Lead University: Lehigh University
PI: Sibel Pamukcu, Department of Civil and Environmental Engineering
Co-PI(s): Mesut Pervizpour, Department of Civil and Environmental Engineering; Greg Ferguson, Department of Chemistry
PA Industry: Earth Engineering Inc.; Spring House PolyX, LLC; J & M Associates
This project proposes the synthesis, laboratory and field characterization of externally stimulated smart particles that perform on demand as oil water separator, contaminant filter, flow retardant/enhancer. The proposed material and method is expected to provide enhanced control over engineered facilities for sustained treatment, filtration and separation capabilities, particularly applicable to oily wastewaters. The end result is envisioned to be modular “smart sand” or “smart glass bead” packs embedded in the subsurface or placed in a wastewater pond or in the vicinity of civil infrastructure to work as in-situ or ex-situ separator or filter systems.
Currently there are a number of methods and materials available on the market that are used to separate oil and other contaminants from water. The technology development proposed in here falls within this category, but is an advanced method of recovery that makes use of the unique reversible filtering and separation characteristic of the smart polymer coated substrate. The particulate substrate (i.e., sand or glass) is prepared using a state-of-art polymerization technique to graft smart polymer on to the particles. An earlier study at Lehigh University have demonstrated that sand packs synthesized with thermally stimulated polymer change their surface wettability at a critical temperature, which is reversible. When used as an oil-water separator or an environmental filter, this unique feature of externally triggered, reversible surface function is believed to provide significant advantage over existing systems. The filtering and separation properties of the smart sand or glass bead packs can be switched on and off on demand, regenerated and reused in a dynamic environment of spatial and temporal variations.