RETRACTED ARTICLE: Amine functionalized magnetic nanoparticles for removal of oil droplets from produced water and accelerated magnetic separation
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Source abstract
Abstract
Magnetic nanoparticles (MNPs) with surface coatings designed for water treatment, in particular for targeted removal of contaminants from produced water in oil fields, have drawn considerable attention due to their environmental merit. The goal of this study was to develop an efficient method of removing very stable, micron-scale oil droplets dispersed in oilfield produced water. We synthesized MNPs in the laboratory with a prescribed surface coating. The MNPs were superparamagnetic magnetite, and the hydrodynamic size of amine functionalized MNPs ranges from 21 to 255 nm with an average size of 66 nm. The initial oil content of 0.25 wt.% was reduced by as much as 99.9% in separated water. The electrostatic attraction between negatively charged oil-in-water emulsions and positively charged MNPs controls, the attachment of MNPs to the droplet surface, and the subsequent aggregation of the electrically neutral oil droplets with attached MNPs (MNPs-oils) play a critical role in accelerated and efficient magnetic separation. The total magnetic separation time was dramatically reduced to as short as 1 s after MNPs, and oil droplets were mixed, in contrast with the case of free, individual MNPs with which separation took about 36∼72 h, depending on the MNP concentrations. Model calculations of magnetic separation velocity, accounting for the MNP magnetization and viscous drag, show that the total magnetic separation time will be approximately 5 min or less, when the size of the MNPs-oils is greater than 360 nm, which can be used as an optimum operating condition.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Enhanced Oil Recovery Techniques · Minerals Flotation and Separation Techniques · Hydrocarbon exploration and reservoir analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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