The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Nano‐Gold as Artificial Enzymes: Hidden Talents
Abstract
Creating artificial enzymes that mimic the complexity and function of natural systems has been a great challenge for the past two decades. In this Progress Report, the focus is on recently discovered “hidden talents” of gold nanomaterials in artificial enzymes, including mimicking of nuclease, esterase, silicatein, glucose oxidase, peroxidase, catalase, and superoxide dismutase. These unexpected enzyme‐like activities can be ascribed to nano‐gold itself or the functional groups present on surrounding monolayer. Along with introducing the mechanisms of the various enzyme‐like activities, the design and development of gold‐based biomimetic catalysts, the search for efficient modulators, and their potential applications in bionics, biosensing, and biomedical sciences are highlighted. Eventually, it is expected that the rapidly growing interest in gold‐based nanozymes will certainly fuel the excitement and stimulate research in this highly active field.
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
Intrinsic peroxidase-like activity of ferromagnetic nanoparticles
Gao, L., Zhuang, J., Nie, L., Zhang, J., Zhang, Y., Gu, N., Wang, T., Feng, J., Yang, D., Perrett, S., et al. (2007) · Nature Nanotechnology · doi:10.1038/nnano.2007.260 · Cited by 7,483
Cited by
Han, L., Li, C., Zhang, T., Lang, Q., & Liu, A. (2015) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.5b03591 · Cited by 280
Wen, D., Liu, W., Haubold, D., Zhu, C., Oschatz, M., Holzschuh, M., Wolf, A., Simon, F., Kaskel, S., & Eychmüller, A. (2016) · ACS Nano · doi:10.1021/acsnano.5b07505 · Cited by 207
Chang, X., Wu, Q., Wu, Y., Xi, X., Cao, J., Chu, H., Liu, Q., Li, Y., Wu, W., Fang, X., et al. (2022) · Nano Letters · doi:10.1021/acs.nanolett.2c03260 · Cited by 109
Robinson, A. P., Zhang, J. Z., Titus, H. E., Karl, M., Merzliakov, M., Dorfman, A. R., Karlik, S., Stewart, M. G., Watt, R. K., Facer, B. D., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-58709-w · Cited by 87
Zhu, F., Liu, Z., Wu, X., Xu, D., Li, Q., Chen, X., Pang, W., Duan, X., & Wang, Y. (2023) · Ultrasonics Sonochemistry · doi:10.1016/j.ultsonch.2023.106618 · Cited by 7
Metadata
- Authors
- Lin, Y., Ren, J., & Qu, X.
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2014-04
- Volume
- 26
- Issue
- 25
- Pages
- 4200-4217
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- OpenAlex
- W1976626594
- Cited by
- 479
- References
- 1
- FWCI
- 11.32
- 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.