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Lanthanide binding tags (LBTs) have been engineered onto the cell surface of E. coli to enhance biosorption and recovery of rare earth elements (REEs). The protonation behavior of the bacterial surfaces before and after LBT-display was compared by modeling acid-base titration data. A multiple discrete site, constant capacitance surface complexation model was constructed to examine rare earth (Tb) binding to cell surface functional groups, comparing wild type and LBT-engineered surfaces. Our acid-base titrations show similar pKa values between the two strains, suggesting induction of LBTs does not significantly alter cell surface protonation behavior. Tb sorption onto the wild type cell surface can be captured by a one-site carboxyl model. The LBT strain exhibited a higher metal loading that can be explained by the increase of sorption sites in the form of lanthanide binding tags. Furthermore, carboxyl site concentrations between wild type and LBT-induced cells were statistically indistinguishable. We thus attribute the engineered strains’ increase in Tb adsorption capacity and affinity to the addition of lanthanide binding tags to the cell surface. The Tb stability constant with the LBT site is two orders of magnitude higher than that with the carboxyl functional group. As a result, at low metal loading 10 μM, a more abundant but low affinity functional group becomes the main source of adsorption that results in an overall higher sorption capacity. This work demonstrates how surface complexation modeling can be implemented for bacterial surfaces engineered with a known protein tag to optimize REE recovery from fluids with variable pH and metal loadings.

The current uncertainty in the global supply of rare earth elements (REEs) necessitates the development of novel extraction technologies that utilize a variety of REE source materials. Herein, we examined the techno-economic performance of integrating a biosorption approach into a large-scale process for producing salable total rare earth oxides (TREOs) from various feedstocks. An airlift bioreactor is proposed to carry out a biosorption process mediated by bioengineered rare earth-adsorbing bacteria. Techno-economic assessments were compared for three distinctive categories of REE feedstocks requiring different pre-processing steps. Key parameters identified that affect profitability include REE concentration, composition of the feedstock, and costs of feedstock pretreatment and waste management. Among the 11 specific feedstocks investigated, coal ash from the Appalachian Basin was projected to be the most profitable, largely due to its high-value REE content. Its cost breakdown includes pre-processing (leaching primarily, 77.1%), biosorption (19.4%), and oxalic acid precipitation and TREO roasting (3.5%). Surprisingly, biosorption from the high-grade Bull Hill REE ore is less profitable due to high material cost and low production revenue. Overall, our results confirmed that the application of biosorption to low-grade feedstocks for REE recovery is economically viable.