A comprehensive study on the irradiation damage of PP/PbO composites under γ-ray exposure

High-performance titanium-based composite strengthened with heterogeneous network structure

Polymer‐based radiation shielding materials are receiving more and more interests due to their desirable advantages in lightweight and maneuverability. Herein, we employ polypropylene (PP) as the matrix to construct γ‐ray shielding composites through the embedment of PbO particles with a wet reaction melt blending method. From the changes in dynamic rheological behaviors and fracture surface of PP/PbO composite, it can be found that the gradient addition of PbO particles facilitates the formation of heterogeneous network structure with, and high PbO content may make the composites undergo a “liquid–solid” transition. Rheological temperature and time scanning show that both PbO content and heterogeneous network structure greatly contribute to the storage modulus (G') and thermal stability. The γ‐ray (137Cs) shielding tests manifest that BPP/PbO‐4 has the best shielding performance, whose thicknesses of half value layer (HVL) and tenth value layer (TVL) are 0.32 and 1.05 cm, respectively, obviously smaller than those shielding materials ever reported. The analyses on effective atomic number (Zeff) and effective electron density (NE) reveal that the good shielding performance of BPP/PbO‐4 benefits from its proper content and dispersion of PbO particles.

A novel heterogeneous network structure titanium matrix composite with a combination of strength and ductility

The effect of hydrophilic and hydrophobic interactions on the rheological and microstructural behavior of cellulose acetate (CA) in a ternary CA, N,N-dimethylacetamide (DMA), nonsolvent (alcohol) system was examined. Increasing nonsolvent concentration increased the viscosity and dynamic viscoelastic properties of the system. At a critical nonsolvent concentration, a sol-gel transition was observed, which was dependent on nonsolvent structure. Increasing the available hydrogen bonding groups within the nonsolvent led to higher modulus (stronger gels) and a sol-gel transition at lower nonsolvent concentration. Likewise, increasing the alkyl chain length (hydrophobicity) of the nonsolvent also enhanced the viscoelastic properties; however, hydrogen bonding, specifically the ability to hydrogen bond donate was critical for gel formation. For all gels studied, the elastic modulus shifts to higher values with increasing hydrophilicity and hydrophobicity of the nonsolvent and exhibits a power-law behavior with nonsolvent content. All of the gels exhibit similar fractal dimensions; however, confocal images of the different systems reveal distinct differences. Increasing the hydrophilicity of the nonsolvent led to a more uniform denser gel microstructure, whereas increasing the hydrophobicity resulted in a larger more heterogeneous network structure despite the increase in moduli.

The surface of reactive nano‐silica coated with a silage coupling agent containing the epoxy group (denoted as E‐SiO2) and dimer fatty acids (DFA) were allowed to participate in the in‐situ polycondensation reaction of unsaturated polyester resin (UPR), thus obtaining E‐SiO2/DFA/UPR hybrid material. Fourier transform infrared spectrometer, scanning electron microscope, and X‐ray energy dispersive spectrometer were used to analyze the structure of the material, morphology of tensile section, and the element composition of the section. It was found that E‐SiO2 grafted onto the DFA/UPR backbone by chemical bonds, and the material exhibited ductile fracture with Si element on the fracture surface. Thermogravimetric analysis, differential scanning calorimetry, stress–strain test, tensile test, bending test, hardness test, and water resistance test, the influence of the content of E‐SiO2 on the thermal stability, mechanical properties, and water resistance of the materials was studied. The results show that E‐SiO2 has a good reinforcing and toughening effect for the in‐situ polymerized E‐SiO2/DFA/UPR composite due to the chemical reaction between the epoxy group of E‐SiO2 and the hydroxyl group (carboxyl group) of DFA/UPR. A heterogeneous network structure was formed in the cured E‐SiO2/DFA/UPR composites. The mechanical properties and thermal properties of E‐SiO2 nanocomposites were improved. When 0.8 wt% E‐SiO2 was added, the tensile strength, Young's modulus, flexural strength, flexural stress, elongation at break, and Shore A hardness increased by 37.03%, 69.18%, 86.81%, 86.80%, 14.0%, and 14.71%, respectively, compared to DFA/UPR. At the same time, the addition of E‐SiO2 also improved the water resistance of hybrid materials.

The team formation problem is required to find a group of individuals that can match the skills required by a collaborative task. Large-scale and comprehensive scientific research tasks need skilled experts from various fields to form a research team and work for it. This paper constructs a dataset and proposes team formation algorithms to find out research teams, which provides decision support for the research projects. The size of existing datasets is relatively small and fields of experts in it are less diversified. This paper extracts information of experts and skills from research news to construct a co-occurrence network with heterogeneous network structure. Based on the dataset, this work designs approximate algorithms regarding skill as the priority to find near optimum teams with provable guarantees. On heterogeneous structure, the proposed algorithms directly search requested skills to form the subgraph of team, which achieve significant improvement in time efficiency. Experimental results suggest that our methods can form the high-quality research team, and have better efficiently compared to naive strategies and scale well with the size of the data.

The team formation problem is required to find a group of individuals that can match the skills required by a collaborative task. Large-scale and comprehensive scientific research tasks need skilled experts from various fields to form a research team and work for it. This paper constructs a dataset and proposes team formation algorithms to find out research teams, which provides decision support for the research projects. The size of existing datasets is relatively small and fields of experts in it are less diversified. This paper extracts information of experts and skills from research news to construct a co-occurrence network with heterogeneous network structure. Based on the dataset, this work designs approximate algorithms regarding skill as the priority to find near optimum teams with provable guarantees. On heterogeneous structure, the proposed algorithms directly search requested skills to form the subgraph of team, which achieve significant improvement in time efficiency. Experimental results suggest that our methods can form the high-quality research team, and have better efficiently compared to naive strategies and scale well with the size of the data.

