Machine Learning Enhances LIBS Accuracy for Classifying Real Plastic Waste

Researchers applied machine learning to laser-induced breakdown spectroscopy (LIBS) to improve classification of common plastics under varying laser conditions. The study demonstrated that combining preprocessing with wavelength selection significantly increased test accuracy, achieving perfect classification on a limited set of real plastic waste samples. This approach highlights the potential for more reliable plastic waste sorting technologies.

Originally published by gnews