# Rapid Detection of Cleanliness on Direct Bonded Copper Substrate by Using UV Hyperspectral Imaging

## TL;DR

This paper introduces a UV hyperspectral imaging system for quickly and non-destructively checking the cleanliness of copper substrates used in electrical devices.

## Contribution

The study presents a novel UV hyperspectral imaging setup combined with multivariate models for real-time cleanliness monitoring of copper substrates.

## Key findings

- A PCA model successfully differentiated 11 cleanliness levels with 100.0% explained variance.
- A PLS-R model achieved high accuracy (R2cv = 0.928) in predicting optimal sonication time for cleanliness.
- The system can predict cleanliness at the pixel level, showing potential for large-scale manufacturing use.

## Abstract

In the manufacturing process of electrical devices, ensuring the cleanliness of technical surfaces, such as direct bonded copper substrates, is crucial. An in-line monitoring system for quality checking must provide sufficiently resolved lateral data in a short time. UV hyperspectral imaging is a promising in-line method for rapid, contactless, and large-scale detection of contamination; thus, UV hyperspectral imaging (225–400 nm) was utilized to characterize the cleanliness of direct bonded copper in a non-destructive way. In total, 11 levels of cleanliness were prepared, and a total of 44 samples were measured to develop multivariate models for characterizing and predicting the cleanliness levels. The setup included a pushbroom imager, a deuterium lamp, and a conveyor belt for laterally resolved measurements of copper surfaces. A principal component analysis (PCA) model effectively differentiated among the sample types based on the first two principal components with approximately 100.0% explained variance. A partial least squares regression (PLS-R) model to determine the optimal sonication time showed reliable performance, with R2cv = 0.928 and RMSECV = 0.849. This model was able to predict the cleanliness of each pixel in a testing sample set, exemplifying a step in the manufacturing process of direct bonded copper substrates. Combined with multivariate data modeling, the in-line UV prototype system demonstrates a significant potential for further advancement towards its application in real-world, large-scale processes.