All-Atom Simulation Method for Zeeman Alignment and Dipolar Assembly of Magnetic Nanoparticles

Metaparticles: Computationally engineered nanomaterials with tunable and responsive properties

In simulations, particles are traditionally treated as rigid platforms with variable sizes, shapes, and interaction parameters. While this representation is applicable for rigid core platforms, particles consisting of soft platforms (e.g., micelles, polymers, elastomers, and lipids) inevitably deform upon application of external stress. We introduce a generic model for flexible particles, which we refer to as MetaParticles (MPs). These particles have tunable properties, can respond to applied tension, and can deform. A MP is represented as a collection of Lennard-Jones beads interconnected by spring-like potentials. We model a series of MPs of variable sizes and symmetries, which we subject to external stress, followed by relaxation upon stress release. The positions and the orientations of the individual beads are propagated by Brownian dynamics. The simulations show that the mechanical properties of the MPs vary with size, bead arrangement, and area of applied stress, and share an elastomer-like response to applied stress. Furthermore, MPs deform following different mechanisms, i.e., small MPs change shape in one step, while larger ones follow a multi-step deformation pathway, with internal rearrangements of the beads. This model is the first step toward the development and understanding of particles with adaptable properties with applications in the biomedical field and in the design of bioinspired metamaterials.

Tuning the dimensional order in self-assembled magnetic nanostructures: theory, simulations, and experiments

A major obstacle to building nanoscale magnetic devices or even experimentally studying novel nanomagnetic spin textures is the present lack of a simple and robust method to fabricate various nano-structured alloys. Here, theoretical and experimental investigations were conducted to understand the underlying physical mechanisms of magnetic particle self-assembly in zero applied magnetic field. By changing the amount of NaOH added during the synthesis, we demonstrate that the resulting morphology of the assembled FeCo structure can be tuned from zero-dimensional (0D) nanoparticles to one-dimensional (1D) chains, and even three-dimensional (3D) networks. Two numerical simulations were developed to predict aspects of nanostructure formation by accounting for the magnetic interactions between individual magnetic nanoparticles. The first utilized the Boltzmann distribution to determine the equilibrium structure of a nanochain, iteratively predicting the local deviation angle θ of each particle as it attaches to a forming chain. The second simulation illustrates the differences in nanostructure arrangement and dimensionality (0D, 1D, or 3D) that arise from random interactions at various nanoparticle densities. The simulation results closely match the experimental findings, as seen from SEM images, demonstrating their ability to capture the system's structural properties. In addition, magnetic hysteresis measurements of the samples were performed along two orthogonal directions to show the influence of dimensional order on the magnetic behavior. The normalized remanence (MR/MS||) of the FeCo alloys increases as the dimensions of nanostructures are increased. Of the three cases, the FeCo 3D network structures exhibit the highest normalized nanostructure remanence of 0.33 and an increased coercivity to above 200 Oe at 300 K. This combined numerical and experimental investigation aims to shed light on the preparation of FeCo nanostructures with tailorable dimensional order and it opens new avenues for exploring the complex spin textures and coercive behavior of these multi-dimensional nanomagnetic structures.

Iron oxide magnetic aggregates: Aspects of synthesis, computational approaches and applications

Superparamagnetic magnetite nanoparticles have been central to numerous investigations in the past few decades for their use in many applications, such as drug delivery, medical diagnostics, magnetic separation, and material science. However, the properties of single magnetic nanoparticles are sometimes not sufficient to accomplish tasks where a strong magnetic response is required. In light of this, aggregated magnetite nanoparticles have been proposed as an alternative advanced material, which may expand and combine some of the advantages of single magnetic nanoparticles, including superparamagnetism, with an enhanced magnetic moment and increased colloidal stability. This review comprehensively discusses the current literature on aggregates made of magnetic iron oxide nanoparticles. This review is divided into three sections. First, the current synthetic strategies for magnetite nanoparticle aggregates are discussed, together with the influence of different stabilizers on the primary crystals and the final aggregate size and morphology. The second section is dedicated to computational approaches, such as density functional methods (which permit accurate predictions of electronic and magnetic properties and shed light on the behavior of surfactant molecules on iron oxide surfaces) and molecular dynamics simulations (which provide additional insight into the influence of ligands on the surface chemistry of iron oxide nanocrystals). The last section discusses current and possible future applications of iron oxide magnetic aggregates, including wastewater treatment, water purification, medical applications, and magnetic aggregates for materials displaying structural colors.

Oxidation-State Dynamics and Emerging Patterns in Magnetite

Magnetite is an important mineral with many interesting applications related to its magnetic, electrical, and thermal properties. Typically studied by electronic structure calculations, these methods are unable to capture the complex ion dynamics at relevant temperatures, time, and length scales. We present a hybrid Monte Carlo/molecular dynamics (MC/MD) method based on iron oxidation-state swapping for accurate atomistic modeling of bulk magnetite, magnetite surfaces, and nanoparticles that captures the complex ionic dynamics. By comparing the oxidation-state patterns with those obtained from density functional theory, we confirmed the accuracy of our approach. Lattice distortions leading to the stabilization of excess charges and a critical surface thickness at which the oxidation states transition from ordered to disordered were observed. This simple yet efficient approach paves the way for elucidating aspects of oxidation-state ordering of inverse spinel structures in general and battery materials in particular.

