Aihua Tang
Papers
1
Total Citations
3
H-Index
1
About
Aihua Tang is a leading researcher in the field of lithium battery safety, with a particular focus on thermal runaway detection and prevention. Their most notable contribution is the development of a machine vision algorithm that enables early recognition and boundary detection of thermal runaway events in lithium batteries. This work, published in 2025, has already garnered 3 citations, reflecting its immediate relevance to the pressing challenge of battery safety in electric vehicles and energy storage systems. Tang’s research integrates computer vision with electrochemical analysis, offering a non-invasive, real-time monitoring solution that can identify pre-failure signatures before catastrophic failure occurs. This breakthrough has significant implications for improving battery reliability and reducing fire risks, positioning Tang as a key innovator in the intersection of artificial intelligence and energy storage safety. Their work is particularly valuable for students and researchers exploring predictive maintenance and failure mitigation strategies in next-generation battery technologies.
Research Focus
Key Achievements
Top Papers
- 1