Microscopic Model Research Articles

Theoretical Study of Co-Doping Effects with Different Ions on the Multiferroic Properties of BiFeO3 Nanoparticles.

Using a microscopic model and the Green's function theory, the size and co-doping effects on the multiferroic and optical (band gap) properties of BiFeO3 (BFO) nanoparticles are investigated. The magnetization increases, whereas the band gap energy decreases with decreasing nanoparticle size. The substitution with Co/Mn, Nd/Sm, Ce/Ni, and Cd/Ni is discussed and explained on a microscopic level. By the ion co-doping appear different strains due to the difference between the doping and host ionic radii, which leads to changes in the exchange interaction constants for tuning all properties. It is observed that by co-doping with Nd/Sm at the Bi site or with Co/Mn at the Fe site, the multiferroic properties are larger than those by doping with one ion. Moreover, by doping with Ni, the multiferroic properties are reduced. But by adding another ion (for example Ce or Cd), an increase in these properties is obtained. This shows the advantages of the co-doping, its flexibility, and its greater possibility of tuning the multiferroic properties compared to single ion substitution. The band gap energy decreases for all co-dopants. The polarization increases with increasing magnetic field. This is evidence of magnetoelectric coupling, which is enhanced by co-doping with Co/Mn. The observed theoretical results are in good qualitative agreement with the existing experimental data.

Microstructure forming mechanism of inconel 625 alloy fabricated by laser/ultra-high (UHF) induction hybrid deposition method

To reveal the microstructure forming mechanism of laser/ultra-high frequency (UHF) induction deposition, this paper developed a microscopic phase-field (PF) model to numerically investigate dendrite growth during solidification. The macroscopic model of molten pool evolution is adopted to provide the solidification conditions for the microscopic PF model. The dendrite growth during laser deposition is simulated to evaluate the effect of UHF induction heat on the dendrite growth. Results show that because of the high temperature gradient and cooling rate, the PDAS of laser-UHF induction hybrid deposited layer is less than that of the laser deposited layer. The UHF induction heat also leads to a high flow velocity of the molten metal during laser-UHF induction hybrid deposition. The high flow velocity contributes to the decrease in PDAS by inhibiting the interdendritic enrichment of solute. During laser-UHF induction hybrid deposition, a higher solute gradient is present in the tip region of dendrite arm, leading to a faster dendrite growth rate. The UHF induction heat also increases the solute distribution coefficient during deposition, which further inhibits the element segregation. Under the action of UHF induction heat, a low interdendritic solute gradient and an evenly distributed solute can be obtained, thus helping increase interdendritic undercooling degrees and decreasing the PDAS. The simulated PDAS and solute distribution have good consistency with the experimental results. The spectral analysis of EDS line detection indicates that the laser-UHF induction hybrid deposited layer has a more refined microstructure and weaker element segregation than the laser deposited layer does.

Simulation Optimization of Station-Level Control of Large-Scale Passenger Flow Based on Queueing Network and Surrogate Model

Urban rail transit encounters supply–demand contradictions during peak hours, seriously affecting passenger experience. Therefore, it is necessary to explore and optimize passenger-flow control strategies for urban rail transit stations during peak hours. However, current research mostly focuses on passenger-flow control at the network level, and there is insufficient exploration of specific operational strategies at the station level. At the same time, the microscopic simulation model for passenger-flow control at the station level faces the challenge of balancing efficiency and accuracy. This paper presents a simulation optimization approach to optimize the station-level passenger-flow controlling measures, based on a queueing network and surrogate model, aiming to improve throughput, minimize congestion, and enhance passenger experience. The first stage of the method modeled the urban railway station using queueing network theory and multi-agent theory, and then built a mesoscale simulation model that was based on an urban railway station. In the second stage, a passenger flow management and control model for ingress flow was established by combining the Kriging model with a queuing network model, and the particle swarm optimization algorithm was used to solve the model. On this basis, a simulation optimization method for station passenger-flow control was established. Finally, we conducted an example analysis of Zhongguancun Station on the Beijing subway. By comparing the simulation results before and after control, as well as comparing the optimal control scheme obtained by this method with the results of other control schemes, the results showed that the simulation optimization method proposed in this paper can propose an optimal passenger-flow control scheme. By using this method, stations can significantly enhance sustainability. For example, the method not only saves human resources but also effectively avoids or reduces congestion, boosting passenger travel efficiency and safety. By minimizing wait times, these methods lower energy consumption and support the sustainable development of public transportation systems, contributing to more sustainable urban environments.

