SEM / TEM
Turn a micrograph into particle statistics automatically.
Niobia segments the image and counts grains — mean size and distribution from a picture, instead of a manual trace.
What this method tells you
SEM / TEM is one of the analytical methods Niobia AI surfaces inside the materials development branch. The short readout is: Niobia segments the image and counts grains — mean size and distribution from a picture, instead of a manual trace.
Where it fits in Niobia
Niobia keeps this method connected to the surrounding workflow, so teams can move from microscopy into adjacent methods without reformatting data or rebuilding the context from scratch.
Method-specific output, not just a screenshot
Niobia packages sem / tem alongside the rest of the materials development 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 SEM / TEM help a team understand?
SEM / TEM sits inside Niobia AI's materials development workflows and helps teams turn raw process, materials, or quality signals into a defensible engineering readout.
When should engineers use SEM / TEM?
Use SEM / TEM 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 SEM / TEM?
The closest companion methods are AFM, Particle size. Reading them together makes it easier to see how Niobia AI moves from one analytical method to the next.