Photoresist pattern defects
Detect resist pattern collapse, bridging, footing, and scumming after develop.
Example outputs shown for illustration. Numbers depend on your samples and protocol.
Image: Mohammad et al., Nanoscale Research Letters 2013 8:139, CC BY 2.0
Results
Each measurement below comes from your own images, tied back to the annotated frame it came from, so results stay comparable across samples, locations, and conditions.
class
Defect count by mode
Each detected feature assigned to a class using the agreed rule set, shown on the image.
Example, not a claimed result
In your report: Per-feature class, counts by class, and annotated overlays.
class
Collapse / bridge / footing class
Each detected feature assigned to a class using the agreed rule set, shown on the image.
Example, not a claimed result
In your report: Per-feature class, counts by class, and annotated overlays.
per area
Location map
Findings placed in sample coordinates to reveal spatial patterns and local density.
In your report: Coordinate-referenced map, regional density, and representative images.
% area
Affected-area %
Segmented area of the feature divided by the eligible area in the two-dimensional image.
In your report: Per-field value, size distribution, and the segmentation overlay used.
per area
Per-field tally
Findings placed in sample coordinates to reveal spatial patterns and local density.
In your report: Coordinate-referenced map, regional density, and representative images.
Built around your image set
Use the calibrated images your team already collects, together with the locations you need to compare.
Each report includes
The artifacts your team receives, ready for review and archive.
Annotated image set
Original images with regions of interest, measurement points, masks, and finding overlays.
Measurement table
Location-indexed values, units, distributions, and QC flags in a structured export.
Method record
Calibration evidence, analysis settings, version history, and validation summary.
Confidence in every resultTraceable measurements, reviewed against your agreed reference method.
- Traceable scale
- The report records the image scale, calibration evidence, and a method-specific expanded measurement uncertainty. It does not use one product-wide accuracy number.
- Reference comparison
- The configured method is compared with your accepted reference method or reviewed annotations, and reports bias by measurement range and image condition.
- Detection performance
- Detections are evaluated against reviewed reference regions with precision, recall, and segmentation overlap, separated by the conditions that affect performance.
- Repeatability
- The locked protocol is rerun on the same inputs and on a defined repeat set. The review records variation from image acquisition, sampling, and analysis separately where possible.
What this result does not establish: Flags pattern deviations visible in the image and classifies them by failure mode. Whether a field is reworkable is your process decision.
The measurement, today
After-develop inspection is a manual scan for a short list of failure modes. Subtle bridges and partial collapse are easy to miss at speed, and the counts are rarely recorded per field.
What it costs
A resist defect becomes a hard mask for the etch beneath it, so it prints straight into the device. Caught at develop, the wafer can be stripped and reworked; caught after etch, it is scrap.
From image to reviewed result
- 1
Image after develop
Load after-develop SEM or optical images of the resist pattern.
- 2
Find deviations
Regions that depart from the intended pattern are detected.
- 3
Classify the mode
Each defect is labelled collapse, bridge, footing, or scumming.
- 4
Map and tally
Defects are located and totalled per field with an affected-area fraction.
Not sure this is the right measurement?
Send a representative image and your measurement goal. A ConductVision scientist will confirm whether this is the right fit, or point you to the closer workflow, before you commit to a quote.
Related applications
Semiconductor defect patterns
Classify wafer-map patterns and quantify defect clusters and densities.
Line edge & width roughness (LER / LWR)
Line edge and line width roughness as 3-sigma deviation along patterned lines.
Critical dimension (CD) metrology
Line width, space, and via diameter measured from top-down images, with per-feature tables.
Send a sample image and a measurement goal
We will show the closest ConductVision workflow and flag what needs custom validation for your images.
