Background
As the core of the global sustainable energy system, lithium-ion batteries are widely applied in electric vehicles, grid-scale energy storage and consumer electronics. However, they are prone to thermal runaway (TR) under thermal, mechanical or electrical abuse, which may trigger exothermic reactions, flammable gas release and structural deformation, and even fires and explosions in severe cases, becoming a core safety bottleneck restricting the high-quality development of the lithium-ion battery industry.
Current lithium-ion battery monitoring technologies have prominent limitations: single-modal sensors can only detect a single parameter such as voltage, temperature and pressure, and fail to correlate the coupled electrochemical, thermal and mechanical processes inside the battery, making it hard to accurately define the thermal runaway early warning window. Traditional multimodal sensors suffer from severe signal crosstalk and rely on complex hardware or algorithms for decoupling. In addition, fiber optic sensors are easily damaged by bending and vibration, while thin-film sensors are mostly limited to temperature-pressure dual-modal monitoring without gas detection function, and their large volume hinders seamless integration with batteries. Therefore, developing a low-crosstalk, multi-dimensional, miniaturized and high-stability monitoring sensor has become an urgent key demand for accurate early warning of lithium-ion battery thermal runaway.
Research Progress
Inspired by the multimodal perception characteristics of insect antennae (for force, temperature and gas), the ECUST interdisciplinary team developed the Electronic Multifunctional Sensing Antenna (EMSA)—a flexible thin-film self-decoupling multimodal sensor fabricated via a maskless laser direct writing process. The sensor realizes intrinsic decoupling of temperature and strain, as well as simultaneous thermo-mechanical-gas trimodal monitoring, with four core technological breakthroughs:
1.Bionic structure with multi-mechanism perception: The sensor is composed of a sensilla-like sensing layer, a 0.05 mm polyimide (PI) flexible substrate (antennae-like) and a customized brain-like back-end data acquisition system. Its temperature, strain and gas modules are based on the Seebeck effect, capacitance change and redox reaction of semiconductor metal oxides for detection, and adopt orthogonal output signals to fundamentally eliminate signal crosstalk (Figure 1).

2.Superior intrinsic decoupling and sensing performance: It achieves reliable intrinsic decoupling of temperature and strain in the 20~110 °C range (the critical interval for lithium-ion battery thermal runaway early warning), and the gas signal can be decoupled by compensating for independent temperature and strain signals. All modules perform as well as or even better than commercial sensors, with a temperature accuracy of ±1 °C, a strain detection range of 0~3500 με, and a minimum hydrogen detection limit of 10 ppm (surpassing the international standard). The sensor also features fast response, excellent long-term stability and strong robustness in high-humidity environments (Figure 2).

3.Outstanding process and integration advantages: The maskless laser direct writing process enables seamless integration of heterogeneous functional materials. The sensor is small in size, customizable, and can be seamlessly attached to the battery surface. Moreover, its manufacturing cost is lower than similar commercial sensors, boasting great industrialization potential (Figure 3).

4.Highly matched multiphysics model synergy: The team developed electrochemical-thermal-mechanical (E-T-M) and electrochemical-thermal-pressure (E-T-P) coupling models, which are highly consistent with the actual measurement data for EMSA. The models can accurately analyze the thermo-mechanical evolution of lithium-ion batteries under normal operation and the internal reaction laws during thermal runaway, realizing precise definition of the early warning window (Figure 4).

Taking lithium iron phosphate pouch cells as the research object, the team completed thermal runaway monitoring experiments under normal charge-discharge conditions and three abuse scenarios (thermal, mechanical and electrical). The results show that EMSA can accurately capture the full-life-cycle multimodal signals of batteries: it can efficiently identify the core precursor nodes of thermal runaway for earlier and more efficient warning judgment under thermal abuse, responds 2.3 seconds earlier than the voltage signal under mechanical abuse, and it can detect hydrogen leakage signals under electrical abuse that are undetectable by temperature sensors. Meanwhile, EMSA can distinguish the trigger types of thermal runaway and support timely intervention before irreversible reactions occur.
Future Outlook
This self-decoupling multimodal sensor (EMSA) not only provides a compact, high-reliability and low-cost innovative solution for lithium-ion battery thermal runaway early warning, but also offers new ideas for the R&D of multimodal sensors with its core design and preparation process. Its maskless laser direct writing integration advantage and bionic multi-mechanism perception decoupling strategy can be extended to the safety monitoring of other energy storage devices and industrial equipment.

In practical applications, EMSA can be directly integrated into the lithium-ion battery systems of electric vehicles, grid-scale energy storage stations and portable electronic devices to realize real-time wireless safety monitoring. The combination of the sensor and multiphysics coupling models can be applied to the safety optimization in the lithium-ion battery design stage, providing data support for risk assessment and process improvement in battery manufacturing, and promoting the safety upgrading of the entire lithium-ion battery industry. In addition, the sensor’s trimodal monitoring and self-decoupling technology can be combined with battery management systems (BMS) and artificial intelligence early warning algorithms to build an integrated platform for lithium-ion battery safety monitoring and early warning, laying a solid technical foundation for the safe and high-quality development of the new energy industry.

The complete study is accessible via DOI:0.34133/research.1120