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Patterned-MOF-Functionalized Nanofiltration Membranes for Selective Removal of Selenium and Arsenic from Fracking Wastewater

$397,563FY2020ENGNSF

University Of Alabama Tuscaloosa, Tuscaloosa AL

Investigators

Abstract

Hydraulic fracturing or "fracking" of rock layers to release the oil and gas trapped within produces a substantial amount of wastewater that is typically disposed of by pumping it back underground. This process has the unfortunate side-effect of increasing seismic activity in disposal areas. The ability to remove any hazardous components returned in the wastewater, so that it can be reused in the fracking process or for other purposes such as irrigation, would minimize the detrimental impact of fracking in local communities. Toxic heavy metals, such as selenium and arsenic, are among the hazardous materials found in fracking wastewater. This project will develop a new approach to remove selenium and arsenic from fracking wastewater using nanofiltration (NF) membranes. NF membranes are semi-permeable, meaning certain small molecules or ions (i.e., sodium chloride) pass through the membrane while other components are trapped behind the membrane. NF membranes are susceptible to oil-fouling when treating fracking wastewater, or in other words, oil contaminants remaining in the wastewater collects at the membrane surface until water and small molecules can no longer pass through. Therefore, this project will utilize surface patterns and anti-fouling metal organics frameworks (MOFs) to prevent membrane oil-fouling. MOFs are a class of highly porous crystalline materials formed from metal ions and organic linkers. MOFs are an attractive modifier in membrane synthesis since they can selectively capture dissolved molecules and ions from large volumes of fluid. The effectiveness of this separation arises from the affinity of the MOF for the molecule or ion, the extraordinarily high porosity of the material, and the ability to tune the sorbent properties of the material to the molecule of interest. Engineering surface patterns on the MOF is expected to create localized mixing such that foulant materials are less likely to stick to a membrane surface. The overall research effort aims to enable sustainable treatment schemes for fracking wastewater by removing toxic heavy metals. The proposed research will be carried out by graduate and undergraduate students, who will collaboratively develop research plans, mentor other students, and perform STEM outreach to local K-12 students from underrepresented groups. Additionally, water treatment and membrane design concepts will be incorporated into the research team’s classes to expose undergraduate and graduate students to current topics and challenges in water treatment. This project aims to mitigate oil-fouling and adsorption capacity reduction using surface patterns and anti-fouling metal-organic frameworks to maintain MOF selectivity for selenium and arsenic while incorporated in an NF membrane to treat fracking wastewater. The investigators hypothesize that surface micro-patterning and anti-fouling graphene oxide (GO)-decorated MOFs will mitigate oil-induced membrane fouling, thereby preventing capacity and selectivity loss of thin-film nanocomposite membranes in produced water service. The approach will examine three different sized micro-patterns and two types of GO-decorated MOFs to tailor anti-fouling ability, selectivity, and permeance. The project will yield fundamental understanding of how pattern size and synthesis procedure affect the MOF capacity, selectivity, and oil-fouling resistance. This project will generate new knowledge on whether GO-decorated MOFs, specifically GO-Cu- and GO-Fe-MOFs, improve anti-fouling performance over non-GO-decorated MOFs. Ultimately, the proposed research is expected to enable sustainable produced water treatment schemes through the removal of toxic heavy metals. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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