Performance prediction of electrochemical degradation of monochloroacetamide (MCAcAm) using machine learning models

Key Points

• Electrochemical degradation performance was successfully predicted using machine learning models, improving accuracy in assessments.
• Key metrics reveal that machine learning can effectively model the degradation of monochloroacetamide with notable precision.
• The analysis employed advanced machine learning approaches to predict the degradation processes of monochloroacetamide.
• Results may enable better environmental processes, though further validation across various conditions is needed.