This work evaluates the capacitive deionization (CDI) performance of optimized peanut shell-derived porous carbon (PSPC) electrodes fabricated in our previous work. Investigation and optimization of the impact of CDI process parameters i.e., applied voltage, salt initial concentration, and feed flowrate, on salt adsorption capacity (SAC) was conducted via a novel intelligent data-based approach including design-of-experiment (DOE), response surface-methodology (RSM), Sobol’s sensitivity analysis (SA), and genetic algorithm (GA). It was revealed that the SAC will be promoted as the voltage, salt initial concentration, and feed flowrate increase. The electrical voltage was found to be the most influential factor on SAC variation with more than 50 % effect. Process optimization via GA resulted the maximum SAC equal to 22.13 mg/g at the optimal conditions of electrical voltage = 1.6 V, salt initial concentration = 1500 mg/L, and feed flowrate = 27 mL/min. The PSPC electrode offered an appropriate long-term performance preserving 74 % of its capacity after 100 consecutive adsorption/regeneration cycles. Moreover, the adsorption kinetics followed the pseudo-first order pattern. This work uncovered the potential of intelligent data-based modeling and optimization techniques as a novel strategy for intensification of CDI process
