A team of researchers at the Massachusetts Institute of Technology (MIT) has developed a novel method for interpreting the faint sounds that lithium-ion batteries produce during charging and discharging, providing new insights into the internal degradation processes that can limit battery life. The work, demonstrates how subtle acoustic emissions can be used to identify specific mechanisms of battery wear and failure, offering the potential for non-destructive, real-time monitoring systems for applications ranging from electric vehicles to grid-scale energy storage. The study was led by Chevron Professor of Chemical Engineering Martin Z. Bazant, with contributions from MIT graduate students Yash Samantaray and Alexander Cohen, and former MIT research scientist Daniel Cogswell, Ph.D. ’10.
Lin, L., Hartono, K., Ko, Y., Mallela, R., Samantaray, Y., Bouteiller, H., Bazant, M. Z., & Wang, H. (2025). Mechanically induced thermal runaway severity analysis of Li-ion batteries and continuous energy release monitoring. Journal of Energy Storage, 133, 118078. https://doi.org/10.1016/j.est.2025.118078
Lithium-ion batteries are widely used, but their internal processes can be difficult to monitor. Before a battery loses capacity, fails unexpectedly, or experiences safety events such as thermal runaway, it often emits faint sounds caused by internal chemical reactions or mechanical stresses. Until now, distinguishing between ordinary background noise and signals indicative of degradation has been a challenge. By combining electrochemical testing with simultaneous recording of acoustic emissions under real-world operating conditions, the MIT team was able to correlate specific sounds with internal processes, including gas generation from side reactions and fracturing due to expansion and contraction of active materials. These correlations were confirmed through post-mortem analyses using electron microscopy, providing a detailed picture of the mechanisms underlying battery degradation.
Chevron Professor of MIT Chemical Engineering stated,
“In this study, through some careful scientific work, our team has managed to decode the acoustic emissions, We were able to classify them as coming from gas bubbles that are generated by side reactions, or by fractures from the expansion and contraction of the active material, and to find signatures of those signals even in noisy data.”
A critical innovation in this study was the use of advanced signal processing techniques, including wavelet transforms, to encode the frequency and duration of individual acoustic events. This allowed the researchers to extract meaningful signals from noisy data and identify degradation signatures with high precision. By tracking the voltage and current at the time of each emission, the team could determine the conditions under which specific degradation mechanisms occurred, such as gas bubble formation or localized material fractures. The combination of high-resolution acoustic monitoring and electrochemical data provides a cost-effective, non-invasive method for observing internal battery processes that previously required expensive or destructive testing.
This approach has several practical implications. For manufacturers, it could improve quality control during battery formation, helping identify cells that are more likely to fail before they are integrated into larger systems. Formation cycling, a standard process in battery manufacturing where cells are charged and discharged to stabilize their chemistry, is both time-consuming and costly. By monitoring acoustic signatures associated with gas evolution and material fracturing, manufacturers could detect poorly formed cells early, reducing production costs and improving reliability. For end-users, including electric vehicle operators and energy storage managers, acoustic monitoring could serve as a predictive maintenance tool, offering early warnings of potential failures or thermal events, enhancing safety, and extending battery life.
The research builds on prior work by the MIT team in collaboration with Oak Ridge National Laboratory, which showed that acoustic emissions can serve as an early warning for thermal runaway, a dangerous situation that can lead to fires if not detected. By identifying gas formation and material fracturing before catastrophic failure occurs, the system functions like an early indicator, similar to detecting the first tiny bubbles in a pot of water before it boils. This insight could inform both laboratory research, where new battery chemistries are tested, and commercial monitoring systems, where continuous observation of battery health is crucial.
Looking forward, the MIT team is working to translate these findings into practical monitoring systems. With funding from Tata Motors, they aim to develop acoustic-based battery health monitoring devices for electric vehicles. Such systems would be compact, passive, and cost-effective, providing continuous assessment of battery condition without altering the cells themselves. Beyond vehicles, this technology could be adapted for grid-scale energy storage, consumer electronics, and industrial applications, wherever reliable battery performance is critical. By giving engineers and researchers a new window into the internal state of batteries, this work has the potential to influence both battery design and lifecycle management, helping ensure safer, longer-lasting energy storage solutions.
The MIT study represents a significant step forward in battery diagnostics. By decoding acoustic emissions and linking them to specific degradation mechanisms, the research provides a non-destructive, real-time method for understanding battery health. As the demand for reliable lithium-ion technology grows across transportation, renewable energy, and electronics, tools that can predict battery lifespan and prevent failure will be increasingly valuable. This work not only advances scientific understanding but also lays the groundwork for practical systems that could enhance safety, efficiency, and longevity of lithium-ion batteries across multiple sectors.
Adrian graduated with a Masters Degree (1st Class Honours) in Chemical Engineering from Chester University along with Harris. His master’s research aimed to develop a standardadised clean water oxygenation transfer procedure to test bubble diffusers that are currently used in the wastewater industry commercial market. He has also undergone placments in both US and China primarely focused within the R&D department and is an associate member of the Institute of Chemical Engineers (IChemE).
