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Optimized graphene oxide foam with enhanced performance and high selectivity for mercury removal from water
CESAM & Department of Chemistry, University of Aveiro.
TEMA-NRD, Mechanical Engineering Department, University of Aveiro, University of Aveiro, Nanotechnology Research Division, University of Aveiro.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0001-8676-8819
CESAM & Department of Chemistry, University of Aveiro.
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2016 (English)In: Journal of Hazardous Materials, ISSN 0304-3894, E-ISSN 1873-3336, Vol. 301, p. 453-461Article in journal (Refereed) Published
Abstract [en]

This work explores the preparation of three-dimensional graphene oxide macroscopic structures, shaped by self-assembling single graphene oxide (3DGO) sheets with control of its surface chemistry by combining with nitrogen functional groups (3DGON), or with nitrogen and sulphur functional groups (3DGOSN), and their application in the removal of mercury (Hg(II)) from aqueous solutions. The chemical structure of the materials was assessed by using different characterization techniques: SEM, XPS and BET. Adsorption studies conducted in Hg(II) contaminated ultra-pure water reveal the enhanced ability of 3DGON for the adsorption of this metal, when compared to the other GO foams. A small dose of 3DGON (10 mg L−1) allows to remove up to 96% of Hg(II) after 24 h of contact time, leading to a residual concentration in solution close to the guideline value for drinking water (1 μg L−1). The ability of this material to adsorb Hg (II) was evaluated relatively to different experimental parameters such as pH, sorbent dose, time and effect on different competing metal ions. Real application was also evaluated by testing its performance in two different natural matrices, river and sea water, with very promising results.

Place, publisher, year, edition, pages
2016. Vol. 301, p. 453-461
National Category
Tribology (Interacting Surfaces including Friction, Lubrication and Wear)
Research subject
Machine Elements
Identifiers
URN: urn:nbn:se:ltu:diva-11011DOI: 10.1016/j.jhazmat.2015.09.028ISI: 000367407200049PubMedID: 26410274Scopus ID: 2-s2.0-84942546511Local ID: 9e7b4772-9b79-4eb4-b7b3-83d336151ec5OAI: oai:DiVA.org:ltu-11011DiVA, id: diva2:983960
Note
Validerad; 2016; Nivå 2; 20150916 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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Emami, Nazanin

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