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Modeling the Transport of Reduced Graphene Oxide—Metal Oxide Nanohybrids in Water Saturated Porous Media (H21M-1866)
Citation:
Wang, D., C. Park, N. Aich, AND C. Su. Modeling the Transport of Reduced Graphene Oxide—Metal Oxide Nanohybrids in Water Saturated Porous Media (H21M-1866). American Geophysical Union Annual Meeting, Washington, District Of Columbia, December 10 - 13, 2018.
Impact/Purpose:
The “new-horizon” nanohybrids (NHs) that are nano/hierarchical assemblies of multiple nanomaterials hold great promise for addressing issues and meeting challenges within water-energy-agriculture-environment nexus, due to their enhanced properties, optimized multifunctionalities, and maximized performances. Increasing production and widespread application of these new NHs will inevitably result in their wide dissemination in the subsurface environment. However, little is known about NHs fate and transport in the subsurface, which greatly limits our capability in maximizing their advantages (e.g., soil and groundwater nanoremediation) while minimizing their potential adverse impacts and risks to the environment and human health. Herein, saturated sand-packed column experiments were performed to study the transport of the most widely used NHs, reduced graphene oxide (RGO)—metal oxide (Fe3O4, TiO2, and ZnO) NHs under environmentally-relevant conditions. Colloid science principles (Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and colloid filtration theory (CFT)) and mathematical models based upon 1D convection-dispersion equation were employed to describe and predict the mobility of RGO-Fe3O4, RGO-TiO2, and RGO-ZnO nanohybrids. Results show that the mobility of the NHs is explainable by DLVO theory and CFT. Numerical simulations suggest that the one-site kinetic retention model (OSKRM) considering both time- and depth-dependent retention accurately approximated breakthrough curves and retention profiles of the nanohybrids; whereas, others (e.g., two-site kinetic retention model) failed. Direct simulations using model-fitted parameters from the OSKRM successfully forecast the transport and retention of the NHs in the environment. Our findings address the existing knowledge gap regarding the impact of physicochemical factors on the transport of the next-generation, multifunctional RGO—metal oxide NHs in the subsurface environments. The results further inform potential risk assessment and management by EPA on the newly-emerging RGO-metal NHs.
Description:
Little is known about the fate and transport of the newly-emerging nanohybrids in the subsurface environments. Saturated sand-packed column experiments were performed to investigate the transport behaviors of reduced graphene oxide (RGO)—metal oxide (Fe3O4, TiO2, and ZnO) nanohybrids under environmentally-relevant conditions (mono- and di-valent electrolytes and natural organic matter). Classical colloid science principles (Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and colloid filtration theory (CFT)) and mathematical models based upon 1D convection-dispersion equation were employed to describe and predict the mobility of RGO-Fe3O4, RGO-TiO2, and RGO-ZnO nanohybrids. Results indicate that the mobility of the three nanohybrids under varying experimental conditions is explainable by DLVO theory and CFT. Numerical simulations suggest that the one-site kinetic retention model (OSKRM) considering both time- and depth-dependent retention accurately approximated breakthrough curves (BTCs) and retention profiles (RPs) of the nanohybrids; whereas, others (e.g., two-site kinetic retention model) failed to capture the BTCs and/or RPs. This is primarily because blocking BTCs and exponential/hyperexponential/uniform RPs occurred, which is within the framework of OSKRM featuring time- (for kinetic Langmuirian blocking) and depth-dependent (for exponential/hyperexponential/uniform) retention kinetics. Employing fitted-parameters (maximum solid-phase retention capacity: Smax=0.0406–3.06 cm3/g; and first-order attachment rate coefficient: ka=0.133–20.6 min–1) extracted from the OSKRM and environmentally-representative physical variables (flow velocity (0.00441–4.41 cm/min), porosity (0.24–0.54), and grain size (210–810 µm)) as initial input conditions, the long-distance transport scenarios (in 500-cm long sand columns) of nanohybrids were predicted via forward simulation. Our findings address the existing knowledge gap regarding the impact of physicochemical factors on the transport of the next-generation, multifunctional RGO—metal oxide nanohybrids in the subsurface environments.