Application of BP Artificial Neural Network in Preparation of Ni-W Graded Coatings.

The internal stress difference between soft-ductile aluminum alloy substrate and hard-brittle Ni-W alloy coating will cause stress concentration, thus leading to the problem of poor bonding force. Herein, this work prepared the Ni-W graded coating on aluminum alloy matrix by the pulse electrodeposition method in order to solve the mechanical mismatch problem between substrate and coatings. More importantly, a backward propagation (BP) neural network was applied to efficiently optimize the pulse electrodeposition process of Ni-W graded coating. The SEM, EDS, XRD, Vickers hardness tester and Weighing scales are used to analyze the micromorphology, chemical element, phase composition, and micro hardness as well as oxidation weight increase, respectively. The results show that the optimal process conditions with BP neural network are as follows: the bath temperature is 30 °C, current density is 15 mA/cm2 and duty cycle is 0.3. The predicted value of the model agrees well with the experimental value curve, the relative error is minor. The maximum error is less than 3%, and the correlation coefficient is 0.9996. The Ni-W graded coating prepared by BP neural network shows good bonding with the substrate which has flat and smooth interface. The thickness of the coating is about 136 µm, which slows down the oxidation of the substrate and plays an effective role in protecting the substrate.

Reduced Graphene Oxide/Silicon Nitride Composite for Cooperative Electromagnetic Absorption in Wide Temperature Spectrum with Excellent Thermal Stability.

The fabrication of a sandwich-like composite that consists of reduced graphene oxide (RGO) and Si3N4 ceramic (RGO/Si3N4) was achieved through the combination of modified freeze-drying approach and chemical vapor infiltration process. Due to a hierarchical structure and a high ratio of ID/ IG (1.27), the RGO/Si3N4 exhibits an unprecedented high polarization relaxation loss (PRL), which accounts for 32% of the whole dielectric loss. The outstanding PRL endows the RGO/Si3N4 composites with unique temperature-independent dielectric properties and electromagnetic (EM) wave absorption performance. Even at a low absorbent content of only 0.16 wt %, the effective absorption bandwidth of RGO/Si3N4 composites can cover the whole X-band (8.2-12.4 GHz) at broad sample thicknesses ranging from 4.3 to 4.6 mm and temperatures ranging from 323 to 873 K. The mechanism for the enhancement of PRL and conductive loss was explicitly investigated. The outstanding absorption performance toward EM waves indicated that the resultant porous RGO/Si3N4 composite can be a promising candidate for the applications under elevated temperature.