Two Approaches to Uniformity
The same tools used to diagnose why runs differ apply within a single run. Instead of comparing entire runs, you look at how the run behaves across its own phases, layers, or time windows.- Monitor Session View (Detailed)
- Explore Similarity (Broad)
Inspect a single run over time to see where its behavior changes.The Monitor session view replays a run with its growth metrics, tool state, and detected events on one timeline. Watching how the metrics evolve across the run reveals drift, excursions, and phases that behave differently from the rest.What you see:
- Growth metrics charts of derived RHEED metrics across the full run, where drift and excursions show up as the values move
- Tool state instrument parameters synchronized with the metrics, giving context for why a particular stretch of the run varied
- Activity timeline of detected changepoints, marking the moments where the run’s behavior shifted
Setting Up
Open the run on the Monitor page
Select the session from the Sessions sidebar on the
Monitor page.
Replay the run end to end
Use the playback bar to scrub through the run, or follow the live edge for an active one. See
Session View.
Watch the metrics across phases
Look for stretches where a metric drifts away from the run’s earlier behavior, or where one
phase, layer, or cycle spreads more than the others.
What to Look For
Drift Over Time
Segments that gradually shift away from early-run behavior indicate drift. In the Monitor session view, this appears as growth metrics that steadily trend away from where they started. In Explore Similarity, drifting segments form a gradient on the map rather than a tight cluster.Outlier Segments
A single segment that diverges sharply from the rest points to a transient disturbance, easiest to spot in Explore Similarity where the outlier sits visibly apart.Phase-Specific Variation
Some recipe phases may be consistently less uniform than others. If segments from one phase always spread more widely, that phase likely needs tighter process control. The Monitor session view makes this visible in the growth metrics, showing which derived properties vary most during the problematic phase.Periodic Structure Consistency
For multilayers and superlattices, watch how each cycle behaves in the growth metrics on the Monitor session view. Consistent cycles repeat nearly identical metric patterns. If early cycles differ from late cycles, or if specific cycles stand out, the time-resolved view shows exactly where within the cycle the variation occurs. Explore Similarity complements this: plot the cycles on the map and consistent ones cluster tightly while outliers separate.Connecting Uniformity to Outcomes
Within-run uniformity metrics become most valuable when connected to final device or material properties. Runs with tight internal clustering tend to produce more consistent outcomes. If loosely clustered runs correlate with degraded performance, that gives you a quantitative uniformity threshold to monitor against.Choosing the Right Approach
| Scenario | Approach | Why |
|---|---|---|
| Seeing where within a run a cycle or phase varies | Monitor session view | Time-resolved metrics and changepoints show exactly when the run’s behavior shifts |
| Checking whether all segments in a run are consistent | Explore Similarity | Immediately reveals outliers and clustering without pre-selecting references |
| Identifying which recipe phase has the most variation | Explore Similarity | Segments from different phases naturally separate on the map if they behave differently |
| Understanding why a specific layer is different | Monitor session view | Detailed metrics and tool state pinpoint what changed during that layer |
| Tracking uniformity improvement across iterations | Explore Similarity | Compare segment clustering tightness across runs to see if uniformity is improving |
Next Steps
Diagnose Why Runs Differ
Compare entire runs against each other when the issue is between runs rather than within one.
Detect Anomalies
Set up automated detection to catch uniformity problems as they develop during active runs.