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Surface-modified magnetite nanoparticles using polyethylene terephthalate waste derivatives for oil spill remediation.

Mahmood M S AbdullahHamad A Al-LohedanNoorah A Faqihi
Published in: RSC advances (2023)
This work aims at synthesizing new cross-linked poly ionic liquids, CPILs, VIMDE-Cl and CPIL, VIMDE-TFA, utilizing polyethylene terephthalate waste as a precursor and applying them to magnetite nanoparticles surface modification, producing surface-modified magnetite nanoparticles, SMNPs, VDCL/MNPs, and VDTA/MNPs, respectively. The structures of VIMDE-Cl and VIMDE-TFA, VDCL/MNPs, and VDTA/MNPs, were verified using different techniques. The particle sizes of SMNPs, VDCL/MNPs, and VDTA/MNPs, were evaluated with a transmission electron microscope and dynamic light scattering. The compatibility of VDCL/MNPs and VDTA/MNPs with crude oil components and their response to an external magnet were also measured using contact angle measurements and a vibrating sample magnetometer. The data confirmed the formation of SMNPs, nanosized structure, compatibility with oil components, and response to an external magnet. For that, VDCL/MNPs and VDTA/MNPs were applied for oil spill recovery using different SMNP : crude oil weight ratios. The impact of contact time on SMNPs' performance was also evaluated. The data indicated increased performance with an increase in SMNPs ratio, reaching maximum values of 99% and 96% for VDCL/MNPs and VDTA/MNPs, respectively, at SMNPs : crude oil ratio of 1 : 1. According to the results, the optimal contact time was 6 min, resulting in 89% and 97% performance for VDCL/MNPs and VDTA/MNPs at 1 : 4 SMNPs : crude oil ratio.
Keyphrases
  • ionic liquid
  • high resolution
  • electronic health record
  • physical activity
  • machine learning
  • weight loss
  • big data
  • deep learning
  • artificial intelligence