Advances in terminal management: simulation of vehicle traffic in container terminals

AbstractControlling and managing traffic flows on internal roads in container terminals are crucial in achieving expected productivity levels and reducing negative externalities caused by congestion inside and outside the terminal areas. This paper proposes a simulation approach which terminal operators can use as a decision-support tool to assess the effects of their management strategies and improve terminal performance, resilience, and sustainability. A microscopic traffic simulation approach models key operations of a typical container terminal affecting road traffic flows. In particular, to estimate quantitative indicators, an import truck process is reproduced, considering the overlapping of the external truck and internal trailer flows. To measure environmental impacts, the model is extended with an instantaneous emissions model linked directly to the step-by-step traffic data. The proposed method is tested on a sector of the PSA Genova Pra’, the main Italian container gateway terminal. Performance indicators related to the terminal’s efficiency and sustainability are estimated, to compare alternative scenarios considering possible operational configurations and disturbance events, such as the closure of a part of the yard. By focusing on the interactions between vehicle flows and terminal equipment operations, this approach offers a new perspective on terminal operations, oriented both towards container terminal operators and stakeholders, such as road hauliers.

The influence of stochastic interface defects on the effective thermal conductivity of fiber-reinforced composites

In this paper, a novel microscopic modeling strategy is proposed to investigate the effective thermal conductivity of composites with consideration of stochastic interface defects. To this end, the subdomain boundary element method combined with asymptotic homogenization is proposed to effectively solve the thermal conduction problem. In order to accurately capture the heat flux on the boundary and the internal region in the representative volume element (RVE), a parameterized sub-cell is constructed to discretize the RVE. On this basis, the influence of stochastic interface defects on the thermal conductivity of composites is investigated by utilizing the Monte Carlo method. Specifically, the effect of the location, length, thickness, and area of the interface defects on the thermal conductivity is investigated. A proportional decrease in the transverse thermal conductivity coefficient is found for interface defect areas ranging from 1% to 10%.

Damage mechanism of rock induced by microcrack evolution: A multi-dimensional perspective

This paper investigated the multi-dimensional and multi-scale damage mechanisms of rocks employing Discrete Element Method (DEM) numerical tests, macroscopic damage models, microscopic damage models, and Acoustic Emission (AE) tests. The study analyzed the correlation between the number of microcracks and AE accumulative ring-down count, established a macroscopic damage evolution equation representing rock volume strain, and explored the mechanisms of microscopic damage evolution. The impact of confining pressure and initial microcracks on rock damage characteristics, the relationship between crack volume strain and macroscopic damage evolution, and the effects of different crack types on microscopic damage evolution were discussed. Key findings include: 1) The DEM incorporating gapped contacts can effectively assess the impact of initial microcrack volume on compaction deformation. Concurrently, the consistency observed between the number of microcracks in DEM and the AE accumulative ring-down count aptly characterizes the failure trend. 2) Macroscopic damage is quantitatively derivable through microcrack enumeration, with the noteworthy observation that microcracks undergo substantial development preceding the volumetric expansion of the rock. Consequently, the evolution of macroscopic damage can be aptly described as a piecewise exponential function relative to rock volume strain. 3) Microcracks manifest in two forms: tension and shear, and the evolution of microscopic damage is intricately linked to the type of microcracks, thus prompting a comprehensive consideration of the microscopic damage induced by different microcrack types. This multi-dimensional exploration enhances our understanding of the dynamic processes underlying rock damage at both macroscopic and microscopic levels.

