- Nano Express
- Open Access

# Assessment of Influence of Magnetic Forces on Aggregation of Zero-valent Iron Nanoparticles

- Dana Rosická
^{1}Email author and - Jan Šembera
^{1}

**Received: **21 June 2010

**Accepted: **10 August 2010

**Published: **24 August 2010

## Abstract

Aggregation of zero-valent nanoparticles in groundwater is influenced by several physical phenomena. The article shortly introduces preceding works in modeling of aggregation of small particles including influence of sedimentation, velocity profile of water, heat fluctuations, and surface electric charge. A brief description of inclusion of magnetic forces into the model of aggregation follows. Rate of influence of the magnetic forces on the aggregation depends on the magnitude of magnetization of the particles, radius of nanoparticles, size of the aggregates, and their concentration in the solution. Presented results show that the magnetic forces have significant influence on aggregation especially of the smallest iron particles.

## Keywords

## Introduction

Zero-valent iron nanoparticles (nZVI) composed of iron and its oxides are spherical particles with diameter approximately 50 nm and with a large specific surface. These particles are used for the decontamination of groundwater and soil and especially for the decontamination of organic pollutants such as halogenated hydrocarbons [1]. Nanoparticles migrate through the soil and can reach the contamination in-situ. Properties of the nZVI and remediation possibilities depend on methods of production [2]. At the Technical University of Liberec, experiments with iron nanoparticles TODA produced by the company Toda Kogyo Corp. [3] and with the nanoparticles NANOFER, produced by the company NANO IRON s.r.o. [4], are made. During a remedial intervention, transport of the iron nanoparticles is slowed down due to rapid aggregation of them. The rate of aggregation increases with growing concentration of particles in solution and with growing ionic strength of the solution [5]. For the preservation of the transport properties, it is advisable to stabilize the particles. A lot of methods of stabilization were published [6–10]. We simulate the transport of the iron nanoparticles and that is why we examine the interactions among them causing the aggregation. Models of aggregation of small particles were published in many articles (e.g. [11–13]). They are mostly based on the publications [14, 15]. However, this generally used model is insufficient for our case. A surface charge established on the surface of particles causes repulsive electrostatic forces between them. The influence on the aggregation into the known aggregation model was implemented [16]. The iron particles corrode in the water, and this process causes change of the surface charge as well as the change of the rate of aggregation [17]. Because the particles are made from iron, they also have magnetic properties, which significantly affects the rate of aggregation [2, 18–21]. That is why we want to derive a mathematical model of magnetic forces among particles and to add it into the aggregation model. There is shown a procedure of the derivation of the model in this paper and there is made also an evaluation of the rate of aggregation influenced by magnetic forces here.

The extended model of the aggregation of iron nanoparticles will be included into a solver of particle transport in groundwater. It would allow to simulate the transport of iron nanoparticles and to predict the efficiency of the remedial intervention. That could be useful for the proposal of optimal remedial intervention, which would enable to decontaminate an affected area efficiently and economically.

## Aggregation of Colloids and Small Particles in Groundwater

The particles in groundwater aggregate easily. They create clumps of particles up to the size of several μm [20] that cohere and decrease the possibility of migration of particles through pores of the ground. The aggregation of particles is proven by experiments described in many articles. In [22], particle size, size distribution and surface composition were characterized by transmission electron microscopy (TEM), X-ray diffraction, high-resolution X-ray photoelectron spectroscopy, X-ray absorption near edge structure, and acoustic/electroacoustic spectrometry. There are presented micrographs of a single particle and aggregates of iron particles in the article. In [3], characterization of iron nanoparticles using TEM according to methods of its preparation is done. In [20], a type of aggregation according to beginning concentration of iron nanoparticles is studied by dynamic light scattering, optical microscopy, and sedimentation measurements.

