Diamond-like carbon (DLC) films with excellent anti-friction and wear resistance, can effectively reduce the energy loss of tribosystems and the wear failure of parts, but the high residual stress limits their application and service life. Researchers found that doping heterogeneous elements in the carbon matrix can alleviate the defects in the microstructure and properties of DLC films (reduce the residual stress; enhance adhesion strength; improve tribological, corrosion resistance, hydrophobic, biocompatibility, and optical properties), and doping elements with different properties will have different effects on the structure and properties of DLC films. In addition, the comprehensive properties of DLC films can be coordinated by controlling the doping elements and their contents. In this paper, the effects of single element and co-doping of carbide-forming elements (Nb, W, Mo, Cr, Ti, Si) and non-carbide-forming elements (Cu, Al, Ag, Ni) on the properties of microstructure, mechanical, tribological, optical, hydrophobic, corrosion resistance, etc. of DLC films are reviewed. The mechanisms of the effects of doping elements on the different properties of DLC films are summarized and analyzed.

As the terminal of the power system, the distribution network is the main area where failures occur. In addition, with the integration of distributed generation, the traditional distribution network becomes more complex, rendering the conventional fault location algorithms based on a single power supply obsolete. Therefore, it is necessary to seek a new algorithm to locate the fault of the distributed power distribution network. In existing fault localization algorithms for distribution networks, since there are only two states of line faults, which can usually be represented by 0 and 1, most algorithms use discrete algorithms with this characteristic for iterative optimization. Therefore, this paper combines the advantages of the particle swarm algorithm and genetic algorithm and uses continuous real numbers for iteration to construct a successive particle swarm genetic algorithm (SPSO-GA) different from previous algorithms. The accuracy, speed, and fault tolerance of SPSO-GA, discrete particle swarm Genetic algorithm, and artificial fish swarm algorithm are compared in an IEEE33-node distribution network with the distributed power supply. The simulation results show that the SPSO-GA algorithm has high optimization accuracy and stability for single, double, or triple faults. Furthermore, SPSO-GA has a rapid convergence velocity, requires fewer particles, and can locate the fault segment accurately for the distribution network containing distorted information.

Molecular dynamics (MD) simulations were conducted to investigate the interactions between a palygorskite coating and linear chain alkanes (dodecane C₁₂, tetradecane C₁₄, hexadecane C₁₆, and octadecane C₁₈), representing base oils in this study. The simulation models were built by placing the alkane molecules on the surface of the palygorskite coating. These systems were annealed and geometrically optimized to obtain the corresponding stable configurations, followed by the analysis of the structural changes occurring during the MD process. The interfacial interaction energies, mean square displacements, and self-diffusion coefficients of the systems were evaluated to characterize the interactions between base lubricant molecules and palygorskite coating. It was found that the alkanes exhibited self-arrangement ability after equilibrium. The interfacial interaction was attractive, and the electrostatic energy was the main component of the binding energy. The chain length of the linear alkanes had a significant impact on the intensity of the interfacial interactions and the molecular diffusion behavior. Moreover, the C₁₂ molecule exhibited higher self-diffusion coefficient values than C₁₄, C₁₆ and C₁₈. Therefore, it could be the best candidate to form an orderliness and stable lubricant film on the surface of the palygorskite coating. The present work provides new insight into the optimization of the structure and composition of coatings and lubricants, which will guide the experimental development of these systems for practical applications.

This article reveals the chip formation and the reducing of cutting force mechanisms of nickel-based superalloy Inconel 718 under elliptical vibration cutting using finite element analysis software. The results are compared with traditional cutting methods. The elliptical motion trajectory of the tool in elliptical vibration cutting machining is analyzed, and a two-dimensional finite element elliptical vibration cutting model is established. The effects of dynamic impact on the elliptical vibration cutting of Inconel 718 were discussed in terms of the surface morphology, chip formation mechanism, and cutting force reduced mechanism. The simulation results show that (1) compared with traditional cutting, the surface morphology of the workpiece machined by elliptical vibration cutting is better, and the machined surface has obvious elliptic indentation; (2) in traditional cutting, sawtooth chips are formed through shear slip, while in elliptical vibration cutting, the faster relative cutting speed [ ], higher tool-tip temperature, and smaller material removal cross-sectional area cause a more prominent thermal softening effect in the chip formation process than that in traditional cutting, which leads to the plastic flow to be dominant in the material removal process, resulting in the strip chips; and (3) compared with traditional cutting, the normal cutting force and the tangential cutting force in elliptical vibration cutting are separately reduced about 51.4% and 60.8%.