Optimizing cadmium ion adsorption: predictive modeling based on literature data
| dc.citation.epage | 635 | |
| dc.citation.rank | M33 | |
| dc.citation.spage | 632 | |
| dc.contributor.author | Nujkić, Maja | |
| dc.contributor.author | Tasić, Žaklina | |
| dc.contributor.author | Stanković, Sonja | |
| dc.contributor.author | Medić, Dragana | |
| dc.date.accessioned | 2025-12-08T08:57:18Z | |
| dc.date.available | 2025-12-08T08:57:18Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | The contamination of water with various heavy metal ions is a global problem and a challenge for research. Heavy metals in concentrations that exceed the permissible limits lead to considerable health problems. Accordingly, researchers are constantly working to find the most suitable technique for their removal. Among the conventional methods, adsorption stands out, in which various natural materials can be used to remove heavy metal ions, including cadmium ions. In this paper, a literature review is given on various natural materials that can be successfully used as biosorbents and optimization has been carried out to obtain optimal conditions for the removal of cadmium ions. | |
| dc.identifier.doi | 10.5937/IOC25632N | |
| dc.identifier.isbn | 978-86-6305-164-5 | |
| dc.identifier.uri | https://ioc.tfbor.bg.ac.rs/public/2025/Proceedings_IOC_2025.pdf | |
| dc.identifier.uri | https://repozitorijum.tfbor.bg.ac.rs/handle/123456789/6036 | |
| dc.language.iso | en | |
| dc.publisher | University of Belgrade - Technical Faculty in Bor | |
| dc.rights.license | CC-BY-NC-ND | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.source | Proceedings [Elektronski izvor] - 56th International October Conference on Mining and Metallurgy - IOC 2025, 22-25 October, 2025, Bor Lake, Serbia | |
| dc.subject | natural materials | |
| dc.subject | wastewaters | |
| dc.subject | Cd2+ ions | |
| dc.subject | biosorption | |
| dc.subject | response surface method | |
| dc.title | Optimizing cadmium ion adsorption: predictive modeling based on literature data | |
| dc.type | conferenceObject | |
| dc.type.version | publishedVersion |
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