University of Science and Technology Beijing

About: University of Science and Technology Beijing is a education organization based out in Beijing, China. It is known for research contribution in the topics: Microstructure & Alloy. The organization has 41558 authors who have published 44473 publications receiving 623229 citations. The organization is also known as: Beijing Steel and Iron Institute.

Interfacial engineering of carbon nanofiber-graphene-carbon nanofiber heterojunctions in flexible lightweight electromagnetic shielding networks.

Abstract: Lightweight carbon materials of effective electromagnetic interference (EMI) shielding have attracted increasing interest because of rapid development of smart communication devices. To meet the requirement in portable electronic devices, flexible shielding materials with ultrathin characteristic have been pursued for this purpose. In this work, we demonstrated a facile strategy for scalable fabrication of flexible all-carbon networks, where the insulting polymeric frames and interfaces have been well eliminated. Microscopically, a novel carbon nanofiber–graphene nanosheet–carbon nanofiber (CNF–GN–CNF) heterojunction, which plays the dominant role as the interfacial modifier, has been observed in the as-fabricated networks. With the presence of CNF–GN–CNF heterojunctions, the all-carbon networks exhibit much increased electrical properties, resulting in the great enhancement of EMI shielding performance. The related mechanism for engineering the CNF interfaces based on the CNF–GN–CNF heterojunctions has b...

Data-Driven Zero-Sum Neuro-Optimal Control for a Class of Continuous-Time Unknown Nonlinear Systems With Disturbance Using ADP

Abstract: This paper is concerned with a new data-driven zero-sum neuro-optimal control problem for continuous-time unknown nonlinear systems with disturbance. According to the input–output data of the nonlinear system, an effective recurrent neural network is introduced to reconstruct the dynamics of the nonlinear system. Considering the system disturbance as a control input, a two-player zero-sum optimal control problem is established. Adaptive dynamic programming (ADP) is developed to obtain the optimal control under the worst case of the disturbance. Three single-layer neural networks, including one critic and two action networks, are employed to approximate the performance index function, the optimal control law, and the disturbance, respectively, for facilitating the implementation of the ADP method. Convergence properties of the ADP method are developed to show that the system state will converge to a finite neighborhood of the equilibrium. The weight matrices of the critic and the two action networks are also convergent to finite neighborhoods of their optimal ones. Finally, the simulation results will show the effectiveness of the developed data-driven ADP methods.

Diffuse Phase Transitions and Giant Electrostrictive Coefficients in Lead-Free Fe3+-Doped 0.5Ba(Zr0.2Ti0.8)O3-0.5(Ba0.7Ca0.3)TiO3 Ferroelectric Ceramics

Abstract: The electrostrictive effect has some advantages over the piezoelectric effect, including temperature stability and hysteresis-free character. In the present work, we report the diffuse phase transitions and electrostrictive properties in lead-free Fe3+-doped 0.5Ba(Zr0.2Ti0.8)O3-0.5(Ba0.7Ca0.3)TiO3 (BZT-0.5BCT) ferroelectric ceramics. The doping concentration was set from 0.25 to 2 mol %. It is found that by introducing Fe3+ ion into BZT-0.5BCT, the temperature corresponding to permittivity maximum Tm was shifted toward lower temperature monotonically by 37 °C per mol % Fe3+ ion. Simultaneously, the phase transitions gradually changed from classical ferroelectric-to-paraelectric phase transitions into diffuse phase transitions with a weak relaxor characteristic. Purely electrostrictive responses with giant electrostrictive coefficient Q33 between 0.04 and 0.05 m4/C2 are observed from 25 to 100 °C for the compositions doped with 1–2 mol % Fe3+ ion. The Q33 of Fe3+-doped BZT-0.5BCT ceramics is almost twice t...

Electric-field-driven Non-volatile Multi-state Switching of Individual Skyrmions in a Multiferroic Heterostructure

Abstract: Electrical manipulation of skyrmions attracts considerable attention for its rich physics and promising applications. To date, such a manipulation is realized mainly via spin-polarized current based on spin-transfer torque or spin–orbital torque effect. However, this scheme is energy consuming and may produce massive Joule heating. To reduce energy dissipation and risk of heightened temperatures of skyrmion-based devices, an effective solution is to use electric field instead of current as stimulus. Here, we realize an electric-field manipulation of skyrmions in a nanostructured ferromagnetic/ferroelectrical heterostructure at room temperature via an inverse magneto-mechanical effect. Intriguingly, such a manipulation is non-volatile and exhibits a multistate feature. Numerical simulations indicate that the electric-field manipulation of skyrmions originates from strain-mediated modification of effective magnetic anisotropy and Dzyaloshinskii–Moriya interaction. Our results open a direction for constructing low-energy-dissipation, non-volatile, and multistate skyrmion-based spintronic devices. Spin-polarized current manipulation of magnetic skyrmions is energy consuming. Here, the authors achieve an electric-field manipulation of individual skyrmions in a nanostructured ferromagnetic/ferroelectrical heterostructure at room temperature via an inverse magneto-mechanical effect.