Simulating the Self-Assembly and Hysteresis Loops of Ferromagnetic Nanoparticles with Sticking of Ligands

Abstract

The agglomeration of ferromagnetic nanoparticles in a fluid is studied using nanoparticle-level Langevin dynamics simulations. The simulations have interdigitation and bridging between ligand coatings included using a computationally-cheap, phenomenological sticking parameter c. The interactions between ligand coatings are shown in this preliminary study to be important in determining the shapes of agglomerates that form. A critical size for the sticking parameter is estimated analytically and via the simulations and indicates where particle agglomerates transition from well-ordered (c is small) to disordered (c is large) shapes. Results are also presented for the hysteresis loops (magnetization versus applied field) for these particle systems in an oscillating magnetic field appropriate for hyperthermia applications. The results show that the clumping of particles has a significant effect on their macroscopic properties, with important consequences on applications. In particular, the work done by an oscillating field on the system has a nonmonotonic dependence on c.

Tunability and Ordering in 2D Arrays of Magnetic Nanoparticles Assembled via Extreme Field Gradients

“…The equations are similar to those in Ref. [37], apart from the addition of the assembling force due to the magnetic field gradient of the hard disk drive. Other forces and torques included were dipolar interactions, steric repulsion, and van der Waals attraction between particles.…”

Analyte‐Driven Clustering of Bio‐Conjugated Magnetic Nanoparticles

“…The characteristic time $$t_{\text{tr}}$$ is given by the translational diffusion and the concentration of the nanoparticles [ 38 ] $$$$\begin{equation} t_{\text{tr}} = \frac{x^26\pi R_\text{h} \eta }{k_\text{B}T} \end{equation}$$$$where $$x=(\frac{V}{N_\text{p}})^{1/3}$$. As can be seen from Equation (10), the clustering is faster (i.e., $$t_\text{r}$$ is smaller) when using solvent with lower viscosity η.…”

Dumbbells, chains, and ribbons: anisotropic self-assembly of isotropic nanoparticles

“…In every field, it is crucial to control the extent of NP selfassembly [13][14][15] , both during the synthesis stage and in the target application environment [15][16][17] . The interaction forces that drive NP self-assembly can originate from geometric, electric, or magnetic properties of the NP core [18][19][20][21][22] . For instance, the shape of the NPs is a feature that can be used to obtain assemblies with specific structures 17,[22][23][24][25] .…”

“…Functionalization with a shell of covalently bound molecules is a common strategy for designing the surface features of colloidal nanomaterials. The functionalizing shell can assure colloidal stability or mediate the self-assembly behavior to form aggregates with controlled shapes 18,19,29,30 . The ligands on the NP surface can mediate NP-NP interactions by different means: simple Coulomb forces for charged ligands [31][32][33][34][35] , hydrogen bonds 14,18 , dipole-dipole interactions 14,18,32 , DNA base pairing interactions 14,18 , and hydrophobic interactions 36,37 .…”