Statistical Optimization of Heavy Metal (Cu2+ and Co2+) Extraction from Printed Circuit Boards and Mobile Batteries Using Chelation Technology

Electronic waste has emerged as one of the fastest growing segments of the solid waste stream in the last two decades because of the greater consumption and obsolescence rates of electronic products. Significant content of metals and polymers present in e-waste may affect the ecosystem and human health if treated inappropriately using primitive recycling methods. Several studies have been reported in the literature for the recovery of metals from e-waste; however, limitations associated with ongoing methods incited this study to move toward modern approaches based on green chemistry principles. The present study is a pioneer effort to employ a novel green technology based on a unique combination of chelation–dechelation concepts to extract metals from printed circuit boards and mobile batteries. The applicability of response surface methodology (RSM) was explored to investigate the mutual interaction effect of process parameters and to provide an improved quality of information. Statistical optimization of the extraction process was performed by coupling of Box–Behnken design and central composite design matrices with RSM. Nearly 85.3% Cu²⁺ and 86.2% Co²⁺ recovery was predicted at the center level of design matrices using quadratic regression models for the respective metals. Maximum ±4% deviation was observed between experimental and predicted extraction efficiency. The high values of regression coefficients (R² = 0.994 for Cu²⁺ recovery and R² = 0.998 for Co²⁺ recovery) indicated that >99% of response variability could be explained by regression models. Relatively lower p-values (<0.0001) and coefficient of variation (<2.8%) indicate the adequacy of the proposed models. The desirability function approach was employed to localize the optimum process parameters, and ramp functions were drawn for the set of optimal points. A well-defined optimal region was identified to maximize the metal extraction with desirability >0.95. Characterization of raw material and residues corroborated the significant extraction of metals. Also, recovered chelating agent was successfully employed in subsequent extraction cycles, which fortifies the concept of a zero-waste technology. The proposed design correlations may prove to be a useful tool in designing pilot and commercial plants for extraction of heavy metals using environmentally friendly chelation technology.