Dual porosity modeling of lanthanide separation using fixed-bed columns of bead-encapsulated, engineered Escherichia coli
Abstract
While biosorption of rare earth elements (REEs) has been studied in the context of recovery and separation from geochemically complex geothermal fluids and mining leachates, selective separation of heavy and light REEs remains a considerable challenge. Experiments performed in batch indicate that E. coli cells engineered with lanthanide binding tags (LBTs) preferentially adsorb REEs, particularly the more valuable heavy REEs, facilitating separation from competing metals such as Cd and Ni. In this study, engineered cells were immobilized in non-sorbing, permeable polyethylene glycol diacrylate (PEGDA) beads and packed into continuous flow, fixed-bed columns. Separation and breakthrough of fourteen lanthanides and yttrium were investigated. We observed notable differences in the columns' adsorption selectivity across the lanthanide series, with greatest retention of europium and least retention of lanthanum. Predictions for mixed-REE adsorption onto these fixed-bed columns were made by coupling a surface complexation model to a calibrated dual porosity model that accounts for inter-bead advective and intra-bead diffusive transport. Thermodynamic binding constants for REE-surface complexation reactions estimated based on data obtained in batch gave good predictions of REE separation on the columns. In regards to the hydrodynamic dispersion, dispersivity plays a significantly larger role than individual lanthanide variations in the effective diffusion coefficient. Thus, separation between light and heavy lanthanides is not controlled by dispersive transport but rather chemical selectivity determined by the reactive term of the advection-reaction-dispersion equation. Our study demonstrates the application of dual-porosity reactive transport modeling to optimize for lanthanide separation during biosorption.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.H21M1938C
- Keywords:
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- 0496 Water quality;
- BIOGEOSCIENCES;
- 1009 Geochemical modeling;
- GEOCHEMISTRY;
- 1847 Modeling;
- HYDROLOGY