The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.
Chitosan functionalized iron nanosheet for enhanced removal of As(III) and Sb(III): Synergistic effect and mechanism
Open accessAbstract
Abstract Neutral trivalent arsenic (As(III)) and antimony (Sb(III)) species are more toxic and harder to remove from wastewater environment than their pentavalent counterparts. Herein, a natural polysaccharide chitosan (CS) functionalized iron nanosheet using an in-situ doping method was designed, aiming to attract As(III) and Sb(III) from aqueous solution. The surface area of the optimum sample was 111.8 cm2/g, a good dispersion of the iron nanocomposite was observed by the TEM and element mapping characterization. In the batch adsorption experiment the factors of doping contents of CS and solution properties (pH, co-existing anions and humic acid) were studied systematically. The result showed that 0.5 wt% CS functionalized iron nanosheet had higher removal capacity, affinity, selectivity and reusability for Sb(III) than As(III). The optimum adsorption were achieved at the adsorbent dosage of 0.4 g/L at a wide pH values, and the maximum adsorption capacity were 108.6 and 138.8 mg/g for As(III) and Sb(III) calculated from Langmuir non-linear fitting, respectively. Both As(III) and Sb(III) removal were independent on pH values, indicating electrostatic attraction was not the dominate removal mechanism. The detailed removal mechanism was confirmed by a synergetic interaction of As-Fe/Sb-Fe complexes and hydrogen bonding using the combined characterization of FTIR and XPS spectra. This study demonstrated that the CS functionalized iron nanosheet with the properties of environmental friendly, low-cost and facile preparation could have potential applications in water purification.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“| Sb 3+ | Chitosan functionalized iron | 138.8 | 50 |”
From Removal of heavy metal ions from wastewater: a comprehensive and critical review (2021) · cites this paper as [50]
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
1 retracted
Awual, M. R., Alharthi, N. H., Okamoto, Y., Karim, M. R., Halim, M. E., Hasan, M. M., Rahman, M. M., Islam, M. M., Khaleque, M. A., & Sheikh, M. C. (2017) · Chemical Engineering Journal · doi:10.1016/j.cej.2017.03.075 · Cited by 352
RetractedSustainable technologies for water purification from heavy metals: review and analysis
Bolisetty, S., Peydayesh, M., & Mezzenga, R. (2019) · Chemical Society Reviews · doi:10.1039/c8cs00493e · Cited by 1,504
Environmental remediation of heavy metal ions by novel-nanomaterials: A review
Wu, Y., Pang, H., Liu, Y., Wang, X., Yu, S., Fu, D., Chen, J., & Wang, X. (2019) · Environmental Pollution · doi:10.1016/j.envpol.2018.12.076 · Cited by 692
He, M., Wang, X., Wu, F., & Fu, Z. (2012) · Science of The Total Environment · doi:10.1016/j.scitotenv.2011.06.009 · Cited by 632
A critical review on arsenic removal from water using iron-based adsorbents
Hao, L., Liu, M., Wang, N., & Li, G. (2018) · RSC Advances · doi:10.1039/c8ra08512a · Cited by 487
Olivera, S., Muralidhara, H. B., Venkatesh, K., Guna, V. K., Gopalakrishna, K., & Kumar K., Y. (2016) · Carbohydrate Polymers · doi:10.1016/j.carbpol.2016.08.017 · Cited by 447
Assessing of lead(III) capturing from contaminated wastewater using ligand doped conjugate adsorbent
Awual, M. R. (2016) · Chemical Engineering Journal · doi:10.1016/j.cej.2015.12.078 · Cited by 437
Advances in Surface Passivation of Nanoscale Zerovalent Iron: A Critical Review
Bae, S., Collins, R. N., Waite, T. D., & Hanna, K. (2018) · Environmental Science & Technology · doi:10.1021/acs.est.8b01734 · Cited by 435
Heavy metal removal using nanoscale zero-valent iron (nZVI): Theory and application
Li, S., Wang, W., Liang, F., & Zhang, W.-X. (2017) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2016.01.032 · Cited by 431
Awual, M. R., Yaita, T., Taguchi, T., Shiwaku, H., Suzuki, S., & Okamoto, Y. (2014) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2014.06.011 · Cited by 376
Cited by
Removal of heavy metal ions from wastewater: a comprehensive and critical review
Qasem, N. A. A., Mohammed, R. H., & Lawal, D. U. (2021) · npj Clean Water · doi:10.1038/s41545-021-00127-0 · Cited by 2,225
Ayub, A., Raza, Z. A., Majeed, M. I., Tariq, M. R., & Irfan, A. (2020) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2020.06.287 · Cited by 266
Abidli, A., Huang, Y., Ben Rejeb, Z., Zaoui, A., & Park, C. B. (2022) · Chemosphere · doi:10.1016/j.chemosphere.2021.133102 · Cited by 194
Nishad, P. A., & Bhaskarapillai, A. (2021) · Chemosphere · doi:10.1016/j.chemosphere.2021.130252 · Cited by 168
Cai, L., Ying, D., Liang, X., Zhu, M., Lin, X., Xu, Q., Cai, Z., Xu, X., & Zhang, L. (2021) · Chemical Engineering Journal · doi:10.1016/j.cej.2021.128404 · Cited by 136
Metadata
- Authors
- Zeng, J., Qi, P., Shi, J., Pichler, T., Wang, F., Wang, Y., & Sui, K.
- Affiliations
- Qingdao University (CN)
- Yantai University (CN)
- University of Bremen (DE)
- Corresponding author
- Qi, Pengfei
- Sui, Kunyan
- Venue
- Chemical Engineering Journal
- Publisher
- Elsevier BV
- Published
- 2020-02
- Volume
- 382
- Pages
- 122999
- ISSN
- 1385-8947 (ISSN-L)
- OpenAlex
- W2978114545
- Cited by
- 107
- References
- 65
- Citations by year
- 2026: 6 · 2025: 14 · 2024: 12 · 2023: 17 · 2022: 21 · 2021: 28 · 2020: 9
- FWCI
- 6.32
- Type
- journal article
- Language
- en
- Open access
- Licence
- cc-by-nc-nd
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- Locations
- Chemical Engineering Journal (publishedVersion)
- Media (https://www.suub.uni-bremen.de/) (submittedVersion, cc-by-nc-nd)
- Staats- und Universitätsbibliothek Bremen
- Funders
- Natural Science Foundation of Shandong Province
- Topics
- Physical Sciences › Environmental Science › Environmental Chemistry › Arsenic contamination and mitigation
- Physical Sciences › Environmental Science › Water Science and Technology › Adsorption and biosorption for pollutant removal
- Physical Sciences › Environmental Science › Environmental Engineering › Environmental remediation with nanomaterials
- Keywords
- chitosan, arsenic(III) removal, antimony(III) removal, adsorption, in situ doping, polysaccharide functionalization, hydrogen bonding, adsorption mechanism, heavy metal removal from water, adsorbent reusability, pH effect, humic acid
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.