The role of the current waveform in mitigating passivation and enhancing electrocoagulation performance: A critical review

A novel combined system for efficient nitrate removal using a continuous flow electrocoagulation and sand filtration (FECF) reactor: Statistical analysis by Taguchi design

In this study, a new hybrid bench-scale electrocoagulation-sand filtration (FECF) reactor was developed for purifying nitrate-contaminated samples. Before and after electrochemical treatment, two sand filters were included in this continuous system to facilitate the purification procedure, and the contaminated water flows horizontally through the entire system according to a specific hydraulic gradient within the reactor, resulting in water purification. Significant improvement in treatment performance was observed due to the presence of metal hydroxides in the second filter media that were not fully involved in the electrocoagulation treatment. Energy dispersive X-ray (EDX) analysis was performed to detect metal hydroxide species in the sand media, and the need for filter regeneration was evaluated by monitoring changes in the system flow rate. Moreover, an evaluation of the effects of different factors including operating time, current intensity, initial pH, type of anode and cathode, initial nitrate concentration, hydraulic head level inside the reactor, number of electrodes, and NaCl electrolyte concentration on the performance of nitrate removal was conducted through the Taguchi design. Further, ANOVA analysis verified the accuracy of the predicted model, and the variables were classified based on their relative importance in the FECF process. According to the regression model, 97% of nitrates were removed with Al electrodes as anode and Fe as cathode, 70 min purification time, current intensity of 3 A, 100 mg/l initial nitrate concentration, pH 8, electrolyte concentration of 1 g/l, electrode number of 6, and 1.5 cm head level.

Determination of optimal operating conditions for AC-powered electrocoagulation process coupling green additive Tartaric Acid to remove Ni2+: Pyomo and RSM approach

A novel Python-based open-source optimization framework, namely Pyomo (Python optimization modeling objects), alongside a conventional optimization method, RSM (response surface methodology), was utilized to determine the optimal operating conditions of an alternating current-powered electrocoagulation (ACPE) process for nickel removal. In this regard, four mutable operating factors, current density (5-9 mA/cm²), initial nickel concentration (200-400 mg/L), initial pH of the solution (5-9), and electrolysis time (30-60 min), along with a fixed amount of an additional eco-friendly substance, Tartaric Acid (155 mg/L) were considered. Metal removal efficiency (OF₁) and operating costs (OF₂) were monitored and evaluated as objective functions with the aim of maximization and minimization, respectively. Experiments were conducted according to the central composite design (CCD), and validation outcomes established a reasonable agreement between the predicted models and the experimental data. The multi-objective optimization process yielded two sets of 30-optimal-solution obtained through Pyomo and RSM. Accordingly, the proposed solutions by the Pyomo were found to be more flexible and eclectic, supplying the local decision maker(s) with a diverse spectrum of optimal operating conditions. Adding TA was also effective in reducing electrical energy consumption by up to 46%.