Wen-Lin Luo,Yao-Yao Xu,Xiong Cheng,Fang-Zhou Wang,Da-Ying Sun,Xiao-Dong Huang,Wen-Hua Gu,Cheng-Hui Li
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引用次数: 0
Abstract
Creating materials that can heal themselves while also being strong, stable, and quick to repair presents a major scientific challenge, as existing materials often sacrifice one of these properties for another. To address this limitation, a conductive composite is developed by incorporating ionic liquids into a common plastic. Measurable changes in the material's electrical properties enable damage detection. When a crack is detected, a small electric current is applied to the area, generating localized heat that melts the plastic to seamlessly seal the damage. This process is integrated with an artificial intelligence (AI) system that autonomously detects damage, triggers healing, and confirms repair completion. By establishing a complete perception-healing-feedback loop, this work realizes the conceptual leap from self-healing to smart-healing, pioneering a new generation of autonomous materials.
期刊介绍:
Advanced Materials, one of the world's most prestigious journals and the foundation of the Advanced portfolio, is the home of choice for best-in-class materials science for more than 30 years. Following this fast-growing and interdisciplinary field, we are considering and publishing the most important discoveries on any and all materials from materials scientists, chemists, physicists, engineers as well as health and life scientists and bringing you the latest results and trends in modern materials-related research every week.