Uncovering the impact of delay phenomenon on random walks in a family of weighted m-triangulation networks

Uncovering the impact of special phenomena on dynamical processes in more distinct weighted network models is still needed. In this paper, we investigate the impact of delay phenomenon on random walk by introducing delayed random walk into a family of weighted m-triangulation networks. Specifically, we introduce delayed random walk into the networks. Then one and three traps are deployed, respectively, on the networks in two rounds of investigation. In both rounds of investigation, average trapping time (ATT) is applied to measure trapping efficiency and derived analytically by harnessing iteration rule of the networks. The analytical solutions of ATT obtained in both investigations show that ATT increases sub-linearity with the size of the network no matter what value the parameter [Formula: see text] manipulating delayed random walk takes. But [Formula: see text] can quantitatively change both its leading scaling and prefactor. So, introduction of delay phenomenon can control trapping efficiency quantitatively. Besides, parameters [Formula: see text] and [Formula: see text] governing networks’ evolution quantitatively impact both the prefactor and leading scaling of ATT simultaneously. In summary, this work may provide incremental insight into understanding the impact of observed phenomena on special trapping process and general random walks in complex systems.

Antagonist effects of grain boundaries between the trapping process and the fast diffusion path in nickel bicrystals

Hydrogen-grain-boundaries interactions and their role in intergranular fracture are well accepted as one of the key features in understanding hydrogen embrittlement in a large variety of common engineer situations. These interactions implicate some fundamental processes classified as segregation, trapping and diffusion of the solute which can be studied as a function of grain boundary configuration. In the present study, we carried out an extensive analysis of four grain-boundaries based on the complementary of atomistic calculations and experimental data. We demonstrate that elastic deformation has an important contribution on the segregation energy which cannot be simply reduced to a volume change and need to consider the deviatoric part of strain. Additionally, some significant configurations of the segregation energy depend on the long-range elastic distortion and allows to rationalize the elastic contribution in three terms. By investigating the different energy barriers involved to reach all the segregation sites, the antagonist impact of grain boundaries on hydrogen diffusion and trapping process was elucidated. The segregation energy and migration energy are two fundamental parameters in order to classify the grain-boundaries as a trapping location or short circuit for diffusion.

Effects of Different Aboveground Structural Parts of Grass Strips on the Sediment-Trapping Process

Grass strips can decrease erosion, trap sediment in silt-laden water flowing downhill, and control nonpoint source pollution. Determining the effects of different parts of grass strips on silt-laden overland flow will improve our understanding of sediment trapping by grass strips with different structures. Sediment trapping by grass strips was studied using a 5° slope, 30 L min−1 m−1 flow rate, 120 g L−1 sediment concentration, and different aboveground components of grass strips (complete grass, removed green grass, and removed green and withered grass). The whole overland flow process was monitored. Meanwhile, the runoff sediment samples at the outlet were collected and measured. Sediment trapping by aboveground grass parts was quantified at different stages. Of the soil bed surface, green grass, and withered grass, the soil bed surface dominated sediment trapping in the initial stage of the sediment-trapping process, contributing about 90% of total sediment deposition in the first 5 min. As the sediment-trapping process continued, the effect of the soil bed surface weakened, and the green grass played a major role at the later stage of sediment trapping. The ratio of the soil bed surface, green grass, and withered grass contributions to total sediment deposition at the stable stage of the experiments was approximately 3:5:2. The results will help assess the effects of vegetation restoration on sediment transport in entire watersheds.

Some Advances on Antagonist Effects of Grain Boundaries between the Trapping Process and the Fast Diffusion Path Investigated on Nickel Bicrystals

Hydrogen-grain-boundaries interactions and their role in intergranular fracture are well accepted as one of the key features in understanding hydrogen embrittlement in a large variety of common engineer situations. These interactions implicate some fundamental processes classified as segregation, trapping and diffusion of the solute which can be studied as a function of grain boundary configuration. In the present study, we carried out an extensive analysis of four grain-boundaries based on the complementary of atomistic calculations and experimental data. We demonstrate that elastic deformation has an important contribution on the segregation energy which cannot be simply reduced to a volume change and need to consider the deviatoric part of strain. Additionally, some significant configurations of the segregation energy depend on the long-range elastic distortion and allows to rationalize the elastic contribution in three terms. By investigating the different energy barriers involved to reach all the segregation sites, the antagonist impact of grain boundaries on hydrogen diffusion and trapping process was elucidated. The segregation energy and migration energy are two fundamental parameters in order to classify the grain-boundaries as a trapping location or short circuit for diffusion.

Dynamic thermal trapping enables cross-species smart nanoparticle swarms

Bioinspired nano/microswarm enables fascinating collective controllability beyond the abilities of the constituent individuals, yet almost invariably, the composed units are of single species. Advancing such swarm technologies poses a grand challenge in synchronous mass manipulation of multimaterials that hold different physiochemical identities. Here, we present a dynamic thermal trapping strategy using thermoresponsive-based magnetic smart nanoparticles as host species to reversibly trap and couple given nonmagnetic entities in aqueous surroundings, enabling cross-species smart nanoparticle swarms (SMARS). Such trapping process endows unaddressable nonmagnetic species with efficient thermo-switchable magnetic response, which determines SMARS’ cross-species synchronized maneuverability. Benefiting from collective merits of hybrid components, SMARS can be configured into specific smart modules spanning from chain, vesicle, droplet, to ionic module, which can implement localized or distributed functions that are single-species unachievable. Our methodology allows dynamic multimaterials integration despite the odds of their intrinsic identities to conceive distinctive structures and functions.

Delayed random walk on deterministic weighted scale-free small-world network with a deep trap

How to effectively control the trapping process in complex systems is of great importance in the study of trapping problem. Recently, the approach of delayed random walk has been introduced into several deterministic network models to steer trapping process. However, exploring delayed random walk on pseudo-fractal web with the co-evolution of topology and weight has remained out of reach. In this paper, we employ delayed random walk to guide trapping process on a salient deterministic weighted scale-free small-world network with the co-evolution of topology and weight. In greater detail, we first place a deep trap at one of initial nodes of the network. Then, a tunable parameter [Formula: see text] is introduced to modulate the transition probability of random walk and dominate the trapping process. Subsequently, trapping efficiency is used as readout of trapping process and average trapping time is employed to measure trapping efficiency. Finally, the closed form solution of average trapping time (ATT) is deduced analytically, which agrees with corresponding numerical solution. The analytical solution of ATT shows that the delayed parameter [Formula: see text] only modifies the prefactor of ATT, and keeps the leading scaling unchanged. In other words, ATT grows sublinearly with network size, whatever values [Formula: see text] takes. In summary, the work may serves as one piece of clues for modulating trapping process toward desired efficiency on more general deterministic networks.