Combination of macroscopic and microscopic crash prediction models with multiple modeling approaches: A highway case study

Road traffic crashes are a global problem and represent a major cause of mortality among children and young people worldwide. Crash prediction models (CPM) play a crucial role in identifying crash-prone areas by predicting the expected number of crashes, thus facilitating the implementation of proactive measures. Previous studies have explored various CPM based on spatial analysis or modeling approaches. Nonetheless, a substantial gap still exists in exploring CPM that simultaneously address the combination of spatial units and modeling approaches, using of heterogeneous data at both the macroscopic and microscopic levels to develop models using Multi-Criteria Decision-Making and Statistical methods. Thus, the objective of this study is to develop multiple CPM using various spatial units of analysis and employing different modeling approaches, combine them, and conduct comparisons to determine the final model that best fits the data. A total of 7 models have been developed: three at the macroscopic level, utilizing Analytic Hierarchy Process (AHP), Negative Binomial (NB), and a combination of both; one at the microscopic level using Geographic Weighted Poisson Regression (GWPR). Additionally, three combined models bring together the previous from both levels, resulting in AHP+GWPR, NB+GWPR, and AHP+NB+GWPR models. These combined and individual models have been compared, and the best-performing has been selected through a validation process. The models were calibrated using data from a case study of a highway located in the northwest of Spain for the period 2016 to 2020. Subsequently, predictions for the year 2021 were made and compared to the actual crash occurrences during that year. The results indicate that the best model is the one that combines the macroscopic and microscopic levels using the approaches AHP+NB+GWPR, which presents a Mean Absolute Deviation (MAD) of 1.55, a Mean Square Error (MSE) of 2.89, does not underestimate any segments and shows a recall of 0.88. The results obtained confirm that the combination of models at the macroscopic and microscopic levels yields the best crashes predictions. This approach offers the advantage that our model, in addition to learning from historical data using statistical methods, also fits to the importance weights assigned by knowledgeable experts on the crashes propensity of the highway in the case study area using the Analytical Hierarchical Process.

Molecular dynamics simulation on the variations in characteristics of aqueous solution with diverse additives: Inspirations for binary ice preparation

Ice slurry, as a novel energy storage medium, possesses the superiority of high energy storage density. The freezing point inhibitors are employed to regulate the supercooling phenomenon of water, while the macroscopic experiments are complicated to elucidate the action mechanism. Consequently, this paper adopts molecular dynamic simulation method to investigate the mean square displacement, radial distribution function, hydrogen bonds types, hydrogen bonds number and length of water at various concentrations of ethanol, NaCl, and SiO2 additives. The results indicate that the average number of hydrogen bonds of the system composed with 600 pure water molecules is 1127.24, and the average length of hydrogen bonds is 2.33 Å. Moreover, the addition of alcoholics and chlorides inhibits the hydrogen bonds between water and water molecules, and promotes the generation of hydrogen bonds, thus weakening the diffusion motion of water molecules. Whereas, it is observed that the addition of nanoparticles leads to agglomeration in pure water system, resulting an increase in the viscosity and a decrease in the diffusion rate of the system. The proposed microscopic model can effectively depict the potential interaction mechanisms of additives and water, which is contributing to develop effective freezing point inhibitors and improve the energy utilization efficiency.

