A 3D Cryogel Filter for Oily Wastewater with Metal Ion Fluorosensing Properties

This work presents the development of poly(sodium) acrylate (PSA)-based nanocomposite cryogels for the effective purification of multicomponent oily wastewater and the simultaneous indication of the presence of heavy metal ions, through gravity-driven filtration. Detailed studies prove that the purification process is mainly attributed to PSA which presents underwater superoleophobicity, necessary for water-oil separation, and contains the appropriate functional groups for the effective adsorption of the methylene blue cationic dye and of the metal cations. On the other hand, the sensing properties are attributed to the graphitic carbon nitride nanosheets (CNNs), present as nanofillers of the composite filter, which modulate their fluorescence upon interaction with the studied metal ions. Although the different loadings of CNNs into the PSA matrix barely affect any of the pollutants' separation efficiencies, reaching values higher than 97% in all cases, their fluorescence-based detection can be significantly altered. Through the optimization of the CNN concentration within the cryogel (3% w/w), sufficiently low amounts of Hg2+ and Cu2+ ions (i.e., 3 mg L-1 for 100 mL of feed solution) can be detected upon the gravity-driven filtration of wastewater and the subsequent monitoring of the evolution of the nanocomposite cryogel's fluorescence intensity, while for the Pb2+ ions a significantly lower detection performance is achieved. Focusing on Hg2+ ions, we prove that their adsorption by the cryogel is dominated by the Na+- heavy metal ion exchange and that the material can be regenerated through the recovery of the adsorbed ions via the interaction with NaOH(aq) solution. The material maintains its excellent separation performance in diverse recovery and reuse cycles. The work presented herein opens an ample space for the development of CNN-based multifunctional materials for the cost- and energy-efficient integrated water treatment and quality monitoring process.