The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Direct Electron-Transfer-Based Peroxymonosulfate Activation by Iron-Doped Manganese Oxide (δ-MnO2) and the Development of Galvanic Oxidation Processes (GOPs)
Abstract
Manganese oxides have been recently investigated as excellent catalysts for peroxymonosulfate (PMS) activation, and the reported mechanisms are mostly forming reactive oxygen species (ROSs). This study investigated the use of iron-doped manganese oxide, synthesized via air oxidation under strong alkaline conditions. The oxidation of three substrates was affected by their adsorption at the catalyst surface, solution pH, and co-solutes. Common ROS scavengers inhibited the oxidation of bisphenol A (BPA), suggesting the possible involvement of ROSs; however, the PMS decomposition tests with and without BPA and the comparison with a 1 O 2 -generation system ruled out the formation of ROSs and pointed to direct electron transfer between the adsorbed BPA and complexed PMS as the mechanism. To prove this mechanism, the catalyst was coated to graphite sheets and a galvanic oxidation process (GOP) was developed to separate BPA and PMS into two half cells. Upon PMS addition into one cell, BPA was quickly oxidized in the other cell, confirming the occurrence of electron transfer. The GOP system successfully degraded BPA in both surface water and hypersaline shale gas-produced water. Overall, this study developed a new catalyst for PMS activation and unveiled the advantages and potential applications of electron shuttling catalysts.
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
Buxton, G. V., Greenstock, C. L., Helman, W. P., & Ross, A. B. (1988) · Journal of Physical and Chemical Reference Data · doi:10.1063/1.555805 · Cited by 12,332
Yun, E.-T., Lee, J. H., Kim, J., Park, H.-D., & Lee, J. (2018) · Environmental Science & Technology · doi:10.1021/acs.est.8b00959 · Cited by 1,175
Zhang, T., Chen, Y., Wang, Y., Le Roux, J., Yang, Y., & Croué, J.-P. (2014) · Environmental Science & Technology · doi:10.1021/es501218f · Cited by 798
Activation of Persulfates by Graphitized Nanodiamonds for Removal of Organic Compounds
Lee, H., Kim, H.-I., Weon, S., Choi, W., Hwang, Y. S., Seo, J., Lee, C., & Kim, J.-H. (2016) · Environmental Science & Technology · doi:10.1021/acs.est.6b02079 · Cited by 688
Cited by
Reactive Species in Advanced Oxidation Processes: Formation, Identification and Reaction Mechanism
Wang, J., & Wang, S. (2020) · Chemical Engineering Journal · doi:10.1016/j.cej.2020.126158 · Cited by 1,585
Origins of Electron-Transfer Regime in Persulfate-Based Nonradical Oxidation Processes
Ren, W., Cheng, C., Shao, P., Luo, X., Zhang, H., Wang, S., & Duan, X. (2022) · Environmental Science & Technology · doi:10.1021/acs.est.1c05374 · Cited by 1,306
Self-citationDing, Y., Wang, X., Fu, L., Peng, X., Pan, C., Mao, Q., Wang, C., & Yan, J. (2021) · Science of The Total Environment · doi:10.1016/j.scitotenv.2020.142794 · Cited by 537
Chen, F., Liu, L.-L., Chen, J.-J., Li, W.-W., Chen, Y.-P., Zhang, Y.-J., Wu, J.-H., Mei, S.-C., Yang, Q., & Yu, H.-Q. (2021) · Water Research · doi:10.1016/j.watres.2020.116799 · Cited by 482
Identification of Fenton-like active Cu sites by heteroatom modulation of electronic density
Zhou, X., Ke, M.-K., Huang, G.-X., Chen, C., Chen, W., Liang, K., Qu, Y., Yang, J., Wang, Y., Li, F., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2119492119 · Cited by 451
Metadata
- Authors
- Huang, K. Z., & Zhang, H.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-10-11
- Volume
- 53
- Issue
- 21
- Pages
- 12610-12620
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W2979385474
- Cited by
- 413
- References
- 4
- FWCI
- 11.36
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Direct Electron-Transfer-Based Peroxymonosulfate Activation by Iron-Doped Manganese Oxide (δ-MnO2) and the Development of Galvanic Oxidation Processes (GOPs). https://app.cochat.ai/papers/10.1021/acs.est.9b03648
- The paper
- Huang, K. Z., & Zhang, H. (2019). Direct Electron-Transfer-Based Peroxymonosulfate Activation by Iron-Doped Manganese Oxide (δ-MnO2) and the Development of Galvanic Oxidation Processes (GOPs). Environmental Science & Technology. https://doi.org/10.1021/acs.est.9b03648
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.
