Magnetic resonance imaging reveals detailed spatial and temporal distribution of iron-based nanoparticles transported through water-saturated porous media

J Contam Hydrol. 2015 Nov:182:51-62. doi: 10.1016/j.jconhyd.2015.08.005. Epub 2015 Aug 24.

Abstract

The application of engineered nanoparticles (ENP) such as iron-based ENP in environmental systems or in the human body inevitably raises the question of their mobility. This also includes aspects of product optimization and assessment of their environmental fate. Therefore, the key aim was to investigate the mobility of iron-based ENP in water-saturated porous media. Laboratory-scale transport experiments were conducted using columns packed with quartz sand as model solid phase. Different superparamagnetic iron oxide nanoparticles (SPION) were selected to study the influence of primary particle size (d(P)=20 nm and 80 nm) and surface functionalization (plain, -COOH and -NH2 groups) on particle mobility. In particular, the influence of natural organic matter (NOM) on the transport and retention behaviour of SPION was investigated. In our approach, a combination of conventional breakthrough curve (BTC) analysis and magnetic resonance imaging (MRI) to non-invasively and non-destructively visualize the SPION inside the column was applied. Particle surface properties (surface functionalization and resulting zeta potential) had a major influence while their primary particle size turned out to be less relevant. In particular, the mobility of SPION was significantly increased in the presence of NOM due to the sorption of NOM onto the particle surface resulting in a more negative zeta potential. MRI provided detailed spatially resolved information complementary to the quantitative BTC results. The approach can be transferred to other porous systems and contributes to a better understanding of particle transport in environmental porous media and porous media in technical applications.

Keywords: Breakthrough curve (BTC) analysis; Colloidal transport; Engineered nanoparticles (ENP); Magnetic resonance imaging (MRI); Natural organic matter (NOM); Superparamagnetic iron oxide nanoparticles (SPION).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Ferric Compounds / analysis
  • Ferric Compounds / chemistry
  • Iron / analysis*
  • Magnetic Resonance Imaging / methods*
  • Nanoparticles / analysis*
  • Nanoparticles / chemistry
  • Particle Size
  • Porosity
  • Quartz
  • Spatio-Temporal Analysis
  • Surface Properties
  • Water
  • Water Pollutants, Chemical / analysis*

Substances

  • Ferric Compounds
  • Water Pollutants, Chemical
  • Water
  • Quartz
  • ferric oxide
  • Iron