Concurrent aggregation and transport of graphene oxide in saturated porous media: Roles of temperature, cation type, and electrolyte concentration

Concurrent aggregation and transport of graphene oxide in saturated porous media: Roles of... Simultaneous aggregation and retention of nanoparticles can occur during their transport in porous media. In this work, the concurrent aggregation and transport of GO in saturated porous media were investigated under the conditions of different combinations of temperature, cation type (valence), and electrolyte concentration. Increasing temperature (6–24 °C) at a relatively high electrolyte concentration (i.e., 50 mM for Na+, 1 mM for Ca2+, 1.75 mM for Mg2+, and 0.03 and 0.05 mM for Al3+) resulted in enhanced GO retention in the porous media. For instance, when the temperature increased from 6 to 24 °C, GO recovery rate decreased from 31.08% to 6.53% for 0.03 mM Al3+ and from 27.11% to 0 for 0.05 mM Al3+. At the same temperature, increasing cation valence and electrolyte concentration also promoted GO retention. Although GO aggregation occurred in the electrolytes during the transport, the deposition mechanisms of GO retention in the media depended on cation type (valence). For 50 mM Na+, surface deposition via secondary minima was the dominant GO retention mechanism. For multivalent cation electrolytes, GO aggregation was rapid and thus other mechanisms such as physical straining and sedimentation also played important roles in controlling GO retention in the media. After passing through the columns, the GO particles in the effluents showed better stability with lower initial aggregation rates. This was probably because less stable GO particles with lower surface charge densities in the porewater were filtered by the porous media, resulting in more stable GO particle with higher surface charge densities in the effluents. An advection–dispersion-reaction model was applied to simulate GO breakthrough curves and the simulations matched all the experimental data well. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Environmental Pollution Elsevier

Concurrent aggregation and transport of graphene oxide in saturated porous media: Roles of temperature, cation type, and electrolyte concentration

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0269-7491
D.O.I.
10.1016/j.envpol.2017.12.063
Publisher site
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Abstract

Simultaneous aggregation and retention of nanoparticles can occur during their transport in porous media. In this work, the concurrent aggregation and transport of GO in saturated porous media were investigated under the conditions of different combinations of temperature, cation type (valence), and electrolyte concentration. Increasing temperature (6–24 °C) at a relatively high electrolyte concentration (i.e., 50 mM for Na+, 1 mM for Ca2+, 1.75 mM for Mg2+, and 0.03 and 0.05 mM for Al3+) resulted in enhanced GO retention in the porous media. For instance, when the temperature increased from 6 to 24 °C, GO recovery rate decreased from 31.08% to 6.53% for 0.03 mM Al3+ and from 27.11% to 0 for 0.05 mM Al3+. At the same temperature, increasing cation valence and electrolyte concentration also promoted GO retention. Although GO aggregation occurred in the electrolytes during the transport, the deposition mechanisms of GO retention in the media depended on cation type (valence). For 50 mM Na+, surface deposition via secondary minima was the dominant GO retention mechanism. For multivalent cation electrolytes, GO aggregation was rapid and thus other mechanisms such as physical straining and sedimentation also played important roles in controlling GO retention in the media. After passing through the columns, the GO particles in the effluents showed better stability with lower initial aggregation rates. This was probably because less stable GO particles with lower surface charge densities in the porewater were filtered by the porous media, resulting in more stable GO particle with higher surface charge densities in the effluents. An advection–dispersion-reaction model was applied to simulate GO breakthrough curves and the simulations matched all the experimental data well.

Journal

Environmental PollutionElsevier

Published: Apr 1, 2018

References

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