Beyond conventional Fenton: AI-assisted Photoelectro-Fenton treatment of real pharmaceutical wastewater with detoxification and sludge valorization
Separation and Purification Technology, cilt.416, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 416
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.seppur.2026.139940
- Dergi Adı: Separation and Purification Technology
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Chemical Abstracts Core, Chimica, Compendex, INSPEC, Academic Search Ultimate (EBSCO), Engineering Source (EBSCO)
- Anahtar Kelimeler: Artificial intelligence modeling, Circular economy, Fenton, Micropollutant degradation, Real pharmaceutical wastewater
- Yıldız Teknik Üniversitesi Adresli: Evet
Özet
This study evaluated Electro-Fenton (EF) and Photoelectro-Fenton (PEF) treatment of real pharmaceutical wastewater by integrating process optimization, pharmaceutical monitoring, acute toxicity, repeated-cycle stability, sludge reuse, energy assessment, and explainable machine learning. Response Surface Methodology identified optimum PEF conditions of pH 2.95, 0.40 A, 94.5 mM H2O2, and approximately 54 min, achieving 96.1% COD and 87.9% color removal. After 75 min of PEF treatment, the UV–Vis signal attributed to diclofenac (DCF) could no longer be reliably distinguished from the background matrix, while the signal attributed to carbamazepine (CBZ) decreased by approximately 98% after 120 min. The corresponding EF removals were approximately 80% and 91%, respectively. PEF reduced integrated acute toxicity by 87.5% and maintained Daphnia magna immobilization below 10% at wastewater proportions of 50% or lower. Six machine-learning algorithms were evaluated using 100 runs and five-fold cross-validation. Artificial Neural Network provided the strongest overall performance for three responses, while grouped permutation feature importance identified reaction time, followed by pH and current, as the most influential predictive variables. Mean COD removals of 91.0% for EF and 95.8% for PEF were maintained over five treatment cycles. Acid-solubilized sludge remained catalytically active over five reuse cycles, with recovered‑iron Photo-Fenton achieving mean COD and color removals of 77.0% and 58.8%, respectively. Specific energy consumption ranged from 1.217 to 9.424 kWh kg−1 COD for EF and from 64.856 to 228.011 kWh kg−1 COD for PEF. PEF provided the highest treatment and detoxification performance, while recovered iron enabled partial sludge valorization.