Autonomous optimization of non-aqueous Li-ion battery electrolytes via robotic experimentation and machine learning coupling
Human-operated optimization of non-aqueous Li-ion battery liquid electrolytes is a time-consuming process. Here, the authors propose an automated workflow that couples robotic experiments with machine learning to optimize liquid electrolyte formulations without human intervention.
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-09-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-022-32938-1 |