Colloidal Shear-Thickening Fluids Using Variable Functional Star-Shaped Particles: A Molecular Dynamics Study

Complex colloidal fluids, depending on constituent shapes and packing fractions, may have a wide range of shear-thinning and/or shear-thickening behaviors. An interesting way to transition between different types of such behavior is by infusing complex functional particles that can be manufactured using modern techniques such as 3D printing. In this paper, we perform 2D molecular dynamics simulations of such fluids with infused star-shaped functional particles, with a variable leg length and number of legs, as they are infused in a non-interacting fluid. We vary the packing fraction (ϕ) of the system, and for each different system, we apply shear at various strain rates, turning the fluid into a shear-thickened fluid and then, in jammed state, rising the apparent viscosity of the fluid and incipient stresses. We demonstrate the dependence of viscosity on the functional particles’ packing fraction and we show the role of shape and design dependence of the functional particles towards the transition to a shear-thickening fluid.

Reducing Calibration Time in PET Systems Based on Monolithic Crystals

In the past years, the gamma-ray detector designs based on the monolithic crystals have demonstrated to be excellent candidates for the design of high-performance PET systems. The monolithic crystals allow to achieve the intrinsic detector resolutions well below state-of-the-art; to increase packing fraction thus, increasing the system sensitivity; and to improve lesion detectability at the edges of the scanner field of view (FOV) because of their intrinsic depth of interaction (DOI) capabilities. The bottleneck to translate to the clinical PET systems based on a large number of monolithic detectors is eventually the requirement of mechanically complex and time-consuming calibration processes. To mitigate this drawback, several methods have been already proposed, such as using non-physically collimated radioactive sources or implementing the neuronal networks (NN) algorithms trained with simulated data. In this work, we aimed to simplify and fasten a calibration process of the monolithic based systems. The Normal procedure consists of individually acquiring a 11 × 11 22Na source array for all the detectors composing the PET system and obtaining the calibration map for each module using a method based on the Voronoi diagrams. Two reducing time methodologies are presented: (i) TEST1, where the calibration map of one detector is estimated and shared among all others, and (ii) TEST2, where the calibration map is slightly modified for each module as a function of their detector uniformity map. The experimental data from a dedicated prostate PET system was used to compare the standard calibration procedure with both the proposed methods. A greater similarity was exhibited between the TEST2 methodology and the Normal procedure; obtaining spatial resolution variances within 0.1 mm error bars and count rate deviations as small as 0.2%. Moreover, the negligible reconstructed image differences (13% deviation at most in the contrast-to-noise ratio) and almost identical contrast values were reported. Therefore, this proposed method allows us to calibrate the PET systems based on the monolithic crystals reducing the calibration time by approximately 80% compared with the Normal procedure.

Experimental and Numerical Analysis of Torque Properties of Rotary Elastomer Particle Damper considering the Effect of Gap and No Gap between Rotor and Body of the Damper

Particle dampers are devices used to control the vibration of mechanical systems. In this research, prototypes of rotary elastomer particle dampers are experimentally tested considering gap and no gap between shaft and cylinder. There is a gap between the rotor and cylinder in the gap model; particles can move from one chamber to another. There is no space for the particles to move from one chamber to another in the no-gap model. Elastomer particles are soft, and they have different behavior from hard (metallic) particles. Experiments on rotary elastomer particle dampers considering the gap between rotor and cylinder helped investigate the effects of the change in packing fraction, rotational speed, size of elastomers, and the gap between the rotor and the damper body. A numerical simulation approach based on the discrete element analysis method is used to perform a quantitative and qualitative analysis of the rotary elastomer particle damper. The simulation results are in great agreement with the experiment results. It is observed that packing fraction, rotational speed, size of elastomer particles, and the gap between rotor and cylinder play a vital role in producing higher damper torque.

TEMPLATE-SHAPE DEPENDENCE ASSEMBLY OF JANUS NANOPARTICLES AT WATER-OIL INTERFACE

In this work, we investigated the crystal formation of anisotropic nanoparticles, namely Janus particles, at the water-oil interface using the dissipative particle dynamics simulation method. By considering three different interface templates, including planar, droplet, and rod, we observe an increase of the disorder-order transition packing fraction with increasing the curvature radius of the templates. Furthermore, the nanoparticles in the planar template assemble into a hexagonal lattice, while for the two remaining templates they aggregate into colloidsome-like structures.

