Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 325

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Selective Degradation of Electron-Rich Organic Pollutants Induced by CuO@Biochar: The Key Role of Outer-Sphere Interaction and Singlet Oxygen

Zhao, Yan, Yu, Lei, Song, Chengye, Chen, Zhiliang, Meng, Fanyue, Song, Min·2022·Environmental Science & Technology

Abstract

Efficient degradation of organic pollutants by oxidative radicals is challenging in the complex soil environment because of the invalid consumption of radicals by nontarget background substances and the generation of secondary halogenated organic pollutants. Nonradical-based oxidation is a promising pollutant removal method due to its high selectivity and environmental adaptability. Herein, a biochar-supported sheetlike CuO (e-CuO@BC) was developed, which exhibited efficient activation of peroxydisulfate (PDS) via nonradical pathways. The activation mechanisms were identified as (i) formation of surface-bonding active complexes via an outer-sphere interaction between e-CuO@BC and PDS and (ii) the continuous generation of 1 O 2 by the cycling of the Cu(I)/Cu(II) redox couple. In addition, the activation of PDS primarily occurred at the crystal facet (001) of e-CuO occupied by Cu atoms and was well facilitated by the Cu–O–C bond, which induced electron-rich centers around CuO. Two oxidative species from PDS activation, including surface-bonding active complexes and 1 O 2, showed a highly selective degradation toward electron-rich pollutants. Moreover, a highly efficient mineralization of organic pollutants and an effective inhibition on the generation of toxic byproducts (i.e., halogenated organics) was indicated by the intermediate and final degradation products. This study provides a comprehensive understanding of the heterogeneous activation process of PS by the e-CuO@BC catalyst for electron-rich organic pollutant removal.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/acs.est.2c01759

Cites

49 of 49 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Cited by

See all 325

Metadata

Authors
Zhao, Y., Yu, L., Song, C., Chen, Z., Meng, F., & Song, M.
Venue
Environmental Science & Technology
Published
2022-05-12
Volume
56
Issue
15
Pages
10710-10720
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W4280582179
Cited by
325
References
49
FWCI
17.83
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.