Recovery of platinum group elements (PGEs) from wastewater : a case for the development of predictive adsorption numerical methods

dc.contributor.authorMosai, Alseno Kagiso
dc.contributor.authorJohnson, Raymond H.
dc.contributor.authorTutu, Hlanganani
dc.contributor.emailalseno.mosai@up.ac.zaen_US
dc.date.accessioned2024-09-09T10:55:07Z
dc.date.issued2024-10
dc.descriptionDATA AVAILABILITY : No data was used for the research described in the article.en_US
dc.description.abstractPlatinum group elements (PGEs) are very important for the modern world, and they are used in many applications due to their physical and chemical properties that cannot be found in other naturally occurring elements. This means that the availability of PGEs now and in the future is very crucial. However, research has indicated that PGEs are at the edge of becoming scarce due to gradually depleting natural resources. This review reports on the recent techniques for the recovery of PGEs from secondary sources. However, there is still a need for cheap and efficient methods and technologies that can be applied at large scale. The need for PGEs speciation information especially in adsorption and/or recovery studies is discussed. Speciation modelling codes (PHREEQC, Geochemist’s workbench, MINEQL+, MINTEQA2 and WHAM) which can be used for this purpose are also discussed. These models can be used for adequate predictive adsorption of PGEs in order to determine the performance of the adsorbents beyond the available laboratory, pilot or real application data. However, most of the PGEs are not included in the available databases used in the numerical models hence, new databases should be developed, or the modification of the available databases will always be a requirement in order to simulate PGEs accurately and successfully, under various conditions. To automate the calibration of the models including calibration-constrained uncertainty analysis of the models, parameter estimation (PEST) software which can estimate important parameters and compute sensitivities of model outputs to parameters, can be coupled with the modelling codes.en_US
dc.description.departmentChemistryen_US
dc.description.embargo2025-08-21
dc.description.librarianhj2024en_US
dc.description.sdgSDG-06:Clean water and sanitationen_US
dc.description.sponsorshipThe University of Pretoria and the National Research Foundation (NRF) of South Africa.en_US
dc.description.urihttps://www.elsevier.com/locate/minengen_US
dc.identifier.citationMosai, A.K., Johnson, R.H. & Tutu, H. 2024, 'Recovery of platinum group elements (PGEs) from wastewater: a case for the development of predictive adsorption numerical methods', Minerals Engineering, vol. 217, art. 108915, pp. 1-18, doi : 10.1016/j.mineng.2024.108915.en_US
dc.identifier.issn0892-6875 (print)
dc.identifier.issn1872-9444 (online)
dc.identifier.other10.1016/j.mineng.2024.108915
dc.identifier.urihttp://hdl.handle.net/2263/98083
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Notice : this is the author’s version of a work that was accepted for publication in Minerals Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Minerals Engineering, vol. 217, art. 108915, pp. 1-18, 2024, doi : 10.1016/j.mineng.2024.108915.en_US
dc.subjectPlatinum group elements (PGEs)en_US
dc.subjectRecoveryen_US
dc.subjectPredictive adsorptionen_US
dc.subjectNumerical modellingen_US
dc.subjectSpeciation modellingen_US
dc.subjectWastewateren_US
dc.subjectSDG-06: Clean water and sanitationen_US
dc.titleRecovery of platinum group elements (PGEs) from wastewater : a case for the development of predictive adsorption numerical methodsen_US
dc.typePostprint Articleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Mosai_Recovery_2024.pdf
Size:
869.23 KB
Format:
Adobe Portable Document Format
Description:
Postprint Article

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: