Study on Chaotic Peculiarities of Magnetic-Mechanical Coupled System of Giant Magnetostrictive Actuator

We studied the chaotic peculiarities of magnetic-mechanical coupled system of GMA. Based on the working principle of GMA and according to Newton’s second law of motion, first piezomagnetic equation, disk spring design theory, and structural dynamics principle of GMA, the present study established a GMA magnetic-mechanical coupled system model. By carrying out data modeling of this coupled system model, the bifurcation chart of the system with the variation of damping factor, excitation force, and exciting frequency parameters as well as the homologous offset oscillogram, phase plane trace chart, and Poincaré diagram was obtained, and the chaotic peculiarities of the system were analyzed. The influence of parametric errors on the coupled system was studied. The analytical results showed that the oscillation equation of the GMA magnetic-mechanical coupled system had nonlinearity and the movement morphology was complicated and diversified. By adjusting the damping factor, exciting frequency, and excitation force parameters of the system, the system could work under the stable interval, which provided theoretical support for the stability design of GMA

Surfactant-Free Synthesis of Single Crystalline SnS 2

Sheetlike tin disulfide (SnS2) single crystal exposed with well-defined {001} facets and flowerlike SnS2 mainly exposed with {010} facets were prepared through a surfactant-free solvothermal process. Photocatalytic degradation of methyl orange (MO) under visible light irradiation indicated that the sheetlike SnS2 showed a much higher activity than flowerlike SnS2. Theoretical and experimental results revealed that the band structure derived from the surface atomic structure played a more important role than the surface energy in the photocatalytic property. The present work has provided a deep insight into the important role of the surface energy and band structure, both of which are derived from the surface atomic structure, in the photocatalytic activity

Achieving high strength and high ductility in metal matrix composites reinforced with a discontinuous three-dimensional graphene-like network

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Activated Carbon Nanochains with Tailored Micro-Meso Pore Structures and Their Application for Supercapacitors

Carbon nanochains (CNCs) were synthesized by a facile chemical vapor deposition process consisting of a 1D chain of interconnected carbon nano-onions for potential application in supercapacitors. In this study, the CNCs were further activated by a chemical method using potassium hydroxide (KOH) as the activation agent to obtain micro-meso pore structures. To improve the specific surface area (SSA) and optimize the pore size distribution (PSD) to enhance the capacitance performance, we investigated the activation parameters, including the KOH content, temperature and duration. The results indicated that CNCs with a hierarchical pore structure and high SSA could be achieved using an activation process with a KOH-to-CNC ratio of 2 at 900 °C for 20 h. The mechanism is also discussed. The activation temperature and duration affect the promotion of the carbon graphitization and exaggeration of the carbon etching. The CNCs activated using the optimal parameters exhibited a high capacitance performance of 112.7 F g^–1 at 50 mV s^–1 with excellent stability in 6 M KOH electrolyte, which was due to the improved surface and micromesoporosity without sacrificing their electronic transmission properties

Machine Learning Enabled Capacitance Prediction for Carbon-Based Supercapacitors

Carbon is the most widely used electrode for the supercapacitors. To predict the capacitance of carbon-based supercapacitors, this work applies three machine learning (ML) methods, including linear regression, Lasso and artificial neural network. For training the ML process, we extracted data from hundreds of published papers. Moreover, five variables were selected to figure out their impact on capacitance, including specific surface area, calculated pore size, ID/IG ratio, N-doping level and voltage window. By evaluated with the real data, all of three methods achieve acceptable prediction results, and ANN exhibits the best performance. More importantly, this work shows the potential of ML in material science and advanced applications

Interface and Doping Effect on the Electrochemical Property of Graphene/LiFePO₄

Surface properties of olivine phosphate LiFePO₄, as cathodes in lithium ion batteries, are of importance for overall performance as the nanoscale of particles has become indispensable. Using the first-principles total energy calculations, the effects of graphene or Mn dopant on the electrochemical properties of graphene/LiFePO₄ have been comprehensively investigated. It is revealed that the interfacial binding between graphene and LiFePO₄ in parallel orientation is stable and improved in the process of doping. The Li adsorption energy at different sites elucidates the core–shell model in Li extraction/insertion process and indicates the anomalous Li storage in the interface between graphene and LiFePO₄. Mechanisms underlying influences of adsorption site, Mn dopant, and graphene modification on the Li adsorption energy are discussed through edge effect, doping stability, and interfacial binding strength, respectively. The surface conductivity is improved in the presence of graphene or Mn dopant with respect to the bandlike electron transport