Supramolecular Assemblies in Active Motor-Filament Systems: Micelles, Bilayers, and Foams

Active matter systems evade the constraints of thermal equilibrium, leading to the emergence of intriguing collective behavior. A paradigmatic example is given by motor-filament mixtures, where the motion of motor proteins drives alignment and sliding interactions between filaments and their self-organization into macroscopic structures. After defining a microscopic model for these systems, we derive continuum equations, exhibiting the formation of active supramolecular assemblies such as micelles, bilayers, and foams. The transition between these structures is driven by a branching instability, which destabilizes the orientational order within the micelles, leading to the growth of bilayers at high microtubule densities. Additionally, we identify a fingering instability, modulating the shape of the micelle interface at high motor densities. We study the role of various mechanisms in these two instabilities, such as contractility, active splay, and anchoring, allowing for generalization beyond the system considered here. Published by the American Physical Society 2024

A Prediction Method for City Traffic Noise Based on Traffic Simulation under a Mixed Distribution Probability

Predicting and assessing urban traffic noise is crucial for environmental management. This paper establishes a traffic noise simulation method based on microscopic traffic simulation, utilizing a traffic simulation under a mixed distribution probability combining normal and exponential distributions. This method integrates a single-vehicle noise prediction model to compute the spatial distribution of noise. Comparison with empirical data demonstrates that the proposed model effectively predicts the level of traffic noise. The accuracy of the model is validated through comparison with measured data, showing minimum and maximum errors of 3.60 dB(A) and 4.37 dB(A), respectively. Additionally, the noise spatial results under microscopic traffic models are compared with those under line source models, revealing that the proposed model provides a more detailed and realistic noise spatial distribution. Furthermore, the noise variation patterns between stable and time-varying traffic flows are investigated. Results indicate that noise levels fluctuate under stable traffic flow, whereas under time-varying traffic flow, noise values exhibit a stepped change.

Reclaiming the Lost Conformality in a Non-Hermitian Quantum 5-State Potts Model.

Conformal symmetry, emerging at critical points, can be lost when renormalization group fixed points collide. Recently, it was proposed that after collisions, real fixed points transition into the complex plane, becoming complex fixed points described by complex conformal field theories (CFTs). Although this idea is compelling, directly demonstrating such complex conformal fixed points in microscopic models remains highly demanding. Furthermore, these concrete models are instrumental in unraveling the mysteries of complex CFTs and illuminating a variety of intriguing physical problems, including weakly first-order transitions in statistical mechanics and the conformal window of gauge theories. In this work, we have successfully addressed this complex challenge for the (1+1)-dimensional quantum 5-state Potts model, whose phase transition has long been known to be weakly first order. By adding an additional non-Hermitian interaction, we successfully identify two conjugate critical points located in the complex parameter space, where the lost conformality is restored in a complex manner. Specifically, we unambiguously demonstrate the radial quantization of the complex CFTs and compute the operator spectrum, as well as new operator product expansion coefficients that were previously unknown.

Gold Clusters on Graphene/Graphite—Structure and Energy Landscape

Adopting an advanced microscopic model of the Au–graphite interaction, a systematic study of Au nanoclusters (up to sizes of 11 238 atoms) on graphene and on graphite is carried out to explore their structure and energy landscape. Using parallel tempering molecular dynamics, structural distribution as a function of temperature is calculated in the entire temperature range. Low‐energy structures are identified through a combination of structural optimization and Wulff–Kaischew construction which are then used to explore the energy landscape. The potential energy surface (PES), which is energy as a function of translation and rotation, is calculated for a few Au nanoclusters along specific directions on carbon lattice. Minimum‐energy pathways are identified on the PES indicating a reduced barrier for pathways involving simultaneous rotation and translation. Diffusion simulations of Au233 on graphite show that diffusion mechanism is directly related to the PES, and the information of the cluster pinning events is already present in the PES. Finally, a comparison of various interaction models highlights the importance of reasonably correct Au–C interactions which is crucial for studying the energy landscape and cluster sliding.

Study on Thermophysical Properties and Phase Change Regulation Mechanism of Optically-Controlled Phase Change Materials: Synthesis, Crystal Structure and Molecular Dynamics.

