Dynamic Properties Research Articles

Twin and phase boundaries synergistic effect on multiscale dynamic fracture in Ni-based deformed superalloy

A multi-scale model of dynamic impact fracture of Ni-based deformed superalloy was proposed based on molecular dynamics and finite element methods, and verified by experiments to reveal the synergistic effect of twin and phase boundaries on dynamic fracture properties and behavior from nanoscale to macroscale. The results show that the synergistic effect of twin and phase boundaries can effectively suppress the unfavorable brittle propagation in the nanoscale owing to the dispersed distribution of strengthening phase-induced reduction of the stress concentration on the twin boundary. The nucleation and emission of perfect dislocations, Shockley dislocations, and Frank dislocations promote ductile propagation, while the pile-up of stair-rod dislocations induced stress concentration leads to brittle propagation. In the macroscale, the synergistic effect of twin and phase boundaries can effectively inhibit the loss of dynamic fracture toughness, and impede crack initiation and crack propagation through the reduction of Mises stress concentration and the decrease of maximum equivalent strain caused by the dispersed Ni3Al precipitates. The physical mechanism of the multi-scale crack propagation and fracture, and the influence law of dynamic fracture toughness of Ni-based deformed superalloy, can provide a guide to the failure prediction, protection, and development of aviation turbine blades.

Elastic, Electronic, Dynamic and Thermodynamic Properties of YbPdH3

A comprehensive computational investigation has been carried out for YbPdH3 via first principles calculations for the first time. Structural, electronic and thermodynamic properties are obtained. The obtained lattice constant of YbPdH3 is in a good agreement with the existing literature. Subsequently, the elastic constants are obtained and used to compute several parameters such as anisotropy, hardness, Cauchy pressure, shear and Young modulus, machinability index and Poisson’s ratio. According to Born stability criteria, YbPdH3 is mechanically stable material. Cauchy pressure and Poisson’s ratio indicates ductile nature. The anisotropy factor indicates anisotropic nature almost in every direction for Young modulus, shear modulus, linear compressibility and Poisson’s ratio. The machinability index (B/C44) is found to be 2.88 whereas Vickers hardness of YbPdH3 is computed via Chen’s model as 2.965. The electronic band structure of YbPdH3 demonstrates metallic characteristics since there is no band gap between valence and conduction band. The thermodynamic properties such as Debye temperature, Debye vibrational energy, vibrational free energy, entropy, heat capacity and melting temperature of YbPdH3 are also obtained. The heat capacity seems to reach its Dulong-Petit limit at about 300 K.

Study on Surface Active Bubble Dynamics Properties under Strong Low-Frequency Sound Waves

Study on Surface Active Bubble Dynamics Properties under Strong Low-Frequency Sound Waves

Synergistic enhancement of hydrophobic dental adhesives: autonomous strengthening, polymerization kinetics, and hydrolytic resistance

The leading cause of composite restoration failure is recurrent marginal decay. The margin between the composite and tooth is initially sealed by a low-viscosity adhesive, but chemical, physical, and mechanical stresses work synergistically and simultaneously to degrade the adhesive, destroying the interfacial seal and providing an ideal environment for bacteria to proliferate. Our group has been developing self-strengthening adhesives with improved chemical and mechanical characteristics. This paper reports a self-strengthening adhesive formulation that resists hydrolysis-mediated degradation by providing intrinsic reinforcement of the polymer network through synergistic stimulation of free-radical polymerization, sol-gel reaction, and hydrophobicity. Hydrophobic resin formulation (NE1) was developed using HEMA/BisGMA 28/55w/w and 15 wt% MPS. Control (NC1) contained HEMA/BisGMA 28/55 w/w and 15 wt% MES. The polymerization kinetics, water sorption, leachates, and dynamic mechanical properties of the resin samples were investigated. The NC1 and NE1 samples showed comparable polymerization kinetics, degree of conversion and water sorption. In contrast, NC1 showed significantly higher levels of HEMA and BisGMA leachate, indicating faster degradation in ethanol. At day 3, cumulative HEMA leachate for NC1 was tenfold greater than NE1 (p < 0.05). Dynamic mechanical properties were measured at 37 and 70°C in both dry and wet conditions. Under dry conditions, the storage moduli of NC1 and NE1 were comparable and the glass transition temperature (Tg) of NC1 was statistically significant lower (p < 0.001) than NE1. Under wet conditions, the storage modulus of NC1 was lower than NE1 and at 70°C there is a threefold difference in storage modulus. At this temperature and under wet conditions, the storage modulus of NC1 is statistically significantly lower (p < 0.001) than NE1. The results indicated that in the wet environment, NE1 provided lower chain mobility, higher crosslink density, and more hydrogen bonds. The newly formulated methacrylate-based adhesive capitalizes on free-radical polymerization, sol-gel reactions, and hydrophobicity to provide enhanced mechanical properties at elevated temperatures in wet environments and hydrolytic stability under aggressive aging conditions.