^{3}s

^{-1}]. It was published in many papers (e.g. [11, 15]). The coefficients give a probability

*P*

_{ ij }of creation of aggregate from particle

*i*and particle

*j*together with concentrations

*n*

_{ i },

*n*

_{ j }of particles

*i*and particles

*j*(1). Particle

*i*means the aggregate created from

*i*elementary nanoparticles.

The ${\beta}_{ij}^{3}$ is the mass transport coefficient of aggregation caused by the gravity, ${\beta}_{ij}^{2}$ is the mass transport coefficient for the velocity gradients, and ${\beta}_{ij}^{1}$ stands for the mass transport coefficient of the heat fluctuations. The notation is adopted from [11].

where *g* is gravity acceleration, η is viscosity of medium, *ϱ* is density of medium, *ϱ*_{
p
} is density of aggregating particles, *d*_{
i
} is diameter of particle *i*.

where *G* is the average velocity gradient in a pore.

where *k*_{
B
} stands for Boltzmann constant and *T* denotes absolute temperature.

The mass transport coefficients for Brownian diffusion, velocity gradients, and sedimentation, for different sizes of aggregates

i | j | ${\beta}_{ij}^{1}$ | ${\beta}_{ij}^{2}$ | ${\beta}_{ij}^{3}$ |
---|---|---|---|---|

1 | 1 | 1.0 × 10 | 2.2 × 10 | 0 |

1 | 10 | 1.3 × 10 | 8.8 × 10 | 5.9 × 10 |

1 | 10 | 1.9 × 10 | 5.0 × 10 | 1.0 × 10 |

1 | 10 | 3.3 × 10 | 3.7 × 10 | 2.0 × 10 |

1 | 10 | 6.5 × 10 | 3.2 × 10 | 3.8 × 10 |

1 | 10 | 1.3 × 10 | 3.0 × 10 | 7.9 × 10 |

1 | 10 | 2.8 × 10 | 3.0 × 10 | 1.7 × 10 |

1 | 10 | 6.0 × 10 | 2.8 × 10 | 3.5 × 10 |

10 | 10 | 1.1 × 10 | 2.2 × 10 | 0 |

10 | 10 | 1.3 × 10 | 8.8 × 10 | 1.2 × 10 |

10 | 10 | 1.1 × 10 | 2.2 × 10 | 5.9 × 10 |

10 | 10 | 1.3 × 10 | 8.8 × 10 | 0 |

The mass transport coefficient for the velocity gradients is quantified for the case with a small size of pores and a large flux (flux = 3.67 × 10^{-4} ms^{-1}, porosity = 0.39, velocity gradient *G* = 50 s^{-1}). In the other cases, the mass transport coefficient would be much smaller than the others.

## Electrostatic Forces Among Iron Nanoparticles

A mathematical model of aggregation for the case of iron particles was compiled. The sedimentation, velocity gradients, and Brownian diffusion are not sufficient for the description of the process aggregation. The surface of iron particles oxidizes. The ions on the surface attract ions from the electrolyte and the electric double layer arises. Therefore, the influence of the electrostatic forces was added in the mass transport coefficients. The detailed derivation of it is published in [16, 23].

_{ i }and σ

_{ j }stand for surface charge on particle

*i*and particle

*j*, respectively,

*ε*

_{0}is permittivity of the medium. If the term that reduces the mass transport coefficient is greater than the mass transport coefficient without the influence of electrostatic forces ${\beta}_{ij}^{3}$, the probability of collision of particles

*i*and

*j*should be equal to zero. That is why

*i*with a particle

*j*is then

The statistical assessment of the importance of the electrostatic forces to the creation of the aggregates was done in [16, 23]. The results are that the mass transport coefficient for Brownian diffusion is limited by the electrostatic forces mostly for large aggregates. The mass transport coefficient for the velocity gradients is not limited by the surface charge for measured ζ potential. The ζ potential would have to be minimally ten times larger to affect the rate of aggregation. The mass transport coefficient for sedimentation is limited by the surface charge mostly for the small particles.