L attice V ibrational C haracteristics , Crystal Structure s , and D ielectric P roperties of Li Mn PO 4 Microwave Dielectric Ceramics as a Function of Sintering Temperature

LiMnPO4 (LMP) microwave dielectric ceramics were manufactured at different temperatures via a standard solid-state reaction method, and the LMP ceramic sintered at 750 °C displayed dielectric properties of εr = 7.82, Q × f = 29,189 (f = 12.7 GHz). The lattice vibrational characteristics of LMP ceramics were studied utilizing both infrared reflection and Raman scattering spectroscopy to clarify the basic principle of the dielectric response. The intrinsic properties that were fitted and simulated based on the infrared spectra agreed with the measured property values. The low-frequency vibrational modes contributed more to the dielectric properties than the high-frequency modes. Upon increasing the temperature, the permittivity was positively correlated with the bond length but showed the opposite trend of the Raman shift of mode 9 Ag(υ1). The Q × f value was positively correlated with the packing fraction but negatively correlated with the FWHM of mode 10 Ag(υ3). Thus, the structure-property relationships of LMP ceramics were established as a function of sintering temperature.

Colloidal Shear Thickening Fluids Using Variable Shaped Functional Star Particles: A Molecular Dynamics Study

Complex colloidal fluids, depending on particulates’ shapes and packing fractions, may have a wide range of shear thinning and thickening behaviors. A particular interesting way to transition between different types of such behavior is by infusing functional complex particles that can be manufactured using modern techicques such as 3D printing. In this paper, we display 2D molecular dynamics simulations of such fluids with infused star-shaped functional particles, with variable leg length and number of legs, as they are infused in a non-interacting, coarse-grained fluid. We vary the packing fraction (ϕ) of the system, and for each different system we apply shear with various strain rate that turns the fluid into a jammed state and rise the apparent viscosity of fluid. We demonstrate the dependence of viscosity with the particles’ packing fraction. We show the role of shape and design dependence of the functional particles towards the transition to a shear thickening fluid .

Stiffening Effect of Fillers Based on Rheology and Micromechanics Models

The aggregate in an asphalt mixture is coated with mastic consisting of bitumen (dilute phase) and filler (particulates phase). The interaction of bitumen and filler and packing of filler plays an important role in the properties of mastics. The micromechanics models from composite rheology can be used to predict the stiffening effect of a suspension. In this research, the stiffening effect of fillers was investigated based on the rheology of mastic. The frequency sweep tests in a dynamic shear rheometer at different temperatures were performed within a linear viscoelastic range to construct the master curves. The volume fractions were expressed as compositional volumes of filler in mastic. The particle shape and surface texture are determined through microscopy. We used six micromechanics-based models to predict the stiffening potential of fillers in mastics. The models include Maron–Pierce, Lewis Nielsen, Mooney, Krieger–Dougherty, Chong, Robinson, and Hashin Models. The results show that the same volume content of filler has a different effective volume. The fillers increase the stiffening effect of the composite, especially at high temperatures. The behaviour of fillers with similar effective volume and packing is identical. The filler type affects the stiffening of mastics. Micromechanics modelling results show that most models show an accurate stiffening effect at lower concentrations with the exception of the Chong Model. The Maron–Pierce Model under-estimates the stiffening potential for granite mastic at higher concentrations beyond the 30% filler content fraction. The value of maximum packing fraction (ϕm) and Einstien coefficient (KE) in the Mooney model are significantly different from other models for limestone and granite, respectively. The line of equality graph shows good agreement of measured and predicted stiffness. It is difficult to precisely model the mastic data with any single model due to the presence of complex stiffening effects beyond volume filling.

High-Throughput Computation of New Carbon Allotropes with Diverse Hybridization and Ultrahigh Hardness

The discovery of new carbon allotropes with different building blocks and crystal symmetries has long been of great interest to broad materials science fields. Herein, we report several hundred new carbon allotropes predicted by the state-of-the-art RG2 code and first-principles calculations. The types of new carbon allotropes that were identified in this work span pure sp2, hybrid sp2/sp3, and pure sp3 C–C bonding. All structures were globally optimized at the first-principles level. The thermodynamic stability of some selected carbon allotropes was further validated by computing their phonon dispersions. The predicted carbon allotropes possess a broad range of Vickers’ hardness. This wide range of Vickers’ hardness is explained in detail in terms of both atomic descriptors such as density, volume per atom, packing fraction, and local potential energy throughout the unit cell, and global descriptors such as elastic modulus, shear modulus, and bulk modulus, universal anisotropy, Pugh’s ratio, and Poisson’s ratio. For the first time, we found strong correlation between Vickers’ hardness and average local potentials in the unit cell. This work provides deep insight into the identification of novel carbon materials with high Vickers’ hardness for modern applications in which ultrahigh hardness is desired. Moreover, the local potential averaged over the entire unit cell of an atomic structure, an easy-to-evaluate atomic descriptor, could serve as a new atomic descriptor for efficient screening of the mechanical properties of unexplored structures in future high-throughput computing and artificial-intelligence-accelerated materials discovery methods.