Scientists leverage artificial intelligence to overcome a major hurdle in zinc-ion battery development, paving the way for cheaper, greener, and more efficient energy storage.
In a significant leap forward for battery innovation, scientists from Singapore’s Nanyang Technological University and China’s Huaiyin Normal University have teamed up to create an AI-powered system that could drastically improve how rechargeable batteries are made.
Led by Dr. Edison Huixiang Ang from the NIE/NTU, the team has harnessed artificial intelligence (AI) to solve one of the biggest challenges in zinc-ion battery technology, preventing dendrite growth.
Zinc-ion batteries are a promising alternative to today’s lithium batteries. They are cheaper, safer, and better for the environment. But they have one big problem-tiny spikes called dendrites can grow inside the battery when it charges. These spikes can cause the battery to stop working or even short-circuit.
To solve this, Dr. Ang’s team turned to AI. Instead of testing materials one by one, the AI quickly checked over 168,000 different combinations. This smart approach led them to a special material made from cerium and iron, called a metal-organic framework (MOF), that helps stop the dangerous spikes from forming.
“AI helped us discover the right material quickly and at a lower cost,” Dr. Edison Ang told Tech Explorist. “This allows us to create safer batteries that are more sustainable for the future.”
The team also created a thin protective layer using this material. In tests, the new battery design worked for over 4,300 hours and stayed almost 100% efficient after 1,400 charge cycles-much better than regular batteries.
This discovery could be useful for electric cars, phones, and storing solar or wind energy. As we move toward a greener world, having strong and reliable batteries is more important than ever.
“AI is helping scientists everywhere work smarter,” said Dr. Ang. “It’s opening the door to new ideas that can change the world.”
Journal Reference
- Jianbo Dong, Guolang Zhou, Wenhao Ding, Jiayi Ji, Qing Wang, Tianshi Wang, Lili Zhang, Xiuyang Zou, Jingzhou Yin and Edison Huixiang Ang. Machine learning-assisted benign transformation of three zinc states in zinc ion batteries. Energy & Environmental Science, 2025,18, 4872-4882. DOI: 10.1039/D5EE00650C
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