Advanced Approaches to Acid Leaching Optimization of Copper from Printed Circuit Board Wastewater Sludge

The most challenging issue associated with recycling the sludge generated from printed circuit boards (PCBs) is the separation of copper (Cu) using different leaching methods. The aim is to mitigate environmental impacts while effectively reclaiming valuable resources. The goal was to enhance the acid leaching process by carefully adjusting sulfuric acid concentrations, liquid-to-solid ratios, and leaching periods to maximize copper extraction from PCB waste. The research utilized an innovative approach that integrated a factorial experimental design with multiple linear regression (MLR) and sophisticated analysis of variance (ANOVA) to thoroughly evaluate the intricate interactions among these essential components. Furthermore, the study implemented predictive analytics to enhance both accuracy and efficiency, while also refining process parameters. Therefore, we found that mean square error (MSE) for MLR is better than the factorial design (FD) and has a good result. The results were impressive, exhibiting considerable improvements in leaching efficacy with an R-squared ($\mathrm{R}^2$) value of 87.58\%, an adjusted R-squared of 84.33\%, and a minimal MSE of 1.02 highlighting the strength of the reanalysis. MLR not only improved predicted accuracy but also provide deeper statistical formal validation technique. Future research areas include applying these enhanced procedures to a larger spectrum of e-waste materials and diving deeper into the environmental effects of leachate byproducts. The study also advises the incorporation of machine learning models to further optimize leaching operations in real-time, potentially revolutionizing recycling procedures in the electronics industry and driving a shift towards a more sustainable and economically practical circular economy.