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Microsoft and PNNL screen 32m materials with AI to find a lower-lithium electrolyte

See how this story connects

Source: Microsoft Azure Quantum BlogAlso reported by Utility Dive

Microsoft and the US Department of Energy’s Pacific Northwest National Laboratory used AI models and high-performance computing on Azure Quantum Elements to screen more than 32 million candidate materials, cutting them to 18 top candidates. PNNL made one of them, a solid electrolyte that replaces some lithium with sodium for up to 70% less lithium, and built a working battery with it. PNNL said the whole process took under nine months.

Why it matters

A national laboratory took an AI-screened material from more than 32 million candidates to a working battery prototype in under nine months.

When
9 Jan 2024
ID
WTA-N-2024-0018
Who
Microsoft, Pacific Northwest National Laboratory, Department of Energy

Summary by wheresthe.ai, from Microsoft Azure Quantum Blog and the reporting credited above. Checked against the source on 9 Oct 2026.

Read the original at Microsoft Azure Quantum Blog

Source copy: download the page as saved on 18 Oct 2026 (PDF). Also held by the Internet Archive.

Cite this story

WTA-N-2024-0018: “Microsoft and PNNL screen 32m materials with AI to find a lower-lithium electrolyte.” wheresthe.ai, 9 Jan 2024. https://wheresthe.ai/d/microsoft-pnnl-ai-battery-electrolyte-2024-01/ (source: Microsoft Azure Quantum Blog).

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