Optically-controlled phase change materials, which are prepared by introducing molecular photoswitches into traditional phase change materials (PCMs), can convert and store solar energy into photochemical enthalpy and phase change enthalpy. However, the thermophysical properties of optically controlled PCMs, which are crucial in the practical, are rarely paid attention to. 4-(phenyldiazenyl)phenyl decanoate (Azo-A-10) is experimentally prepared as an optically-controlled PCMs, whose energy storage density is 210.0 kJ·kg-1, and the trans single crystal structure is obtained. The density, phase transition temperature, thermal conductivity, and other parameters in trans state are measured experimentally. Furthermore, a microscopic model of Azo-A-10 is established, and the thermophysical properties are analyzed based on molecular dynamics. The results show that the microstructure parameter (order parameters) and thermophysical properties (density, radial distribution function, self-diffusion coefficient, phase change temperature, and thermal conductivity) of partially or completely isomerized Azo-A-10, which are challenging to observe in experiments, can be predicted by molecular dynamics simulation. The optically-controlled phase change mechanism can be clarified according to the differences in microstructure. The optically-controlled switchability of thermophysical properties of an optically-controlled PCM is analyzed. This study provides ideas for the improvement, development, and application of optically-controlled PCMs in the future.

Mesoscale modeling of deformations and defects in thin crystalline sheets

We present a mesoscale description of deformations and defects in thin, flexible sheets with crystalline order, tackling the interplay between in-plane elasticity, out-of-plane deformation, as well as dislocation nucleation and motion. Our approach is based on the Phase-Field Crystal (PFC) model, which describes the microscopic atomic density in crystals at diffusive timescales, naturally encoding elasticity and plasticity effects. In its amplitude expansion (APFC), a coarse-grained description of the mechanical properties of crystals is achieved. We introduce surface PFC and surface APFC models in a convenient height-function formulation encoding deformation in the normal direction. This framework is proven consistent with classical aspects of strain-induced buckling, defect nucleation on deformed surfaces, and out-of-plane relaxation near dislocations. In particular, we benchmark and discuss the results of numerical simulations by looking at the continuum limit for buckling under uniaxial compression and at evidence from microscopic models for deformation at defects and defect arrangements, demonstrating the scale-bridging capabilities of the proposed framework. Results concerning the interplay between lattice distortion at dislocations and out-of-plane deformation are also illustrated by looking at the annihilation of dislocation dipoles and systems hosting many dislocations. With the novel formulation proposed here, and its assessment with established approaches, we envision applications to multiscale investigations of crystalline order on deformable surfaces.

(Invited) Probe the Reaction Intermediates on Noble Metal Electrodes during Oer with Vibrational Sum Frequency Spectroscopy

Electrochemical water splitting on noble metal surface is an important reaction of both fundamental and application interest. It is well known that the bottleneck of this reaction is the poor kinetics for oxygen generation from water oxidation. Despite of years study, the mechanisms in terms of the roles of the thin oxides film that formed on the metal surface before/during oxygen evolution are still inexplicit. One of the main reasons is the lack of molecular level information about the oxide thin film structures. In this study, we investigated the electrochemical oxidation of gold and platinum in solutions with different pHs by employing surface specific vibrational sum frequency spectroscopy (VSFS)1-3. By analyzing the potential dependent behaviors of different types of adsorbed species, we could gain molecular level information regarding the structures and formation mechanisms of metal-oxides. The results of this study will provide essential data toward understanding the oxygen evolution mechanism and also suggest strategies for developing better water splitting catalysts. [1]. Zhang, I. Y.; Zwaschka, G.; Wang, Z.; Wolf, M.; Campen, R. K.; Tong, Y., Resolving the chemical identity of H2SO4 derived anions on Pt(111) electrodes: they're sulfate. Physical Chemistry Chemical Physics 2019, 21 (35), 19147-19152.[2]. Zwaschka, G.; Wolf, M.; Campen, R. K.; Tong, Y., A Microscopic Model of the Electrochemical Vibrational Stark Effect: Understanding VSF Spectroscopy of (bi)Sulfate on Pt(111). Surf. Sci. 2018, 678, 78-85.[3]Gong, X.; Campen, R. K.; Tong, Y. Direct Observation of the Potential-Dependent Protonation and Reorientation of 4-(Dimethylamino)pyridine on Gold Electrodes. J. Phys. Chem. C 2023, 127 (33), 16615-16622. DOI: 10.1021/acs.jpcc.3c03038.

