Batterylife Farasis: 123 Lithium-Ion Pouch Cells for Cycle Life Prediction

123 industrial-grade large-format lithium-ion pouch cells released with a Nature article on predicting battery cycle life. The cells feature diverse material-design combinations and cycling protocols. The dataset was published by the author Battery-Life and is sourced from Zenodo and Code Ocean.

Use Cases

• Predict battery cycle life based on minimal experimental data, as referenced in the associated Nature article.
• Analyze the impact of diverse material-design combinations on battery performance.
• Benchmark machine learning models for time-series forecasting of battery degradation.
• Study the effects of different cycling protocols on lithium-ion pouch cell longevity.

Strengths

• Contains 123 individual cell records, providing a substantial sample size for analysis.
• Data is industrial-grade and associated with a peer-reviewed Nature article, suggesting high quality.
• Explicitly described as having diverse material-design combinations and cycling protocols.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count per cell file is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Zenodo and Code Ocean, as per the Nature article's Data availability section.

Collection Method

Released as part of the research for the article 'Discovery Learning predicts battery cycle life from minimal experiments'.

Freshness

Last updated 2026-07-03 02:12:53; freshness should be verified.