Aiming at the problems of lack of data on the nonlinear morphology to divide uneven grain boundary in bulk ceramics, a unique approach of nanorobot-based characterization of three-dimensional nonlinear structure length can be creatively proposed under scanning electron microscope to quantify the actual morphology of local micro-area grain boundary in bulk ZnO. Contour shapes of the targeted grain boundaries in plane X-Y can be imaged using SEM. Z-directional relative height differences at different positions can be sequentially probed by nanorobot. Experiments demonstrate that it is effective to characterize three-dimensional length structures of nonlinear grain boundaries in bulk materials. By quantifying Z-directional relative height differences, it can be verified to show that irregular characteristics exist in three-dimensional grain boundary length, which can extend the depth effect on nonlinear bulk conductance. Furthermore, this method can also obtain nonlinear quantitative topographies to divide grain boundaries to uneven structure in the analysis of bulk polycrystalline materials.
In this paper, the giant magneto-impedance (GMI) model of a cylindrical alloy fiber was established by the Maxwell equation and Landau–Lifshitz equation to simulate the influence of physical parameters of cylindrical alloy fiber on GMI under different control parameters. MATLAB was employed to calculate the magneto-impedance of cylindrical fibers and draw its curves. We found that when the anisotropic equivalent field of the fiber changes from 10Oe to 50Oe, the peak position of the GMI ratio also moves from about 10Oe to 50Oe, and the peak value gradually increases from 100% to 300%. The GMI ratio increased rapidly with the decrease in the magnetization damping coefficient. Our findings could further guide the design of supersensitive micro GMI sensors by optimally regulating the magnetic damping coefficient, the angle between the external magnetic field and easy axis and the anisotropic equivalent field of cylindrical alloy fibers.
In this paper, the impulsive multiple-bipartite consensus problem is discussed for networked second-order multi-agent systems (MASs) over directed network topology with acyclic partition. The definition of the multiple-bipartite consensus is introduced into second-order MASs by effectively combining the characteristics of bipartite consensus and group consensus based on the unique structure of network topology with acyclic and structural balance. By thoroughly exploring the coupling state between agents, a distributed impulsive multiple-bipartite consensus control protocol is designed for each agent by only measuring the relative information of its neighbors. Some sufficient conditions that guarantee realizing multiple-bipartite consensus are given, and the corresponding stability analysis is based on an improved Laplacian matrix associated with the network topology. Finally, some simulation examples are presented to verify the theoretical results.
In combination with the collective behavior evolutions of bipartite consensus and cluster/group consensus, this paper proposes the notion of multiple-bipartite consensus in networked Lagrangian systems (NLSs). The distributed leaderless and leader-following multiple-bipartite consensus control laws for NLSs are presented in the cooperative-competitive network, where the negative interactions between agents can exist in the same subnetwork. By introducing an acyclic partition and adding the integral item in the control protocols, the final explicit convergence states in the leaderless case are eventually obtained. Moreover, the leader-following scenario can be realized in fifinite time with integrated controllers. All of the effectiveness has been illustrated through numerical simulations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.