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Influence of the Interface of Carbon Nanotube-Reinforced Aluminum Matrix Composites on the Mechanical Properties – a Review

Li Rong, Pan Zhilin, Zeng Qi, Xiaoli Ye

Archives of Foundry Engineering

2022

Vol. 22, iss. 1

23--36

Carbon nanotubes (CNTs) are a good reinforcement for metal matrix composite materials; they can significantly improve the mechanical, wear-resistant, and heat-resistant properties of the materials. Due to the differences in the atomic structure and surface energy between CNTs and aluminum-based materials, the bonding interface effect that occurs when nanoscale CNTs are added to the aluminum alloy system as a reinforcement becomes more pronounced, and the bonding interface is important for the material mechanical performance. Firstly, a comparative analysis of the interface connection methods of four CNT-reinforced aluminum matrix composites is provided, and the combination mechanisms of various interface connection methods are explained. Secondly, the influence of several factors, including the preparation method and process as well as the state of the material, on the material bonding interface during the composite preparation process is analyzed. Furthermore, it is explained how the state of the bonding interface can be optimized by adopting appropriate technical and technological means. Through the study of the interface of CNT-reinforced aluminum-based composite materials, the influence of the interface on the overall performance of the composite material is determined, which provides directions and ideas for the preparation of future high-performance CNT-reinforced aluminum-based composite materials.

Simulation and Analysis of Sintering Furnace Temperature Based on Fuzzy Neural Network Control

Chaoxin Zou, Rong Li, Zhiping Xie, Ming Su, Jingshi Zeng, Xu Ji, Xiaoli Ye, Ye Wang

Archives of Foundry Engineering

2021

Vol. 21, iss. 1

23--30

Aiming at the problems of delay and couple in the sintering temperature control system of lithium batteries, a fuzzy neural network controller that can solve complex nonlinear temperature control is designed in this paper. The influence of heating voltage, air inlet speed and air inlet volume on the control of temperature of lithium battery sintering is analyzed, and a fuzzy control system by using MATLAB toolbox is established. And on this basis, a fuzzy neural network controller is designed, and then a PID control system and a fuzzy neural network control system are established through SIMULINK. The simulation shows that the response time of the fuzzy neural network control system compared with the PID control system is shortened by 24s, the system stability adjustment time is shortened by 160s, and the maximum overshoot is reduced by 6.1%. The research results show that the fuzzy neural network control system can not only realize the adjustment of lithium battery sintering temperature control faster, but also has strong adaptability, fault tolerance and anti-interference ability.