Ultrasound-enhanced catalytic degradation of simulated dye wastewater using waste printed circuit boards: catalytic performance and artificial neuron network-based simulation.

Abstract

Recent developments of heterogeneous advanced oxidation for refractory organic contaminants and catalysts made of solid waste have attracted much attention. In this work, waste printed circuit board (wPCB) was used for catalytic degradation of simulated textile wastewater enhanced by ultrasound. Catalytic degradation of rhodamine B (RhB) and methylene blue (MB) was conducted in the presence of H2O2. Effect of ultrasound, wPCB, H2O2, pH, and dye concentration was investigated by single factor experiments. The growing catalytic efficiency was determined by ultrasound. The removal efficiency of MB and RhB are influenced by wPCB, H2O2, pH, and dye concentration. Degradation efficiency is accelerated with increasing wPCB dosage and H2O2 and decreasing dye concentration. Effective degradation of MB and RhB is obtained under broader pH region, attractively at neutral pH. Under optimal conditions, MB removal reaches 98.83% at 90min while RhB removal reaches 99.57% at 80min. Hydroxyl radicals play an important role in catalytic process. Tentative mechanism for catalytic degradation of MB and RhB are discussed based on multiple characterizations. Superior reusability of wPCB proves that wPCB is highly durable catalyst. Due to low cost and high efficiency, wPCB is attractive as effective catalyst for treatment of organic wastewater. Artificial neuron network-based (ANN) simulation, as a widely used artificial intelligence algorithm, was one of preferred methods for the wastewater treatment due to its unique properties in solving complex processes. An ANN model was designed for the prediction of the performance of ultrasound-enhanced catalytic degradation with a high R value (0.99).