질화알루미늄 나노분말의 자가 접착과 미세구조화 특성을 활용한 고효율 유수분리 소재 개발

Development of Highly Efficient Oil-Water Separation Materials Utilizing the Self-Bonding and Microstructuring Characteristics of Aluminum Nitride Nanopowders

The discharge of oily wastewater into water bodies and soil poses a serious hazard to the environment and public health. Various conventional techniques have been employed to treat oil-water mixtures and emulsions; Unfortunately, these approaches are frequently expensive, time-consuming, and unsatisfactory outcomes. Porous materials and adsorbents are commonly used for purification, but their use is limited by low separation efficiencies and the risk of secondary contamination. Recent advancements in nanotechnology have driven the development of innovative materials and technologies for oil-contaminated wastewater treatment. Nanomaterials can offer enhanced oil-water separation properties due to their high surface area and tunable surface chemistry. The fabrication of nanofiber membranes with precise pore sizes and surface properties can further improve separation efficiency. Notably, novel technologies have emerged utilizing nanomaterials with special surface wetting properties, such as superhydrophobicity, to selectively separate oil from oil-water mixtures or emulsions. These special wetting surfaces are promising for high-efficiency oil separation in emulsions and allow the use of materials with relatively large pores, enhancing throughput and separation efficiency. In this study, we introduce a facile and scalable method for fabrication of superhydrophobic-superoleophilic felt fabrics for oil/water mixture and emulsion separation. AlN nanopowders are hydrolyzed to create the desired microstructures, which firmly adhere to the fabric surface without the need for a binder resin, enabling specialized wetting properties. This approach is applicable regardless of the material's size and shape, enabling efficient separation of oil and water from oil-water mixtures and emulsions. The oil-water separation materials proposed in this study exhibit low cost, high scalability, and efficiency, demonstrating their potential for broad industrial applications.