Selective recovery of copper from copper tailings and wastewater using chelating resins with bis-picolylamine functional groups

Industrial and mining wastewater, along with copper tailings, are typically highly acidic and contain copper and other heavy metals, which may contaminate and damage the environment. Copper (Cu) is, however, a valuable metal, making its removal and recovery from such wastewater and tailings environmentally and economically advantageous. Chelating ion exchange resins featuring bis-picolylamine functional groups are especially suitable for application requiring selective recovery of Cu(II) from highly acidic media. In this study, and for the first time, the kinetics, binding capacity and selectivity of Lewatit MDS TP 220 chelating resin towards Cu(II) are reported. The resin was characterized by Zeta potential, scanning electron microscope (SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). Factors including pH, initial concentration, contact time, temperature, and selectivity were investigated to assess the adsorption performance of the chelating resin. The adsorption kinetics tests revealed fast adsorption within the first 5-30 min and fitted the pseudo-second-order model, signifying chemisorption process. The adsorption isotherm followed the Langmuir model, implying monolayer adsorption process. The maximum adsorption capacity (qm) for Cu(II) determined by the Langmuir model was 103.9 mg/g. The adsorption thermodynamics showed an endothermic and spontaneous adsorption. FTIR and XPS studies suggested coordination or chelation as the possible adsorption mechanism. Lewatit MDS TP 220 exhibited excellent Cu(II) adsorption, desorption with 2 M ammonium hydroxide (NH4OH), and selectivity in multi-metal ions solution. Additionally, the resin demonstrated excellent reusability after five regeneration steps. This chelating resin is a potential adsorbent for effective and recurrent recovery of Cu(II) from copper tailings and wastewater, thereby contributing to environmental remediation.

Shape Memory Respirator Mask for Airborne Viruses

The emergence of COVID-19 has spurred demand for facemasks and prompted many studies aiming to develop masks that provide maximum protection. Filtration capacity and fit define the level of protection a mask can provide, and the fit is in large part determined by face shape and size. Due to differences in face dimensions and shapes, a mask of one size will not be likely to fit all faces. In this work, we examined shape memory polymers (SMPs) for producing facemasks that are able to alter their shape and size to fit every face. Polymer blends with and without additives or compatibilizers were melt-extruded, and their morphology, melting and crystallization behavior, mechanical properties, and shape memory (SM) behavior were characterized. All the blends had phase-separated morphology. The mechanical properties of the SMPs were modified by altering the content of polymers and compatibilizers or additives in the blends. The reversible and fixing phases are determined by the melting transitions. SM behavior is caused by physical interaction at the interface between the two phases in the blend and the crystallization of the reversible phase. The optimal SM blend and printing material for the mask was determined to be a polylactic acid (PLA)/polycaprolactone (PCL) blend with 30% PCL. A 3D-printed respirator mask was manufactured and fitted to several faces after being thermally activated at 65°C. The mask had excellent SM and could be molded and remolded to fit a variety of facial shapes and sizes. The mask also exhibited self-healing and healed from surface scratches.