Song Chiwon, Lee Haran, Park Chan, Lee Byeongjun, Kim Jungmin, Park Cheoljeong, Lai Chi Hung, Cho Seong J
Department of Mechanical Engineering, Chungnam National University, Daejeon 34134, Republic of Korea.
Polymers (Basel). 2025 Mar 30;17(7):941. doi: 10.3390/polym17070941.
This review focuses on deepening the structural understanding of crack-based strain sensors (CBSS) on stretchable and flexible polymeric substrates and promoting sensor performance optimization. CBSS are cutting-edge devices that purposely incorporate cracks into their functional elements, thereby achieving high sensitivity, wide working ranges, and rapid response times. To optimize the performance of CBSS, systematic research on the structural characteristics of cracks is essential. This review comprehensively analyzes the key factors determining CBSS performance such as the crack mechanism, geometrical factors, and functional structures and proposes optimization strategies grounded in these insights. In addition, we explore the potential of numerical analysis and machine learning to offer novel perspectives for sensor optimization. Following this, we introduce various applications of CBSS. Finally, we discuss the current challenges and future prospects in CBSS research, providing a roadmap for next-generation technologies.
本综述着重于加深对可拉伸柔性聚合物基底上基于裂纹的应变传感器(CBSS)的结构理解,并促进传感器性能优化。CBSS是前沿器件,其功能元件特意引入裂纹,从而实现高灵敏度、宽工作范围和快速响应时间。为优化CBSS的性能,对裂纹结构特征进行系统研究至关重要。本综述全面分析了决定CBSS性能的关键因素,如裂纹机制、几何因素和功能结构,并基于这些见解提出了优化策略。此外,我们探讨了数值分析和机器学习为传感器优化提供新视角的潜力。在此之后,我们介绍了CBSS的各种应用。最后,我们讨论了CBSS研究中的当前挑战和未来前景,为下一代技术提供了路线图。