Microsoft AI creates cheap solid-state battery by sifting through 32 million virtual electrolyte materials

Microsoft used the power of its novel AI models to identify and screen suitable materials for solid-state battery electrolyte as part of its Azure Quantum team efforts to use artificial intelligence for spearheading scientific discovery.

Microsoft’s novel AI algorithms screened 32 million potential material combos to identify more than half a million stable candidates that don’t exist in nature:

We used AI models to screen this pool of materials for functional properties like redox potential and band gap, further reducing the number of potential candidates to about 800… Then, our Microsoft Quantum researchers used AI-accelerated MD simulations to investigate dynamic properties like ionic diffusivity. These simulations used AI models for forces at each MD step, rather than the slower DFT-based method. This stage reduced the number of candidates to 150. Then, practical features such as novelty, mechanics, and element availability were taken into consideration to create the set of 18 top candidates.

Together with the federal Department of Energy’s Pacific Northwest National Laboratory tests, Microsoft’s Azure Quantum team wound down the candidates to one breakthrough discovery. Instead of rare and expensive lithium, it uses abundant sodium and yet covers all the solid-state electrolyte performance parameters fed by the algorithm.

Microsoft’s Azure Quantum AI effort led to building viable cell prototypes that address the main obstacle before commercializing solid-state batteries – their cost – in a fraction of the time that would have been needed with more traditional scientific research methods.

The solid-state battery was then tested "at both room temperature and high temperature," tips Microsoft, evoking an "interesting" reaction by none other than Tesla’s CEO Elon Musk, who immediately saw the potential in what is often considered as the Holy Grail of EV batteries.

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