The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Biosorption of Heavy Metals
Open accessAbstract
Industrialization has led to introduction of heavy metals in the environment. Heavy metals are known to persist in the environment and become a risk for organisms. Micro-organisms are present in industrial effluents. They have adopted different strategies to cope up with the harmful effects of these metals. These strategies can be metabolism dependent or independent. One such strategy is biosorption which is binding of metal ions with metal binding proteins present on the cell wall. Biosorption is exhibited by bacteria, algae, fungi and yeasts. Not only living organisms, but also residuals of dead bodies of microorganisms shows biosorbent properties like agricultural wastes including husk, seeds, peels and stalks of different crops. Different factors affect the rate of biosorption which includes temperature, pH, nature of biosorbents, surface area to volume ratio, concentration of biomass, initial metal ion concentration and metal affinity to biosorbent. Various models including Freundlich model and Langmuir model can be used to describe biosorption. Recovery of biosorbed metals can be done using agents like thiosulfate, mineral acids and organic acids. Choice of desorption agent should be carefully selected to prevent alteration of physical properties of a biosorbent.
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
Gadd, G. M. (2009) · Journal of Chemical Technology & Biotechnology · doi:10.1002/jctb.1999 · Cited by 1,287
Cited by
Metals, minerals and microbes: geomicrobiology and bioremediation
Gadd, G. M. (2010) · Microbiology · doi:10.1099/mic.0.037143-0 · Cited by 2,013
Microbial and plant derived biomass for removal of heavy metals from wastewater
Ahluwalia, S. S., & Goyal, D. (2007) · Bioresource Technology · doi:10.1016/j.biortech.2005.12.006 · Cited by 1,586
Gadd, G. M. (2009) · Journal of Chemical Technology & Biotechnology · doi:10.1002/jctb.1999 · Cited by 1,287
Chai, W. S., Cheun, J. Y., Kumar, P. S., Mubashir, M., Majeed, Z., Banat, F., Ho, S.-H., & Show, P. L. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2021.126589 · Cited by 1,275
Toxic and genotoxic effects of hexavalent chromium in environment and its bioremediation strategies
Mishra, S., & Bharagava, R. N. (2016) · Journal of Environmental Science and Health, Part C · doi:10.1080/10590501.2015.1096883 · Cited by 513
Metadata
- Authors
- Shamim, S.
- Venue
- Biosorption
- Publisher
- InTech
- Published
- 2018-07-18
- OpenAlex
- W2884220380
- Cited by
- 538
- References
- 1
- FWCI
- 46.18
- Type
- book chapter
- Language
- en
- Open access
- hybrid
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.