Solvent Effects in Ligand Stripping Behavior of Colloidal Nanoparticles

Inorganic colloidal nanoparticle (NP) properties can be tuned by stripping stabilizing ligands using a poor solvent. However, the mechanism behind ligand stripping is poorly understood, in part because in situ measurements of ligand stripping are challenging at the nanoscale. Here, we investigate ethanol solvent-mediated oleylamine ligand stripping from magnetite (Fe₃O₄) NPs in different compositions of ethanol/hexane mixtures using atomistic molecular dynamics (MD) simulations and thermogravimetric analysis (TGA). Our study elucidates a complex interplay of ethanol interactions with system components and indicates the existence of a threshold concentration of ∼34 vol % ethanol, above which ligand stripping saturates. Moreover, hydrogen bonding between ethanol and stripped ligands inhibits subsequent readsorption of the ligands on the NP surface. A proposed modification of the Langmuir isotherm explains the role of the enthalpy of mixing of the ligands and solvents on the ligand stripping mechanism. A good agreement between the MD predictions and TGA measurements of ligand stripping from Fe₃O₄ NPs validates the simulation observations. Our findings demonstrate that the ligand coverage of NPs can be controlled by using a poor solvent below the threshold concentration and highlight the importance of ligand-solvent interactions that modulate the properties of colloidal NPs. The study also provides an approach for a detailed in silico study of ligand stripping and exchange from colloidal NPs that are crucial for applications of NPs spanning self-assembly, optoelectronics, nanomedicine, and catalysis.

Self-Assembly of Magnetic Nanochains in an Intrinsic Magnetic Dipole Force-Dominated Regime

Magnetic nanoparticle chains offer the anisotropic magnetic properties that are often desirable for micro- and nanoscale systems; however, to date, large-scale fabrication of these nanochains is limited by the need for an external magnetic field during the synthesis. In this work, the unique self-assembly of nanoparticles into chains as a result of their intrinsic dipolar interactions only is examined. In particular, it is shown that in a high concentration reaction regime, the dipole-dipole coupling between two neighboring magnetic iron cobalt (FeCo) nanocubes, was significantly strengthened due to small separation between particles and their high magnetic moments. This dipole-dipole interaction enables the independent alignment and synthesis of magnetic FeCo nanochains without the assistance of any templates, surfactants, or even external magnetic field. Furthermore, the precursor concentration ([M] = 0.016, 0.021, 0.032, 0.048, 0.064, and 0.096 m) that dictates the degree of dipole interaction is examined-a property dependent on particle size and inter-particle distance. By varying the spinner speed, it is demonstrated that the balance between magnetic dipole coupling and fluid dynamics can be used to understand the self-assembly process and control the final structural topology from that of dimers to linear chains (with aspect ratio >10:1) and even to branched networks. Simulations unveil the magnetic and fluid force landscapes that determine the individual nanoparticle interactions and provide a general insight into predicting the resulting nanochain morphology. This work uncovers the enormous potential of an intrinsic magnetic dipole-induced assembly, which is expected to open new doors for efficient fabrication of 1D magnetic materials, and the potential for more complex assemblies with further studies.

Simultaneous Enhancement of Magnetothermal and Photothermal Responses by Zn, Co Co-Doped Ferrite Nanoparticles

Reducing nanoparticle (NP) dosage for hyperthermia therapy has remained a great challenge. In this work, efficiencies of alternating current (AC) magnetic field and near-infrared (NIR) heating are simultaneously enhanced by Zn and Co co-doping of magnetite NPs. The optimum magnetic anisotropy for maximized loss power under each magnetic field is achieved by tuning the doping concentration. The specific loss power of Zn_0.3 Co_0.08 Fe_2.62 O₄ @SiO₂ NPs reaches 2428 W g^-1 under an AC field of 27 kA m^-1 at 430 kHz; 12 296 W g^-1 under NIR laser irradiation at 808 nm and 2.5 W cm^-2 ; and an unprecedented value of 14 724 W g^-1 under dual mode. These values far exceed what has been achieved previously in iron oxide NPs. Ex vivo experiments on sacrificial mice show that while the NP dosage is substantially reduced to that used for magnetic resonance imaging, the surface body temperature of the mice reaches 50 °C after exposure to both AC field and laser irradiation under field parameters and laser intensity below safety limits. This nanoplatform is thus promising for multi-modal local hyperthermia therapy.

Magneto-Mechanical Approach in Biomedicine: Benefits, Challenges, and Future Perspectives

The magneto-mechanical approach is a powerful technique used in many different applications in biomedicine, including remote control enzyme activity, cell receptors, cancer-selective treatments, mechanically-activated drug releases, etc. This approach is based on the use of a combination of magnetic nanoparticles and external magnetic fields that have led to the movement of such nanoparticles with torques and forces (enough to change the conformation of biomolecules or even break weak chemical bonds). However, despite many theoretical and experimental works on this topic, it is difficult to predict the magneto-mechanical effects in each particular case, while the important results are scattered and often cannot be translated to other experiments. The main reason is that the magneto-mechanical effect is extremely sensitive to changes in any parameter of magnetic nanoparticles and the environment and changes in the parameters of the applied magnetic field. Thus, in this review, we (1) summarize and propose a simplified theoretical explanation of the main factors affecting the efficiency of the magneto-mechanical approach; (2) discuss the nature of the MNP-mediated mechanical forces and their order of magnitude; (3) show some of the main applications of the magneto-mechanical approach in the control over the properties of biological systems.