New research has potentially found a solution for some of consumers' biggest concerns about electric vehicle adoption: reducing fire hazards and extending battery life.
In a new study published in npj Computational Materials, researchers, including a Ph.D. student from Skoltech and AIRI Institute, demonstrated how neural networks can significantly accelerate the discovery of solid electrolyte materials. This advancement could address one of the biggest hurdles in EV battery design: creating batteries that are safer, longer-lasting, and capable of holding more charge while reducing fire risks.
Data shows that traditional internal combustion engine vehicles already have a much higher fire hazard risk than EVs.
Solid-state batteries are a highly anticipated successor to traditional lithium-ion EV batteries. Instead of using flammable liquid electrolytes, solid-state batteries utilize ceramic or other solid materials to move lithium ions between electrodes. These materials offer greater stability, enabling faster charging, longer ranges, and improved safety.
However, most known solid electrolytes do not yet meet all the technical requirements for commercial EVs. Researchers are now using artificial intelligence neural networks to predict new materials with high ionic mobility at speeds far surpassing traditional trial-and-error methods.
"We demonstrated that graph neural networks can identify new solid-state battery materials with high ionic mobility and do it orders of magnitude faster than traditional quantum chemistry methods," explained Artem Dembitskiy, the lead author of the study and a Ph.D. student at Skoltech. "Machine learning lets us screen tens of thousands of materials in a fraction of the time."
This innovative approach has helped the team identify two promising new protective coatings that could stabilize next-generation batteries and prevent dangerous short circuits.
The potential of solid-state batteries is significant: Some automakers estimate they could offer up to 50% more range compared to today's EVs, along with reduced fire risk and longer battery life. This translates into lower long-term maintenance costs and fewer battery replacements.
This research builds on previous AI-assisted breakthroughs in EV battery technology, fueling solid-state battery innovations that could enable EVs to last a decade longer than current battery technology.
Pairing these high-efficiency EVs with home solar can drive savings even further. By charging at home using solar energy, drivers can lower their electricity bills and easily compare rates on sites like EnergySage.
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While these solid-state batteries are not yet ready for mass-market EVs, AI tools like these are helping us get there faster. This breakthrough could enable automakers to reduce their reliance on nonrenewable fuels and create a cleaner, more affordable future for drivers everywhere.
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