廃回路基板からのクエン酸浸出による持続可能な金属回収：応答曲面法と予測モデリング

Recycling printed circuit boards (PCBs) is crucial for reducing pollution, recovering valuable metals, and conserving resources. This study presents a green method for metal extraction from mobile phone PCBs using citric acid (C₆H₈O₇). The dissolution of Ag, Al, and Zn was examined in relation to variables such as pulp density, time, citric acid concentration, and temperature. The findings demonstrate the leaching of Ag, Al, and Zn is approximately 93%, 91% and 92%, respectively, under conditions of 1 M citric acid, a pulp density of 70 g L^-1, a temperature of 75 °C, and a mixing time of 120 minutes. Response surface methodology was employed to optimize the conventional hydrometallurgical method. Thus, utilizing citric acid as a green solvent not only enhances leaching efficiency but also offers a more sustainable alternative for the recovery of valuable metals from mobile PCBs. To further enhance prediction accuracy, multiple machine learning models were evaluated using process data. Among these, polynomial regression achieved the best performance (R ² = 1.000; RMSE ≈ 0), effectively capturing nonlinear relationships between parameters and silver recovery. This integration of experimental optimization and data driven modeling confirms citric acid as a sustainable lixiviant for efficient silver recovery from PCBs, reducing reliance on inorganic acids and environmental impact. It also demonstrates the effectiveness of polynomial modeling in minimizing experimental effort and enhancing leaching efficiency.