A heterogeneous transfer learning method for fault prediction of railway track circuit

Chitin nanofiber was prepared from purified crab shell chitin by repeated high-pressure homogenization in water. The chitin nanofiber/water dispersion thus prepared was viscous and translucent, and maintained a stable dispersion at room temperature for several months. AFM images showed that the chitin nanofibers had heterogeneous network structures with widths ranging from several nanometers to several tens of nanometers. Some kinks and twisted structures were also observed in the AFM images. X-ray diffraction patterns showed that both the crystallinity index and crystal width of the original alpha-chitin decreased with nanofibrillation. Solid-state 13C-NMR spectra showed that the chemical shifts of all carbons were unchanged before and after nanofibrillation, and that all C6–OH groups had the gauche-gauche conformation irrespective of the crystalline fibril surfaces and insides. The degree of N-acetylation increased from 0.83 to 0.98, which was probably due to C2–NH2 groups present in the original chitin being partially removed during high-pressure homogenization in water. The original chitin and chitin nanofiber were dissolved in 8% LiCl/DMAc, and the solutions after dilution to 1% LiCl/DMAc were subjected to size-exclusion chromatography combined with multi-angle laser-light scattering to determine their molar masses and molar mass distributions. The weight-average molar mass (Mw) value of the original chitin was 271,200 (degree of polymerization [DP] ~1340). The Mw value of the chitin nanofiber was 165,500 (DP 820), showing that the DP of the original chitin decreased by 40% through the nanofibrillation in water to form the chitin nanofiber. Chitin nanofibers were prepared from purified crab-shell chitin particles by repeated high-pressure homogenization in water. AFM images showed that the chitin nanofibers had heterogeneous network structures. X-ray diffraction patterns showed that both the crystallinity index and crystal width of the original α-chitin decreased by nanofibrillation. Solid-state 13C-NMR spectra showed that all C6–OH groups had the gauche–gauche conformation. The degree of N-acetylation increased from 0.83 to 0.98 by nanofibrillation, while the weight-average molar masses of the original chitin and chitin nanofibers were 271,200 and 165,500, respectively.

In general, multilayer networks are often a significantly more apt description of real-life systems than isolated or single networks. In this paper, we explore the effect of memory on the evolution of prisoner's dilemma (PD) game by constructing different kinds of two-layer networks. The results show that the heterogeneous network structure is conducive to promoting individuals to adopt cooperative behaviors. However, as the lure income T increases, the individuals who take cooperative behavior in the entire system gradually decrease. Further research shows that if no more than one layer of network presents large heterogeneity, then the less the individuals are affected by historical gains, the better the cooperation will be among individuals. By contrast, if both layers of networks are less heterogeneous, the greater the impact of historical returns on individuals, the easier it is for cooperation between individuals. Furthermore, if individuals change their strategies mainly by imitating the strategies of their neighbors, then it is beneficial to promote cooperation among individuals in the entire system. However, it is not conducive to cooperation among individuals if individuals change their own strategy mainly through strategies of their counterparts. The final result indicates that, if at least one layer is a heterogeneous network structure, the cooperation between individuals in the entire system will be blocked when the length of the individual's historical memory is too long.

A heterogeneous network structure publishing security framework based on cloud-edge collaboration

Precise path computation based on functional block-based disaggregation for future heterogeneous access-metro networks

Heterogeneous network structures formed in TiC/TC4/β-Ti composites for enhancing strength with good ductility

Traffic projections for the coming years indicate that the demand for wireless data is increasing exponentially, driven by new multimedia services and the wide availability of smartphones. A promising approach for providing additional required network capacity is the deployment of small cells in a heterogeneous network structure, which increases the spatial frequency re-use. However, the deployment of small cells into existing macrocellular networks can lead to interference and handover problems, particularly when re-using the frequency spectrum. In this paper, a novel configuration of the cellular network structure and frequency use for both macrocell and small cells is proposed to address these problems while maintaining high frequency re-use. Simulations for UMTS HSDPA show that the proposed multi-carrier heterogeneous network structure can increase the average user throughput of macrocells and small cells by 51% and 116% respectively, and the throughput of the worst 5th percentile by 213%, compared to a dedicated carrier reference deployment. The proposed solution also significantly outperforms partial frequency re-use deployments.

Designing and optimizing the polymer network structure at the molecular level to manipulate its mechanical properties are of great scientific significance. Although heterogeneous multi-network structures have been extensively investigated, little effort has been devoted to investigating heterogeneous single-networks with a well-defined interface. Herein, through coarse-grained molecular dynamics simulation, we successfully fabricated a heterogeneous single-network, which was divided into several regions with different crosslink densities. Firstly, we found that there is an optimal crosslink density ratio between high and low crosslink density regions to obtain the best stress-strain behavior. Secondly, the effect of the regularity of the network topology (by changing the distribution of two-phase regions) on mechanical properties was also studied. It was clearly observed that the polymer network showed better elastic response and mechanical properties as the distribution of two-phase regions became uniform. Finally, we investigated the effect of the selective distribution of nanoparticles (NPs) on mechanical properties by introducing NPs into a pre-designed multiphase network. Results showed that the selective distribution of NPs in the high crosslink density region had a more significant effect on the mechanical reinforcement. Generally, our simulated results may provide some guidelines to design polymer network structures to achieve high-performance polymer nanocomposites with excellent mechanical properties.