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Updated: Jun 27, 2026

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Cross-Contamination Identification of Additive Manufacturing Metal Powders Using Spatially Confined Particle-Flow

Leiyi Ding1, Dan Feng1, Yinghao Wang1

  • 1Analytical & Testing Center, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.

Sensors (Basel, Switzerland)
|June 26, 2026
PubMed
Summary

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This summary is machine-generated.

This study introduces a new method using Laser-Induced Breakdown Spectroscopy (LIBS) to detect cross-contamination in metal powders for additive manufacturing. The technique improves stability and accuracy for online powder quality monitoring.

Area of Science:

  • Materials Science
  • Analytical Chemistry
  • Additive Manufacturing

Background:

  • Laser-induced breakdown spectroscopy (LIBS) is promising for metal powder quality monitoring.
  • Challenges include particle splashing and plasma instability in direct LIBS analysis of flowing powders.

Purpose of the Study:

  • To develop an integrated framework for identifying cross-contamination in additive manufacturing metal powders.
  • To enhance the stability and reliability of LIBS analysis for flowing powders.

Main Methods:

  • A stable powder stream was created using vibratory feeding and flow focusing.
  • Cylindrical spatial confinement was achieved using a hollow quartz tube.
  • Spectra underwent outlier removal, baseline correction, and normalization.
Keywords:
additive manufacturingcross-contaminationlaser-induced breakdown spectroscopy (LIBS)machine learningmetal powdersonline quality monitoring

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  • Principal Component Analysis (PCA) and machine learning models were used for classification.

    • Main Results:

    • LIBS spectra showed distinct distributions based on contamination levels.
    • Spectral differences increased with higher contamination.
    • Machine learning models achieved high accuracy, with PCA-SVM-RBF excelling at low concentrations.
    • Classification accuracy was best at higher contamination levels, with continuous transitions observed at lower levels.

    Conclusions:

    • The proposed spatially confined particle-flow LIBS framework effectively identifies cross-contamination in metal powders.
    • This method offers a feasible route for online powder quality monitoring in additive manufacturing.