The scarcity of potable water is an imminent threat to at least half the world's population. Engineered nanomaterials (ENMs) have the potential to treat water from polluted sources to mitigate the scarcity of potable water. However, the performance demands on these materials in practical applications has not been studied in detail. This is but one of the challenges that hinder the widespread implementation of ENMs for water treatment. The emerging fit-for-purpose paradigm which encourages water treatment at the point-of-use (POU) or point-of-entry (POE) could lower the barrier for the use of ENMs in water technology by incorporating smaller, decentralized ENM-based treatment systems. This work develops a bottom-up and top-down modeling framework to facilitate the design of nanoporous membrane-based sorbents, a promising class of ENMs, for POU and POE water treatment applications. Langmuir isotherm and membrane structure-property calculations provide the multiscale link between molecular properties, including affinity, saturation capacity, and pore size, device design decisions, including membrane area and thickness, and system design decisions, including sorbent mass and number of parallel modules. The framework predicts that for lead contaminants, existing materials are near molecular and systems limitations; improvements in the properties of adsorptive materials to treat lead will yield few benefits for POU and POE treatment systems. Moreover, the framework provides dimensionless formulas that apply to all adsorptive systems that exhibit (near) equilibrium behavior as an easy-to-use tool for the broader membrane science and environmental engineering communities to assess the feasibility of emerging materials to meet process demands. A case study regarding materials for arsenic removal demonstrates how to apply the modeling framework to calculate material properties targets and predict system performance for an arbitrary single-solute adsorption process. Finally, these dimensionless models are used to identify three distinct regions of relative performance between batch and semi-continuous processes. These results give caution to applying scale-up heuristics outside their valid region, which can lead to under- or over-design during bottom-up studies. The presented modeling framework is a crucial step to fully optimize engineered nanomaterials across material, device, and system scales.
Drinking water treatment by iron anode-based electrocoagulation: humic acids and arsenic removal
