Multifunctional graphene thermal switch material with adaptive heat control, flame retardant and machine learning-assisted monitor for high-efficiency battery management

Safe and efficient operation of high-energy-density battery systems relies on thermal management. But current methods of thermal management are not always up to snuff when it comes to thermal response and flame resistance. By manipulating the microstructure of low-grade graphene through gas evaporation and directional freeze-drying, we were able to create a thermally switchable flame-retardant material that can undergo fast transitions. In 20 seconds at around 140 °C, the material goes from being conductive (1.23 W·m -1 ·K -1 ) to being insulating (0.11 W·m -1 ·K -1 ), thus combining the roles of efficient heat transfer and thermal insulation. By acting as a separator in nickel-manganese lithium-ion batteries, this material improves the stability of the modules and decreases the dangers of explosions caused by thermal runaway by drastically reducing heat diffusion. Additionally, a thermosensitive flame-retardant composite with many functions based on graphene was created to assist with responsive heat management. In order to facilitate proactive risk assessment, infrared imaging and real-time temperature data were used to detect early-stage thermal abnormalities using the machine learning system. A new, economical, and scalable method for controlling electric vehicle and energy storage battery safety has been developed through the combination of intelligent detection and thermal switching. This method promotes improvements in performance and inherent safety. • Development of a thermally switchable flame-retardant graphene-based material enables thermal management. • Enhanced battery safety through intelligent separator design reduces thermal runaway risks. • Integration of YOLO-based deep learning and infrared imaging enables real-time detection of thermal abnormalities. • Thermal control and intelligent diagnosis enhance battery performance and safety.

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Publication Details

Journal
Composites Part B Engineering
Published
2026-02-03
DOI
https://doi.org/10.1016/j.compositesb.2026.113480
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
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article

Multifunctional graphene thermal switch material with adaptive heat control, flame retardant and machine learning-assisted monitor for high-efficiency battery management

Lili Zheng, Haiqin Zhang, Mingjia Li, Yihao Li et al.
Composites Part B Engineering
Advanced Battery Technologies Research
article

Multifunctional graphene thermal switch material with adaptive heat control, flame retardant and machine learning-assisted monitor for high-efficiency battery management

Lili Zheng, Haiqin Zhang, Mingjia Li, Yihao Li, Tianle Zhang, Song Shi, Hongyao Xue, Yan He, Peng Wang, Zhiming Liu
article en

Abstract

Safe and efficient operation of high-energy-density battery systems relies on thermal management. But current methods of thermal management are not always up to snuff when it comes to thermal response and flame resistance. By manipulating the microstructure of low-grade graphene through gas evaporation and directional freeze-drying, we were able to create a thermally switchable flame-retardant material that can undergo fast transitions. In 20 seconds at around 140 °C, the material goes from being conductive (1.23 W·m -1 ·K -1 ) to being insulating (0.11 W·m -1 ·K -1 ), thus combining the roles of efficient heat transfer and thermal insulation. By acting as a separator in nickel-manganese lithium-ion batteries, this material improves the stability of the modules and decreases the dangers of explosions caused by thermal runaway by drastically reducing heat diffusion. Additionally, a thermosensitive flame-retardant composite with many functions based on graphene was created to assist with responsive heat management. In order to facilitate proactive risk assessment, infrared imaging and real-time temperature data were used to detect early-stage thermal abnormalities using the machine learning system. A new, economical, and scalable method for controlling electric vehicle and energy storage battery safety has been developed through the combination of intelligent detection and thermal switching. This method promotes improvements in performance and inherent safety. • Development of a thermally switchable flame-retardant graphene-based material enables thermal management. • Enhanced battery safety through intelligent separator design reduces thermal runaway risks. • Integration of YOLO-based deep learning and infrared imaging enables real-time detection of thermal abnormalities. • Thermal control and intelligent diagnosis enhance battery performance and safety.

Composites Part B EngineeringVol. 314
Qingdao University (CN), Beijing Institute of Technology (CN), Qingdao University of Science and Technology (CN), Beijing Research Institute of Mechanical and Electrical Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 69%
Advanced Battery Technologies Research
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