Modeling of Lithium-Flow Batteries with Aqueous Electrolyte

Flow batteries with aqueous electrolyte at the cathode are safe, low-cost and ecofriendly energy storage systems. When the aqueous cathode is coupled with a Li-metal anode with organic electrolyte, these batteries have extremely high energy densities (over 4,000 Wh/Kg), which makes them attractive not only for grid applications (where flow batteries are often used) but also in maritime applications such long endurance surface vessel systems and wave gliders [1-4]. In this presentation, we derive the mathematical model for lithium-flow batteries and use this model to predict the performance of the batteries under different discharge conditions, cathode microstructures, water flow velocities, etc. The results are then compared to experimental data already available in the literature. The mathematical model is based on coupling the flow equations (Navier-Stokes) with electrochemical equations for reaction rates and using average microscopic models for the cathode. For instance, Fig. 1 shows the voltage of a flow battery as a function of time for different water velocities in a flow battery simulated by solving the above model. For low water velocities, the water is not able to provide enough oxygen in the cathode and the voltage of the battery collapses after a few seconds. However, as long as the water velocity is above approx. 1.2 cm/s, the battery will have enough oxygen to operate continuously; in this case, the higher the flow of the water, the higher the voltage of the battery in the stationary state will be because of lower overpotential losses. In these simulations, the anode contained Li-metal. The cathode had a length of 1 cm (measured in the direction of water flow) and a thickness of 100 μm. The cell was discharged at a small rate of 0.01 mA/cm2. The incoming water had an oxygen concentration of 5 mg/l (which is equal to the oxygen concentration in seawater) and was pumped through the cathode at different velocities. A detailed derivation of the mathematical model and more simulation results and predictions will be presented at the meeting.

Tuning the ground state of cuprate superconducting thin films by nanofaceted substrates

Anisotropic transport properties have been assessed in a number of cuprate superconductors, providing evidence for a nematic state. We have recently shown that in ultra-thin YBa2Cu3O7−δ films, where nematicity is induced via strain engineering, there is a suppression of charge density wave scattering along the orthorhombic a-axis and a concomitant enhancement of strange metal behavior along the b-axis. Here we develop a microscopic model, that is based on the strong interaction between the substrate facets and the thin film, to account for the unconventional phenomenology. Based on the atomic force microscopy imaging of the substrates’ surface, the model is able to predict the absence (presence) of nematicity and the resulting transport properties in films grown on SrTiO3 (MgO) substrates. Our result paves the way to new tuning capabilities of the ground state of high-temperature superconductors by substrate engineering.

The mechanism of tuning filler orientation degree in composites based on AC electric field assist: from microscopic dynamical model to macroscopic electrical properties

Using the AC electric field to induce the orientation of nonlinear conductive fillers in composites is an effective solution for alleviating electric field distortion in power modules. However, the mechanism by which the electric field affects the filler dynamic characteristics and the composites’ electrical properties remains unclear. In this paper, the correlation between the microscopic dynamic processes of fillers and the macroscopic current amplitude was analyzed. The results show that the current increases rapidly (0 ∼ 173 s) and then slowly (173 ∼ 869 s) at 600 V mm−1, influenced by the rotation and attraction processes of the fillers. This demonstrates that the orientation stops at about 869 s and the filler orientation state is a key factor in determining the dielectric properties. Secondly, the global orientation evaluation index D for the filler network was proposed, which can also derive the minimum time and energy loss required for preparation. Finally, the impact of different filler orientations on the composites’ conductivity was investigated. In the low electric field stress region, with the average carrier jump distance decreasing from 150.23 to 109.71 nm as the D increases from −0.93 to −0.05. On this basis, materials with nonlinear conductivity gradient distribution can be easily prepared. Before optimization, the electric field stress of the power module at the triple point was 35.79 kV. This composite can reduce the value to 15.42 kV, a decrease of 56.9%, while maintaining good electric field uniformity.

