Flexible conductive materials possess excellent flexibility, stretchability, and electrical conductivity, enabling them to accommodate complex dynamic deformation modes, stretching, twisting, and wrinkling.This paper systematically reviews the structural characteristics, performance advantages, and fabrication features of the three major material systems, carbon-based materials, polymer composites, and novel flexible conductive materials, elucidates their electrical transport behavior and underlying mechanisms under mechanical deformation and cyclic strain, and compares the application limitations and shortcomings of different materials.Based on this, the paper summarizes current challenges regarding material performance synergy, long-term stability, processing costs, and large-scale fabrication, and analyzes future development directions such as composite structure design, mechanistic research, fabrication processes, and device integration. This paper systematically summarizes the common limitations across various device applications, providing a theoretical reference for the design and engineering applications of high-performance strain sensors and human-computer interaction devices.

This study strongly focuses on the topic "To what extent can mathematical modelling be used to calculate the maximum cornering speed of a Formula One car", which focuses on the practical application of mathematical modelling in the analysis of F1 car dynamics. Firstly, through the literature review, this paper introduced related concepts in physics and engineering. Next, modelling with different complexities is sorted out. Factors determining maximum cornering speed in F1 cars are also briefly introduced. Secondly, models are established, from the basic model of a mass point, the rigid body and the Paceijka Magic Formula. Thirdly, this paper analyzed them by theoretical derivation and chose independent situations to calculate theoretical results. Finally, it compared the percentage error with practical data and discussed the applicability and limitations, respectively. The results show that, with the increase of the complexity of the model, percentage error gradually decreases, much closer to the actual situation. However, at the same time, it also needs higher requirements in data analysis and handling. Therefore, mathematical modelling has strong explanatory ability here, but its scope of application still depends on the rationality of model assumptions. The conclusion of this study has a certain reference value for understanding the dynamics of racing cars and also helps to apply physics and math to practical engineering problems, which has a positive significance for learning vehicle dynamics and engineering modelling.

Soft robots represent an emerging class of robots characterized by strong adaptability, excellent flexibility, and high maneuverability. Today, they are widely used in fields such as bioengineering, disaster relief, industrial production, medical services, exploration, and surveying. Drive technology is a key factor limiting their performance. Based on a review and analysis of relevant domestic and international literature from recent years, this paper investigates three typical and common drive methods: pneumatic drive, hydraulic drive, and dielectric elastomer drive. The paper elucidates the principles and research progress of these three drive methods and compares their advantages and disadvantages from multiple perspectives, including response speed, execution accuracy, output power, and application scenarios. The results indicate that pneumatic drive technology is highly mature and offers balanced overall performance; hydraulic drive can achieve high output force and power but results in bulky equipment; and dielectric elastomer drive offers fast response speeds but requires a higher drive voltage. This study provides a theoretical reference for the selection of soft robot actuators and the research and development of hybrid drive systems.