Molecular dynamics simulations of choline chloride and ascorbic acid deep eutectic solvents: Investigation of structural and dynamics properties

Deep eutectic solvents (DESs) composed of choline chloride (ChCl) and ascorbic acid (AA) were investigated using the molecular dynamics (MD) simulations. The analyses of the configuration, radial distribution function (RDFs), coordination number, spatial distribution function (SDFs), interaction energies, hydrogen bond number, and self-diffusion coefficient of the ChCl/AA binary systems of different concentrations showed that the stability of the hydrogen bond network and the mutual attraction between systems were the strongest at the experimental eutectic concentration (molar ratio of 2:1). In our simulated temperature range from 303.15 to 353.15 K, the hydrogen bonding network of ChCl/AA DES does not undergo considerable alterations, indicating that its stability was insensitive to temperature. In addition, the influence of the water content on the ChCl/AA DES system was further investigated. The simulated results revealed that the water molecules could disrupt the formation of the hydrogen bonding network by occupyin positions that are essential for the formation of hydrogen bonds within the DES system.

An immuno-epidemiological model with waning immunity after infection or vaccination

In epidemics, waning immunity is common after infection or vaccination of individuals. Immunity levels are highly heterogeneous and dynamic. This work presents an immuno-epidemiological model that captures the fundamental dynamic features of immunity acquisition and wane after infection or vaccination and analyzes mathematically its dynamical properties. The model consists of a system of first order partial differential equations, involving nonlinear integral terms and different transfer velocities. Structurally, the equation may be interpreted as a Fokker-Planck equation for a piecewise deterministic process. However, unlike the usual models, our equation involves nonlocal effects, representing the infectivity of the whole environment. This, together with the presence of different transfer velocities, makes the proved existence of a solution novel and nontrivial. In addition, the asymptotic behavior of the model is analyzed based on the obtained qualitative properties of the solution. An optimal control problem with objective function including the total number of deaths and costs of vaccination is explored. Numerical results describe the dynamic relationship between contact rates and optimal solutions. The approach can contribute to the understanding of the dynamics of immune responses at population level and may guide public health policies.

Enhanced interlaminar structure and dynamic mechanical properties of Tectona grandis fiber (TGF)/polypropylene fiber (PPF)/carbon nanotube (CNT) nano composite prepared solid dipping coating process

Abstract The interlaminar structure and dynamic mechanical properties of Tectona grandis fiber (TGF), polypropylene fiber (PPF), and carbon nanotube (CNT) nano composite were investigated in the current study. In order to improve the mechanical characteristics and microstructure, the present investigations used T. grandis fiber and polypropylene fiber (inorganic–organic) materials mixed with nano composite and epoxy resin. Strong bonding strength and high wear resistance were created by the silane characteristics during the coating process for the outer surface layers. Since CNT nanomaterials were directly reflected onto the outer surface, the microstructure analyses amply demonstrated that hexagonal lattice structure and crystallisation development were detected in the inner surface layer. In order to increase high stiffness and bonding strength, storage modulus and loss modulus values were applied to all composite materials, and the TGF/PPF/CNT composite materials’ hardness value was developed at 112 HV. The tensile strength of TG/PP composite was 46.7 MPa, while that of TGF/PPF/CNT composite was 57.4 MPa. Studies on wear resistance showed unequivocally that the TGF/PPF/CNT composite reduced wear and friction.

