Scientists have discovered a pioneering method to radically improve the lifespan of batteries. The new technique, developed by a team from Qingdao Institute of Bioenergy and Bioprocess Technology (QIBEBT) in China, enables a highly-promising type of battery to achieve 20,000 charging cycles with an energy density of 390 Wh/kg.
Artificial intelligence (AI) and large-scale cloud computing is speeding up the search for new battery materials. An AI-enhanced collaboration between Microsoft and the Pacific Northwest National Laboratory (PNNL) has already produced one promising new material, which the two are sharing publicly today.
A brand new substance, which could reduce lithium use in batteries, has been discovered using artificial intelligence (AI) and supercomputing. The findings were made by Microsoft and the Pacific Northwest National Laboratory (PNNL), which is part of the US Department of Energy.
First, the researchers used AI to filter the materials based on stability, namely, whether they could actually exist in the real world. That pared the list down to fewer than 600,000 candidates. Further AI analysis selected candidates likely to have the electrical and chemical properties necessary for batteries.
The process from inception to the development of a working battery prototype took less than nine months. The two organisations achieved this by using advanced AI and high-performance computing which combines large numbers of computers to solve complex scientific and mathematical tasks.
In the hunt for new materials, scientists have traditionally relied on tinkering in the lab, guided by intuition, with a hefty serving of trial and error. But now a new battery material has been discovered by combining two computing superpowers: artificial intelligence and supercomputing.