## Magnetic Field of Iron Particles

**r**near a permanent magnet is equal to

where the vector **M** is the vector of magnetic polarization at the point *dV*, the vector **R** is the difference between the source of magnetic field *dV* and the point **r**, *R* is the length of **R**.

**H**can be subsequently computed as

**H**and a permanent magnet with the vector of polarization

**M**

_{0}at the point

**r**is equal to

### Magnetic Forces Between Two Spherical Iron Nanoparticles

*a*located at the point [0, 0, 0] was determined:

where *a* is the radius of the nanoparticle and [*x*_{1}, *x*_{2}, *x*_{3}] are the coordinates of the point **r**. The direction of the vector of polarization **M** is set to the direction *x*_{3}, *M* is the magnitude of the vector **M**.

_{i 3}stands for Kronecker delta and

*i*= 1, 2, 3. The symbol

*C*(

**r**) replaces

*a*which is touching the center of the upper right side of the figure. The figure is created by the software Mathematica 5, copyrighted by Wolfram Research, Inc.

### Magnetic Field Around an Aggregate

The aggregate of iron nanoparticles is in fact a clump of many permanent magnets. It is impossible to establish an analytical model of interaction of two such aggregates. To analyze statistically the influence of the magnetic forces on aggregation of two nanoparticle aggregates, a script for the examination of the worst possibility (the largest forces) and the averaged possibility of influencing the aggregation by the magnetic forces was written down.

where φ_{
i
} is potential of magnetic field of the nanoparticle located in the point **r**_{
i
}.

The influence of magnetic forces in comparison with the gravitational forces is investigated. It could be compared also with other affecting forces but the gravitation force was chosen for the reason of small number of variables. If one aggregate is in a fixed position and another one is located somewhere vertically under it, there should be a unique distance ("effective range") between them so that if they are closer than it, the lower aggregate would attach to higher one by magnetic forces. If they are more distant, they would sediment separately. The distance is measured between the surfaces of particles.

^{-1}. More important information than absolute values is the trends of the lines.

According to the results from the Table 1 in the Section 2, sedimentation influences the aggregation mostly when the difference between sizes of the two aggregates is large. Consequently, the dashed line in the Figure 4 gives a good information about the influence of magnetic forces on aggregation of aggregates of different sizes. The solid line comparing the influence of magnetic and gravitational forces between two similar aggregates does not include the real information about the influence of magnetic forces because another force than gravitational governs the aggregation process in such a case.

On the basis of this result, it is obvious that the magnetic forces among particles have significant effect on the rate of aggregation of the particles. On the basis of the effective range, concentration of particles uniformly dispersed in solution can be computed. According to distances between particles, the concentration would have to be very small (about 15 mg l^{-1}) to be possible to neglect the influence of the magnetic forces.

## Conclusion

The influence of the magnetic forces among iron particles on the rate of aggregation in terms of the "effective range" was assessed. The effective range is a distance in which the magnetic forces outweigh the gravitation force that causes the aggregation. To assess the magnetic field around more interacting aggregates, it should be made a model using the Finite Element Method (FEM) or another numerical method. The next steps in the studying of nanoparticle aggregation due to magnetic forces can be the evaluation of the effective range in comparison with other forces indicated in this paper and/or building a FEM model of nZVI aggregate.

## Declarations

### Acknowledgements

This result is realized under the state subsidy of the Czech Republic within the research and development project "Advanced Remediation Technologies and Processes Center" 1M0554—Program of Research Centers PP2-DP01 supported by Ministry of Education and within the research project FR-TI1/456 "Development and implementation of the tools additively modulating soil and water bioremediation"—Program MPO-TIP supported by Ministry of Industry and Trade. Kind thanks to Jiří Tuček from the Palacký University Olomouc for granting of Figure 2.

## Authors’ Affiliations

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## Copyright

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.