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Chloride ion diffusion properties are important factors that affect the durability of cementitious materials. Researchers have conducted much exploration in this field, both experimentally and theoretically. Numerical simulation techniques have been greatly improved as theoretical methods and testing techniques have been updated. Researchers have modeled cement particles mostly as circular shapes, simulated the diffusion of chloride ions, and derived chloride ion diffusion coefficients in two-dimensional models. In this paper, a three-dimensional random walk method based on Brownian motion is employed to evaluate the chloride ion diffusivity of cement paste with the use of numerical simulation techniques. Unlike previous simplified two-dimensional or three-dimensional models with restricted walks, this is a true three-dimensional simulation technique that can visually represent the cement hydration process and the diffusion behavior of chloride ions in cement paste. During the simulation, the cement particles were reduced to spheres, which were randomly distributed in a simulation cell with periodic boundary conditions. Brownian particles were then dropped into the cell and permanently captured if their initial position in the gel fell. Otherwise, a sphere tangential to the nearest cement particle was constructed, with the initial position as the center. Then, the Brownian particles randomly jumped to the surface of this sphere. The process was repeated to derive the average arrival time. In addition, the diffusion coefficient of chloride ions was deduced. The effectiveness of the method was also tentatively confirmed by the experimental data. [ABSTRACT FROM AUTHOR]

In the last years, a few experiments in the fields of biological and soft matter physics in colloidal suspensions have reported "normal diffusion" with a Laplacian probability distribution in the particle's displacements (i.e., Brownian yet non-Gaussian diffusion). To model this behavior, different stochastic and microscopic models have been proposed, with the former introducing new random elements that incorporate our lack of information about the media and the latter describing a limited number of interesting physical scenarios. This incentivizes the search of a more thorough understanding of how the media interacts with itself and with the particle being diffused in Brownian yet non-Gaussian diffusion. For this reason, a comprehensive mathematical model to explain Brownian yet non-Gaussian diffusion that includes weak molecular interactions is proposed in this paper. Based on the theory of interfaces by De Gennes and Langevin dynamics, it is shown that long-range interactions in a weakly interacting fluid at shorter time scales leads to a Laplacian probability distribution in the radial particle's displacements. Further, it is shown that a phase separation can explain a high diffusivity and causes this Laplacian distribution to evolve towards a Gaussian via a transition probability in the interval of time as it was observed in experiments. To verify these model predictions, the experimental data of the Brownian motion of colloidal beads on phospholipid bilayer by Wang et al. are used and compared with the results of the theory. This comparison suggests that the proposed model is able to explain qualitatively and quantitatively the Brownian yet non-Gaussian diffusion. [ABSTRACT FROM AUTHOR]

Rocket kerosene plays an important role in the regenerative cooling process of rocket thrust chambers. Its thermal conductivity determines the cooling efficiency and the tendency to coke in rocket kerosene engines. In this paper, graphene nanoplatelets (GNPs) were introduced into rocket kerosene to improve its thermal conductivity. Molecular dynamics simulation was used to investigate the thermal conductivity of the composite system and its underlying thermal conductivity mechanism. Firstly, by studying the effect of the mass fraction of GNPs, it was found that, when the graphene mass fraction increases from 1.14% to 6.49%, the thermal conductivity of the composite system increases from 4.26% to 17.83%, which can be explained by the percolation theory. Secondly, the influence of the size of GNPs on the thermal conductivity of the composite system was studied. Basically, the thermal conductivity was found to increase by increasing the aspect ratio of GNPs, indicating that GNPs with a higher aspect ratio are more conducive to improving the thermal conductivity of rocket kerosene. By carefully analyzing the effect of the size of GNPs on thermal conductivity, it was concluded that the thermal conduction enhancement by adding GNPs is determined by the combined effect of the percolation theory and the Brownian motion. The results of the temperature effect study showed that the ratio of thermal conductivity to rocket kerosene increased from 1.16 to 1.26 and from 1.07 to 1.11 for the composite systems, with graphene sizes of 41.18 Å × 64.00 Å and 24.14 Å × 17.22 Å in the temperature range of 293 K to 343 K, respectively. It is further proved that the Brownian motion of GNPs has a non-negligible effect on the thermal conductivity of the composite system. This work provides microscopic insights into the thermal conduction mechanism of GNPs in nanofluids and will offer practical guidance for improving the thermal conductivity of rocket kerosene. [ABSTRACT FROM AUTHOR]

