This dataset contains over a thousand computed tomography (CT) scans of various batteries, offering a unique view into the impact of manufacturing variations on battery quality. It explores batteries across different chemistries and form factors, including lithium-ion and sodium-ion.

Researchers and engineers will find in this dataset an opportunity to inspect the manufacturing variability and defects in commercially available batteries.

Summary:

• Dataset of CT scans for as-produced batteries.
• Covers various chemistries and form factors.
• Observes manufacturing variability and defects.
• Facilitates non-destructive 3D inspection for quality control.

Review the data and its implications in the full article here.

The dataset stands to be a valuable resource for advancing not just battery technology but also for improving computer vision techniques used in quality control and inspection. It demonstrates the potential for AI to enhance quality assurance measures in high-volume manufacturing.