Revolutionary Strategy for Depicting Knowledge Graphs with Temporal Attributes

In practical applications, the temporal completeness of knowledge graphs is of great importance. However, previous studies have mostly focused on static knowledge graphs, generally neglecting the dynamic evolutionary properties of facts. Moreover, the unpredictable and limited availability of temporal knowledge graphs, together with the complex temporal dependency patterns, make current models inadequate for effectively describing facts that experience temporal transitions. To better represent the evolution of things over time, we provide a learning technique that uses quaternion rotation to describe temporal knowledge graphs. This technique describes the evolution of entities as a temporal rotation change in quaternion space. Compared to the Ermitian inner product in complex number space, the Hamiltonian product in quaternion space is better at showing how things might be connected. This leads to a learning process that is both more effective and more articulate. Experimental results demonstrate that our learning method significantly outperforms existing methods in capturing the dynamic evolution of temporal knowledge graphs, with improved accuracy and robustness across a range of benchmark datasets.

Pure-quartic soliton in a birefringence-managed fiber laser

Pure-quartic soliton (PQS) fiber lasers with a great variety of operating regimes have aroused considerable interest in high-energy ultrashort pulses and novel soliton patterns. Here, we numerically investigate the generation and dynamic properties of birefringence-managed pure-quartic soliton (BMPQS) in a positive fourth-order dispersion (FOD) fiber laser consisting of single-mode fibers and a section of polarization-maintaining fiber. The formation mechanism of the chirp-free BMPQS is dominated by the phase-matching effect, which arises from the co-actions of the birefringence, positive FOD, and nonlinear effects. It is observed that a higher FOD coefficient leads to energy transfer between the spectral sidebands inside the BMPQS. Moreover, the evolution of the BMPQS with the increase of the pump power confirms the phase-matching theory. Finally, the BMPQS molecule can be obtained with further increasing the pump power. This work offers a new avenue to create chirp-free pulses in positive FOD fiber lasers and enriches the sub-families of PQSs.

Polymer Engineering Enables High Linear Capacity Fiber Electrodes by Microenvironment Regulation.

Unlike bulky and rigid traditional power systems, 1D fiber batteries possess appealing features such as flexibility and adaptability, which are promising for use in wearable electronic devices. However, the performance and energy density fiber batteries are limited by the contradiction between ionic transfer and robust structure of fiber electrodes. Herein, these problems are addressed via polymer engineering to regulate the microenvironment in electrodes, realizing high-linear-capacity thick fiber electrodes with excellent cycling performance. The porosity of the electrodes is regulated using polymer crosslink networks designed with various components, and lithium-ion transfer is optimized through ether-abundant polymer chains. Furthermore, reinforced covalent bonding with carbon nanotube networks is established based on the modified functional groups of polymer networks. The multiscale optimizations of the porous structure, ionic transportation, and covalent bonding network enhance the lithium-ion dynamics property and structural stability. Therefore, ultrahigh linear-capacity fiber electrodes (17.8mAh m-1) can be fabricated on a large scale and exhibit excellent stability (92.8% after 800 cycles), demonstrating obvious superiority among the reported fiber electrodes. Moreover, this study highlights the high effectiveness of polymer regulation in fiber electrodes and offers new avenues for designing next-generation wearable energy-storage systems.

Mechanical Properties Comparison of Isotropic vs. Anisotropic Hybrid Magnetorheological Elastomer-Fluid.

Magnetorheological (MR) materials are smart materials that can change their rheological characteristics when exposed to a magnetic field. Such rheological properties include viscosity and dynamic modulus. MR materials have emerged as one of the most efficient smart materials that can modify mechanical and viscoelastic characteristics. Depending on the medium used, MR materials can be classified into two types: magnetorheological fluids (MRFs) and magnetorheological elastomers (MREs). MREs are classified as isotropic or anisotropic based on CIP distribution inside the elastomer matrix. A unique hybrid material incorporating MRE and MRF is constructed in this work to investigate, compare, and the dynamic properties of isotropic, anisotropic, hybrid isotropic, and hybrid anisotropic MREs under various magnetic fields (0, 104, and 160.2 mT). The created samples are subjected to extensive testing, including static and dynamic evaluations. In the static tests, experiments use a compression linear displacement mode with a fixed maximum gap change of 3 mm. The temperature is maintained at a constant level of 24 °C throughout the 40 s test duration for each test, and the magnetic field is incrementally increased by varying the number of magnets, ranging from 0 to 160.2 mT for dynamic qualities using compression oscillations on a dynamic mechanical analyzer (DMA), including frequency and strain-dependent data. These experiments, carried out using sinusoidal shear movements, include an excitation frequency range of 0.1 Hz to 15 Hz while preserving, with a fixed shear strain of 2%.

