Deep learning-based transmembrane pulsed electro-chemisorption for improved energy efficacy of recovering ammonia from wastewater

The transmembrane electro-chemisorption technology for recovering ammonia from wastewater has gained growing attention for its chemicals saving and easy scalability. However, high energy consumption remains a challenge for its application. Herein, a deep learning (DL)-based transmembrane pulsed electro-chemisorption method was first developed to efficiently improve the energy efficacy of a stacked transmembrane electro-chemisorption (sTMECS) system for recovering ammonia. When the sTMECS system was adjusted from direct current power supply (DCPS) mode to default pulse power supply (PPS) mode with duty cycle of 50 ​%, the specific energy consumption ( SEC ) for recovering ammonia from synthetic wastewater decreased from 144.5 ​kWh/kg N to 36.1 ​kWh/kg N. Furthermore, a backpropagation neural network (BPNN) model was constructed and trained using experimental datasets of the sTMECS system, and an intelligent dynamic strategy for adjusting the duty cycle was proposed. The SEC for recovering ammonia from real urine under intelligent PPS mode was 18.9 ​kWh/kg N, showing reductions of 80.7 ​% and 23.1 ​% compared to DCPS mode and default PPS mode, respectively. Therefore, this study provides a new way for recovering ammonia from wastewater with relatively low energy consumption via combining the artificial intelligence technologies with the present ammonia-recovering methods, which is also conducive to reducing the carbon footprint. • A DL-based pulsed electro-chemisorption method was developed to enhance energy efficacy of recovering ammonia from wastewater. • Switching the sTMECS system from DCPS mode to PPS mode improved energy efficacy of recovering ammonia. • The BPNN model was constructed and trained using experimental datasets of the sTMECS system. • The intelligent dynamic strategy for adjusting duty cycle of PPS mode was proposed. • Its validity for enhancing energy efficacy was verified by recovering ammonia from real urea.