Capacity fade
Capacity retention against cycle number, with the 80% end-of-life line.
The knee is where degradation accelerates. Niobia projects cycle life to the 80% state-of-health threshold from the early trend.
What this method tells you
Capacity fade is one of the analytical methods Niobia AI surfaces inside the electrochemical branch. The short readout is: The knee is where degradation accelerates. Niobia projects cycle life to the 80% state-of-health threshold from the early trend.
Where it fits in Niobia
Niobia keeps this method connected to the surrounding workflow, so teams can move from galvanostatic into adjacent methods without reformatting data or rebuilding the context from scratch.
Method-specific output, not just a screenshot
Niobia packages capacity fade alongside the rest of the electrochemical stack, so the result stays connected to the raw inputs, the upstream context, and the next method the team needs to run.
Frequently asked
What does Capacity fade help a team understand?
Capacity fade sits inside Niobia AI's electrochemical workflows and helps teams turn raw process, materials, or quality signals into a defensible engineering readout.
When should engineers use Capacity fade?
Use Capacity fade when the question is better answered by that specific method than by a generic summary: it provides the method-specific signal, tradeoffs, and context the broader workflow depends on.
What should I read alongside Capacity fade?
The closest companion methods are Charge / discharge & CCCV. Reading them together makes it easier to see how Niobia AI moves from one analytical method to the next.