Principal component analysis (PCA) as a machine-learning technique could serve in disease diagnosis and prognosis by evaluating the dynamic morphological features of exosomes via Cryo-TEM-imaging. This hypothesis was investigated after the crude isolation of similarly featured exosomes derived from the extracellular vehicles (EVs) of immature dendritic cells (IDCs) JAWSII. It is possible to identify functional molecular groups by FTIR, but the unique physical and morphological characteristics of exosomes can only be revealed by specialized imaging techniques such as cryo-TEM. On the other hand, PCA has the ability to examine the morphological features of each of these IDC-derived exosomes by considering software parameters such as various membrane projections and differences in Gaussians, Hessian, hue, and class to assess the 3D orientation, shape, size, and brightness of the isolated IDC-derived exosome structures. In addition, Brownian motions from nanoparticle tracking analysis of EV IDC-derived exosomes were also compared with EV IDC-derived exosome images collected by scanning electron microscopy and confocal microscopy. Sodium-Dodecyl-Sulphate-Polyacrylamide-Gel-Electrophoresis (SDS-PAGE) was performed to separate the protein content of the crude isolates showing that no considerable protein contamination occurred during the crude isolation technique of IDC-derived-exosomes. This is an important finding because no additional purification of these exosomes is required, making PCA analysis both valuable and novel. [ABSTRACT FROM AUTHOR]

The filling of channels in porous media with particles of a material can be interpreted in a first approximation as a packing of spheres in cylindrical recipients. Numerous studies on micro- and nanoscopic scales show that they are, as a rule, not ideal cylinders. In this paper, the channels, which have an irregular shape and a circular cross-section, as well as the packing algorithms are investigated. Five patterns of channel shapes are detected to represent any irregular porous structures. A novel heuristic packing algorithm for monosized spheres and different irregularities is proposed. It begins with an initial configuration based on an fcc unit cell and the subsequent densification of the obtained structure by shaking and gravity procedures. A verification of the algorithm was carried out for nine sinusoidal axisymmetric channels with different Dmin/Dmax ratio by MATLAB® simulations, reaching a packing fraction of at least 0.67 (for sphere diameters of 5%Dmin or less), superior to a random close packing density. The maximum packing fraction was 73.01% for a channel with a ratio of Dmin/Dmax = 0.1 and a sphere size of 5%Dmin. For sphere diameters of 50%Dmin or larger, it was possible to increase the packing factor after applying shaking and gravity movements. [ABSTRACT FROM AUTHOR]

Colloidal particles in nematic liquid crystals show a beautiful variety of complex phenomena with promising applications. Their dynamical behaviour is determined by topology and interactions with the liquid crystal and external fields. Here, a nematic magnetic nanocapsule reoriented periodically by time-varying magnetic fields is studied using numerical simulations. The approach combines Molecular Dynamics to resolve solute–solvent interactions and Nematic Multiparticle Collision Dynamics to incorporate nematohydrodynamic fields and fluctuations. A Saturn ring defect resulting from homeotropic anchoring conditions surrounds the capsule and rotates together with it. Magnetically induced rotations of the capsule can produce transformations of this topological defect, which changes from a disclination curve to a defect structure extending over the surface of the capsule. Transformations occur for large magnetic fields. At moderate fields, elastic torques prevent changes of the topological defect by tilting the capsule out from the rotation plane of the magnetic field. [ABSTRACT FROM AUTHOR]

In mesoscopic scale, concrete is regarded as a heterogeneous three-phase material composed of mortar, aggregate and interfacial transition zone (ITZ). The effect of mesoscopic structure on the mechanical behaviors of concrete should be paid more attention. The fractal characteristics of aggregate were calculated, then the geometric models of aggregate were reconstructed by using fractal Brownian motion. Based on the random distribution of aggregates, the concrete mesoscopic structure model was established. And the numerical model was generated by using grid mapping technology. The dynamic compression experiments of concrete under Split Hopkinson Pressure Bar (SHPB) loading verify the reliability and validity of the mesoscopic structural model and the parameters of the constitutive model. Based on these, a numerical study of concrete under dynamic splitting is carried out. By changing the parameters of the constitutive model, the effects of tensile strengths of aggregate, mortar and ITZ on the dynamic tensile strength of concrete are discussed. The results show that the dynamic failure of specimen usually occurs at the interfacial transition zone, then extends to the mortar, and the aggregates rarely fail. However, the increase of strain rate intensifies this process. When the strain rate increases from 72.93 s−1 to 186.51 s−1, a large number of aggregate elements are deleted due to reaching the failure threshold. The variation of tensile strengths of each phase component have the same effect on the dynamic tensile strength and energy of concrete. The dynamic tensile strength and energy of concrete are most affected by the tensile strength of mortar, following by the ITZ, but the tensile strength of aggregate has almost no effect. [ABSTRACT FROM AUTHOR]