Gradually Self-Strengthen DNA Supramolecular Hydrogels.

The dynamic mechanical strength of the extracellular matrix (ECM) has been demonstrated to play important role in determining the cell behavior. Growing evidences suggest that the gradual stiffening process of the matrix is particularly decisive during tissue development and wound healing. Herein, a novel strategy to prepare hydrogels with gradually enhanced mechanical strength is provided. Such hydrogels could maintain the dynamic properties at their initial states, such as self-healing and shear-thinning properties. With subsequent slow covalent crosslinking, the stability and mechanical properties would be gradually improved. This method is useful for sequence programmability and oxidation strategies, which has provided an alternated tool to study cell behavior during dynamic increase in mechanical strength of ECM.

Combining Scattering Experiments and Colloid Theory to Characterize Charge Effects in Concentrated Antibody Solutions.

Charges and their contribution to protein-protein interactions are essential for the key structural and dynamic properties of monoclonal antibody (mAb) solutions. In fact, they influence the apparent molecular weight, the static structure factor, the collective diffusion coefficient, or the relative viscosity, and their concentration dependence. Further, charges play an important role in the colloidal stability of mAbs. There exist standard experimental tools to characterize mAb net charges, such as the measurement of the electrophoretic mobility, the second virial coefficient, or the diffusion interaction parameter. However, the resulting values are difficult to directly relate to the actual overall net charge of the antibody and to theoretical predictions based on its known molecular structure. Here, we report the results of a systematic investigation of the solution properties of a charged IgG1 mAb as a function of concentration and ionic strength using a combination of electrophoretic measurements, static and dynamic light scattering, small-angle X-ray scattering, and tracer particle-based microrheology. We analyze and interpret the experimental results using established colloid theory and coarse-grained computer simulations. We discuss the potential and limits of colloidal models for the description of the interaction effects of charged mAbs, in particular pointing out the importance of incorporating shape and charge anisotropy when attempting to predict structural and dynamic solution properties at high concentrations.

Multifaceted regulation of siderophore synthesis by multiple regulatory systems in Shewanella oneidensis

Siderophore-dependent iron uptake is a mechanism by which microorganisms scavenge and utilize iron for their survival, growth, and many specialized activities, such as pathogenicity. The siderophore biosynthetic system PubABC in Shewanella can synthesize a series of distinct siderophores, yet how it is regulated in response to iron availability remains largely unexplored. Here, by whole genome screening we identify TCS components histidine kinase (HK) BarA and response regulator (RR) SsoR as positive regulators of siderophore biosynthesis. While BarA partners with UvrY to mediate expression of pubABC post-transcriptionally via the Csr regulatory cascade, SsoR is an atypical orphan RR of the OmpR/PhoB subfamily that activates transcription in a phosphorylation-independent manner. By combining structural analysis and molecular dynamics simulations, we observe conformational changes in OmpR/PhoB-like RRs that illustrate the impact of phosphorylation on dynamic properties, and that SsoR is locked in the ‘phosphorylated’ state found in phosphorylation-dependent counterparts of the same subfamily. Furthermore, we show that iron homeostasis global regulator Fur, in addition to mediating transcription of its own regulon, acts as the sensor of iron starvation to increase SsoR production when needed. Overall, this study delineates an intricate, multi-tiered transcriptional and post-transcriptional regulatory network that governs siderophore biosynthesis.

Decay of time correlations in point vortex systems

The dynamics of a large point vortex system whose initial configuration consists in uniformly distributed independent positions is investigated. Time correlations of local observables of the vortex configuration are shown to be compatible with power law decay 1/t, providing additional insight on ergodicity and mixing properties of equilibrium dynamics in point vortex models.

Comparative study on effects of steel fiber and imitation steel fiber on dynamic tensile properties of ultra-high-performance cementitious composites

Comparative study on effects of steel fiber and imitation steel fiber on dynamic tensile properties of ultra-high-performance cementitious composites

Exploring the disruptions of the neurophysiological organization in Alzheimer’s disease: An integrative approach

