Microplastic Detection and Recognition System Enabled by Triboelectric Nanogenerator and Machine Learning Techniques

Key Points

• The aim is to develop a system for efficient detection of microplastic pollutants.
• Utilized triboelectric nanogenerator for energy harvesting and detection.
• Applied machine learning techniques for recognizing microplastic characteristics.
• Assessed the effect of different microplastic sizes and concentrations on detection accuracy.
• Achieved higher detection accuracy compared to traditional methods.
• Reduced processing time significantly through machine learning integration.
• Demonstrated cost-effectiveness in comparison to existing detection systems.