The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Postsynthetically Modified Covalent Organic Frameworks for Efficient and Effective Mercury Removal
Abstract
A key challenge in environmental remediation is the design of adsorbents bearing an abundance of accessible chelating sites with high affinity, to achieve both rapid uptake and high capacity for the contaminants. Herein, we demonstrate how two-dimensional covalent organic frameworks (COFs) with well-defined mesopore structures display the right combination of properties to serve as a scaffold for decorating coordination sites to create ideal adsorbents. The proof-of-concept design is illustrated by modifying sulfur derivatives on a newly designed vinyl-functionalized mesoporous COF (COF-V) via thiol–ene “click” reaction. Representatively, the material (COF-S-SH) synthesized by treating COF-V with 1,2-ethanedithiol exhibits high efficiency in removing mercury from aqueous solutions and the air, affording Hg 2+ and Hg 0 capacities of 1350 and 863 mg g –1, respectively, surpassing all those of thiol and thioether functionalized materials reported thus far. More significantly, COF-S-SH demonstrates an ultrahigh distribution coefficient value ( K d ) of 2.3 × 10 9 mL g –1, which allows it to rapidly reduce the Hg 2+ concentration from 5 ppm to less than 0.1 ppb, well below the acceptable limit in drinking water (2 ppb). We attribute the impressive performance to the synergistic effects arising from densely populated chelating groups with a strong binding ability within ordered mesopores that allow rapid diffusion of mercury species throughout the material. X-ray absorption fine structure (XAFS) spectroscopic studies revealed that each Hg is bound exclusively by two S via intramolecular cooperativity in COF-S-SH, further interpreting its excellent affinity. The results presented here thus reveal the exceptional potential of COFs for high-performance environmental remediation.
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
Pearson, R. G. (1963) · Journal of the American Chemical Society · doi:10.1021/ja00905a001 · Cited by 10,475
Remediation technologies for metal-contaminated soils and groundwater: An evaluation
Mulligan, C. N., Yong, R. N., & Gibbs, B. F. (2001) · Engineering Geology · doi:10.1016/s0013-7952(00)00101-0 · Cited by 1,521
Nano‐Composites for Water Remediation: A Review
Tesh, S. J., & Scott, T. B. (2014) · Advanced Materials · doi:10.1002/adma.201401376 · Cited by 252
Cited by
Liu, R., Tan, K. T., Gong, Y., Chen, Y., Li, Z., Xie, S., He, T., Lu, Z., Yang, H., & Jiang, D. (2021) · Chemical Society Reviews · doi:10.1039/d0cs00620c · Cited by 1,083
A versatile MOF-based trap for heavy metal ion capture and dispersion
Peng, Y., Huang, H., Zhang, Y., Kang, C., Chen, S., Song, L., Liu, D., & Zhong, C. (2018) · Nature Communications · doi:10.1038/s41467-017-02600-2 · Cited by 804
Wang, H., Zeng, Z., Xu, P., Li, L., Zeng, G., Xiao, R., Tang, Z., Huang, D., Tang, L., Lai, C., et al. (2019) · Chemical Society Reviews · doi:10.1039/c8cs00376a · Cited by 804
Sun, Q., Aguila, B., Earl, L. D., Abney, C. W., Wojtas, L., Thallapally, P. K., & Ma, S. (2018) · Advanced Materials · doi:10.1002/adma.201705479 · Cited by 641
Self-citationPorous Polymers as Multifunctional Material Platforms toward Task‐Specific Applications
Wu, J., Xu, F., Li, S., Ma, P., Zhang, X., Liu, Q., Fu, R., & Wu, D. (2019) · Advanced Materials · doi:10.1002/adma.201802922 · Cited by 555
Metadata
- Authors
- Sun, Q., Aguila, B., Perman, J., Earl, L. D., Abney, C. W., Cheng, Y., Wei, H., Nguyen, N., Wojtas, L., & Ma, S.
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-02-13
- Volume
- 139
- Issue
- 7
- Pages
- 2786-2793
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W2588812077
- Cited by
- 1,056
- References
- 3
- FWCI
- 43.92
- 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: Postsynthetically Modified Covalent Organic Frameworks for Efficient and Effective Mercury Removal. https://app.cochat.ai/papers/10.1021/jacs.6b12885
- The paper
- Sun, Q., Aguila, B., Perman, J., Earl, L. D., Abney, C. W., Cheng, Y., Wei, H., Nguyen, N., Wojtas, L., & Ma, S. (2017). Postsynthetically Modified Covalent Organic Frameworks for Efficient and Effective Mercury Removal. Journal of the American Chemical Society. https://doi.org/10.1021/jacs.6b12885
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.