja017773n · Cited by 355
Cited by
Superhydrophobic surfaces: from structural control to functional application
Zhang, X., Shi, F., Niu, J., Jiang, Y., & Wang, Z. (2008) · J. Mater. Chem. · doi:10.1039/b711226b · Cited by 1,768
Bioinspired Surfaces with Superwettability: New Insight on Theory, Design, and Applications
Wang, S., Liu, K., Yao, X., & Jiang, L. (2015) · Chemical Reviews · doi:10.1021/cr400083y · Cited by 1,646
Self-citationDefinition of Superhydrophobic States
Wang, S., & Jiang, L. (2007) · Advanced Materials · doi:10.1002/adma.200700934 · Cited by 969
Self-citationBio‐Inspired, Smart, Multiscale Interfacial Materials
Xia, F., & Jiang, L. (2008) · Advanced Materials · doi:10.1002/adma.200800836 · Cited by 963
Self-citationFabrication of Superhydrophobic Surfaces with High and Low Adhesion Inspired from Rose Petal
Bhushan, B., & Her, E. K. (2010) · Langmuir · doi:10.1021/la904585j · Cited by 507
Metadata
- Authors
- Hong, X., Gao, X., & Jiang, L.
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2007-01-23
- Volume
- 129
- Issue
- 6
- Pages
- 1478-1479
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W2038452534
- Cited by
- 442
- References
- 1
- FWCI
- 13.19
- Type
- journal article
- Language
- en
- Open access
- closed
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.
