The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Adsorption of Heavy Metals–A Review
Abstract
Abstract Many researchers have used coal fly ash; rice husk ash, nano material and conducting polymer- as adsorbents to remove water pollutants including Cr, Pb, Hg, Zn, Mn and Cu, heavy metal. The main objective in this study to identify the nano materials used for heavy metal adsorption process effectively. The different parameters, pH, contact time etc. which affect the adsorption process. By reviewing this paper to find out the scope of conducting polymer based nanocomposite for heavy metal removal in aqueous system.
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
Low-cost adsorbents for heavy metals uptake from contaminated water: a review
Babel, S. (2003) · Journal of Hazardous Materials · doi:10.1016/s0304-3894(02)00263-7 · Cited by 3,444
Cited by
Burakov, A. E., Galunin, E. V., Burakova, I. V., Kucherova, A. E., Agarwal, S., Tkachev, A. G., & Gupta, V. K. (2018) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2017.11.034 · Cited by 1,612
Application of Biosorption for Removal of Heavy Metals from Wastewater
Kanamarlapudi, S. L. R. K., Chintalpudi, V. K., & Muddada, S. (2018) · Biosorption · doi:10.5772/intechopen.77315 · Cited by 351
Toxicity of heavy metals in plants and animals and their uptake by magnetic iron oxide nanoparticles
Rehman, A. U., Nazir, S., Irshad, R., Tahir, K., ur Rehman, K., Islam, R. U., & Wahab, Z. (2021) · Journal of Molecular Liquids · doi:10.1016/j.molliq.2020.114455 · Cited by 322
An overview of chromium removal techniques from tannery effluent
Nur-E-Alam, M., Mia, M. A. S., Ahmad, F., & Rahman, M. M. (2020) · Applied Water Science · doi:10.1007/s13201-020-01286-0 · Cited by 246
Ugwu, E. I., Othmani, A., & Nnaji, C. C. (2022) · International Journal of Environmental Science and Technology · doi:10.1007/s13762-021-03560-3 · Cited by 105
Metadata
- Authors
- Arora, R.
- Venue
- Materials Today: Proceedings
- Publisher
- Elsevier BV
- Published
- 2019
- Volume
- 18
- Pages
- 4745-4750
- ISSN
- 2214-7853 (ISSN-L)
- OpenAlex
- W2990522298
- Cited by
- 519
- References
- 1
- FWCI
- 22.89
- 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: Adsorption of Heavy Metals–A Review. https://app.cochat.ai/papers/10.1016/j.matpr.2019.07.462
- The paper
- Arora, R. (2019). Adsorption of Heavy Metals–A Review. Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2019.07.462
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.
