Capture and removal of nanoplastics using ZIF-derived defective nanoframework: Structure-performance correlation, theoretical calculation and application

Nanoplastics, as a novel pollutant, are widely found in the environment and water, which also can be migrated to vegetables and fruits through irrigation water and the growing process, posing threat to the human health. In this study, post-modification strategy was implemented to synthesize a series of fine-tuning hierarchically porous ZIF-derived nanoframework (Zn-Co-Ni-ZIF, Zn-Co-TA-ZIF and ZIF67-Ni-ZIF) with various morphologies and structures to investigate the relationship between the polystyrene nanoplastics (PS-NPs) adsorption performance and structure property. The correlation degree between PS-NPs adsorption property and structure parameter followed the order of the intensity of Co2p > the intensity of M-N > the number of linker deficiencies > crystal defect > zeta potential. The gray models (GM) (1,1) between adsorption capacity and evaluation items were successfully established (C < 0.342; RSD < 18.108 %) but zeta potential. A highly linked association (R 2 = 0.9561) between the PV meso /PV micro and equilibrium constants k t 2 may be discovered. The combined findings from experimental analysis and Density Functional Theory calculations demonstrated that the adsorption capacity of adsorbents for PS-NPs was greatly enhanced by the introduction of additional defects and the reinforcement of adsorbent-adsorbate interactions, including electrostatic and coordination interactions. Among the selected materials, Zn-Co-ZIF and Zn-Co-Ni-(60 mg)-ZIF exhibited better resistance to acid, alkali, and salt. Moreover, the PS-NPs removal efficiency of Zn-Co-ZIF and Zn-Co-Ni(60 mg)-ZIF were > 83.55 % and > 87.80 %, respectively, in irrigation water, watermelon, strawberry, and carrot, meeting the environmental and food safety. Therefore, this work provides valuable insights into the modification of MOFs to improve the elimination of micropollutants in water, fruit, vegetable, as well as a comprehensive comprehension of the correlations between structure and performance.