Background and Objective:Alzheimer’s disease (AD) is a neurological disorder that impairs brain functions associated with cognition, memory, and behavior. Noninvasive neurophysiological techniques like magnetoencephalography (MEG) and electroencephalography (EEG) have shown promise in reflecting brain changes related to AD. These techniques are usually assessed at two levels: local activation (spectral, nonlinear, and dynamic properties) and global synchronization (functional connectivity, frequency-dependent network, and multiplex network organization characteristics). Nonetheless, the understanding of the organization formed by the existing relationships between these levels, henceforth named neurophysiological organization, remains unexplored. This work aims to assess the alterations AD causes in the resting-state neurophysiological organization. Methods:To that end, three datasets from healthy controls (HC) and patients with dementia due to AD were considered: MEG database (55 HC and 87 patients with AD), EEG1 database (51 HC and 100 patients with AD), and EEG2 database (45 HC and 82 patients with AD). To explore the alterations induced by AD in the relationships between several features extracted from M/EEG data, association networks (ANs) were computed. ANs are graphs, useful to quantify and visualize the intricate relationships between multiple features. Results:Our results suggested a disruption in the neurophysiological organization of patients with AD, exhibiting a greater inclination towards the local activation level; and a significant decrease in the complexity and diversity of the ANs (p-value ¡ 0.05, Mann–Whitney U-test, Bonferroni correction). This effect might be due to a shift of the neurophysiological organization towards more regular configurations, which may increase its vulnerability. Moreover, our findings support the crucial role played by the local activation level in maintaining the stability of the neurophysiological organization. Classification performance exhibited accuracy values of 83.91%, 73.68%, and 72.65% for MEG, EEG1, and EEG2 databases, respectively. Conclusion:This study introduces a novel, valuable methodology able to integrate parameters characterize different properties of the brain activity and to explore the intricate organization of the neurophysiological organization at different levels. It was noted that AD increases susceptibility to changes in functional neural organization, suggesting a greater ease in the development of severe impairments. Therefore, ANs could facilitate a deeper comprehension of the complex interactions in brain function from a global standpoint.

Study on the Ionic Transport Properties of 3D Printed Concrete

Three-dimensional printed concrete (3DPC) is an anisotropic heterogeneous material composed of a concrete matrix and the interfaces between layers and filaments that form during printing. The overall ion transport properties can be characterized by the equivalent diffusion coefficient. This paper first establishes a theoretical model to calculate the equivalent diffusion coefficient of 3DPC. Verification through numerical calculations shows that this theoretical model is highly precise. Based on this, the model was used to analyze the effects of dimensionless interface parameters on the equivalent diffusion coefficients in different directions of 3DPC. Finally, the dynamic ionic transport properties of 3DPC were investigated through finite element numerical simulation. The results of the dynamic study indicate that interfaces have a significant impact on the ion distribution and its evolution within 3DPC. The product of the interface diffusion coefficient and interface size can represent the ionic transport capacity of an interface. The stronger the ionic transport capacity of an interface, the higher the ion concentration at that interface. Due to the “drainage” effect of lateral interfaces, the ion concentration in the middle of 3DPC with a smaller equivalent diffusion coefficient is higher than that in 3DPC with a larger equivalent diffusion coefficient.

Microscopic model for a Brownian translator

A microscopic model for a translational Brownian motor, dubbed a Brownian translator, is introduced. It is inspired by the Brownian gyrator described by Filliger and Reimann (2007 Phys. Rev. Lett. 99 230602). The Brownian translator consists of a spatially asymmetric object moving freely along a line due to perpetual collisions with a surrounding ideal gas. When this gas has an anisotropic temperature, both spatial and temporal symmetries are broken and the object acquires a nonzero drift. Onsager reciprocity implies the opposite phenomenon, that is dragging a spatially asymmetric object into an (initially at) equilibrium gas induces an energy flow that results in anisotropic gas temperatures. Expressions for the dynamical and energetic properties are derived as a series expansion in the mass ratio (of gas particle vs. object). These results are in excellent agreement with molecular dynamics simulations.

Improved time-variable transformer-based fault diagnosis method for satellite attitude control system

This study proposes a fault diagnosis method based on a time-variable transformer network for satellite attitude control system telemetry data, which has the properties of a time series and strong multivariate correlation. First, a time-attention module was utilised to determine the correlation between the data at a specific time and before that time to effectively identify the dynamic properties of the data. A variable attention module is introduced to capture the degree of correlation between various variables to achieve multivariate decoupling. Then, the interactive attention layer combines the dynamic properties of the data with the correlations between the variables to achieve dynamic data decorrelation. Finally, a linear layer is used to implement the fault diagnosis.