Recovery of Rare Earth Elements from Geothermal Fluids through Bacterial Cell Surface Adsorption

The increasing demand for rare earth elements (REEs) in the modern economy motivates the development of novel strategies for cost-effective REE recovery from nontraditional feedstocks. We previously engineered E. coli to express lanthanide binding tags on the cell surface, which increased the REE biosorption capacity and selectivity. Here we examined how REE adsorption by the engineered E. coli is affected by various geochemical factors relevant to geothermal fluids, including total dissolved solids (TDS), temperature, pH, and the presence of specific competing metals. REE biosorption is robust to TDS, with high REE recovery efficiency and selectivity observed with TDS as high as 165,000 ppm. Among several metals tested, U, Al, and Pb were found to be the most competitive, causing >25% reduction in REE biosorption when present at concentrations ∼3- to 11-fold higher than the REEs. Optimal REE biosorption occurred between pH 5–6, and sorption capacity was reduced by ∼65% at pH 2. REE recovery efficiency and selectivity increased as a function of temperature up to ∼70 °C due to the thermodynamic properties of metal complexation on the bacterial surface. Together, these data define the optimal and boundary conditions for biosorption and demonstrate its potential utility for selective REE recovery from geofluids

Supplemental Material - A Novel Osteoporosis Screening Protocol to Identify Orthopedic Surgery Patients for Preoperative Bone Health Optimization

Supplemental Material for A Novel Osteoporosis Screening Protocol to Identify Orthopedic Surgery Patients for Preoperative Bone Health Optimization by Elliot Chang, Brian Nickel, Neil Binkley, James Bernatz, Diane Krueger, Alec Winzenried, and Paul A. Anderson in Geriatric Orthopaedic Surgery & Rehabilitation</p

Community Data Mining Approach for Surface Complexation Database Development

This paper presents a comprehensive data-to-model workflow, including a findable, accessible, interoperable, reusable (FAIR) community sorption database (newly developed LLNL Surface Complexation/Ion Exchange (L-SCIE) database) along with a data fitting workflow to efficiently optimize surface complexation reaction constants with multiple surface complexation model (SCM) constructs. This workflow serves as a universal framework to mine, compile, and analyze large numbers of published sorption data as well as to estimate reaction constants for parameterizing reactive transport models. The framework includes (1) data digitization from published papers, (2) data unification including unit conversions, and (3) data-model integration and reaction constant estimation using geochemical software PHREEQC coupled with the universal parameter estimation code PEST. We demonstrate our approach using an analysis of U­(VI) sorption to quartz based on a first L-SCIE implementation, concluding that a multisite SCM construct with carbonate surface species yielded the best fit to community data. Surface complexation reaction constants extracted from this approach captured all available sorption data available in the literature and provided insight into previously published reaction constants and surface complexation model constructs. The L-SCIE sorption database presented herein allows for automating this approach across a wide range of metals and minerals and implementing novel machine learning approaches to reactive transport in the future

Microbe Encapsulation for Selective Rare-Earth Recovery from Electronic Waste Leachates

Rare earth elements (REEs) are indispensable components of many green technologies and of increasing demand globally. However, refining REEs from raw materials using current technologies is energy intensive and enviromentally damaging. Here, we describe the development of a novel biosorption-based flow-through process for selective REE recovery from electronic wastes. An Escherichia coli strain previously engineered to display lanthanide-binding tags on the cell surface was encapsulated within a permeable polyethylene glycol diacrylate (PEGDA) hydrogel at high cell density using an emulsion process. This microbe bead adsorbent contained a homogenous distribution of cells whose surface functional groups remained accessible and effective for selective REE adsorption. The microbe beads were packed into fixed-bed columns, and breakthrough experiments demonstrated effective Nd extraction at a flow velocity of up to 3 m/h at pH 4–6. The microbe bead columns were stable for reuse, retaining 85% of the adsorption capacity after nine consecutive adsorption/desorption cycles. A bench-scale breakthrough curve with a NdFeB magnet leachate revealed a two-bed volume increase in breakthrough points for REEs compared to non-REE impurities and 97% REE purity of the adsorbed fraction upon breakthrough. These results demonstrate that the microbe beads are capable of repeatedly separating REEs from non-REE metals in a column system, paving the way for a biomass-based REE recovery system