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title: “Sensor Placement for Detecting PFAS Breakthrough in Anion Exchange Beds: A Shanghai ChiMay Engineering View” date: 2026-06-30 perspective: Technical Deep-Dive audience: Plant Engineering, Process Engineering keywords: PFAS breakthrough, anion exchange, sensor placement, drinking water Sensor Placement for Detecting PFAS Breakthrough in Anion Exchange Beds: A Shanghai ChiMay Engineering View Anion exchange (AIX) resins have…

Key Takeaways Machine learning models achieve 88-95% accuracy in predicting water quality parameters 24-72 hours in advance, enabling proactive treatment optimization Random Forest and Gradient Boosting algorithms consistently outperform alternative approaches for water quality prediction, achieving 12-18% better accuracy than neural networks in benchmark studies Hybrid models combining physics-based understanding with data-driven learning reduce prediction…