Data collection for microscopic modelling of urban parcel transport to and from establishments – empirical insights into city logistics in the region of Karlsruhe, Germany

City logistics plays a central role in supplying and disposing goods for establishments and residents in urban areas. However, the steadily rising demand for transporting goods puts cities under pressure. Hence, municipalities strive for alternative solutions for urban freight transport, especially parcel shipments on the first and last mile. Freight demand models are suitable to evaluate the transport-related effects of such solutions. However, developing those models requires a sufficient amount of data, which, to date, especially for establishments, cannot be covered in its necessary scope and accuracy by publicly available sources. Although parcel shipments to and from establishments make up to 40 % of the overall courier, express, and parcel market, these are often neglected in existing modelling approaches. Hence, in this study, we present a data collection concept for generating highly relevant data for the microscopic modelling of urban freight, i.e., parcel transport focusing on establishments. To reflect transport demand (i.e., establishments that need to have goods shipped) and transport supply (i.e., carriers that provide a transport service), a mixed-method approach is developed comprising complementary components. On the one hand, an online establishment survey is designed aiming to reveal disaggregated transport demand data for the subsequent modelling process. The survey focuses on the delivery and shipment characteristics of goods, such as temporal and spatial demand patterns. On the other hand, expert interviews are conceptualized to identify relevant patterns of transport supply carriers such as courier, express, and parcel service providers and shall further work as secondary data for the modelling process. The approach is applied in the region of Karlsruhe, Germany. It can be shown that the survey is generally suitable for generating freight transport data on a disaggregated level and that the mixed-method approach is capable of mutually validating the data obtained. However, our approach also emphasizes the necessity to conduct an establishment survey as a personal rather than a self-reporting interview, even if the costs are higher.

Molecular dynamics modelling of interacting magnetic nanoparticles for investigating equilibrium and dynamic ensemble properties

Magnetic nanoparticles have the potential to be used in various biomedical applications, including magnetic drug targeting and hyperthermia for cancer treatment. In both cases, precise prediction of the local particle concentration is required to plan a successful therapy, which is a challenging task due to several complex flow phenomena. Computational macroscopic and microscopic models have been developed to support this process, but they have limitations in terms of interactions implementation, micromagnetic dynamics or computational costs. This study aims to develop a model that can represent micromagnetic dynamics and being employed to study equilibrium properties of particle ensembles in viscous media. Therefore, a kinetic Monte Carlo method in combination with Langevin equations is used. So, magnetization dynamics and mechanical motion can be simulated in combination very efficiently. The new model is validated with another model based on the stochastic Landau-Lifshitz-Gilbert equation. Various interaction potentials like Van der Waals, steric and electrostatic interactions are included to study their specific influence on structural properties. Also, methods to control the errors while integrating the equations of motion and using the Ewald method for calculating interaction quantities are implemented. As a validation we studied equilibrium and time dependent properties of non-interacting particle ensembles as well as errors made by the Ewald-method used for interaction quantities calculation. In all studies we found very good agreement of the simulation results with the theoretical predictions. The developed models can now be used for investigating equilibrium and dynamic properties of ferrofluids, or more general for biomedical research for magnetic drug targeting, hyperthermia, or imaging techniques. Furthermore, the new hybrid model can be also used for simulations in the range of milliseconds with reasonable computational effort.