Samuel E. Baltazar
Co-authors: Javier Rojas-Nunez, P. Sepulveda, Rafael Freire
Universidad de Santiago de Chile
Towards the efficient adsorption of water contaminants with nanoparticles
The presence of metalloids and heavy metals in aqueous sources is a major concern in many countries. Several pollutants such methylated arsenicals and metals are already associated with different human health issues and diseases, demanding new alternatives to purify water resources. Some of these alternatives involve the use of nanoparticles due to their affinity with metals and metalloids species. In this context, shape, size, concentration and distribution of nanoparticles are very important features to consider, due to the physico-chemical properties at their surface, playing an important role in the different sorption mechanisms.
We study the interaction of metals and arsenic complexes in contact with iron-based nanoparticles at the atomic scale from first principle calculations. Additionally, the interplay between metallic elements is claimed to limit the oxidation of iron, establishing an electron transfer between both metals. This aspect was considered for FeCu particles using molecular dynamics simulations combined with an annealing process, allowing to study the concentration effect on the morphology of nanoparticles up to nanoscale size. From the considered contaminant species, higher adsorption energy was found for the complexation of Fe3O4(001) with As(III) being 1.3 eV higher than the adsorption energy for As(V) 1. In the case of As(III), a large partial band charge density was found, which was associated to the O-Fe bond formation, while more delocalized electron density was found in the adsorption of As(V) subspecies, with the formation of two Fe-O bonds. As(V) is mainly adsorbed on the surface with a double O-Fe bond formation in the most stable configuration. Finally, we envisage the sorption capacity of other iron oxide surfaces as well as other pollutant compounds.
1 Baltazar, S. E., Romero, A. H., & Salgado, M. (2017). Computational Materials Science, 127, 110-120.
We acknowledge the financial support of DICYT 041931BR project and "Fondo basal para centros cientficos y tecnolgicos" FB0807. J. Rojas-Nunez acknowledges the financial support of the CONICYT's "doctorado nacional" scholarship PCHA-21150699 and USA1799 Vridei 041931SB_GO Universidad de Santiago de Chile.