Cellulose nanocrystal regulated ultra-loose, lightweight, and hierarchical porous reduced graphene oxide hybrid aerogel for capturing and determining organic pollutants from water

The ultra-loose and lightweight reduced graphene oxide/cellulose nanocrystal (rGO/CNC) hybrid aerogel was developed by hydrothermal method. Owing to the dispersibility and plentiful chemical groups of CNC, a variety of rGO/CNC hybrid aerogels with tunable dimensions were formed, thereby overcoming the limitation of size control of rGO aerogels by hydrothermal treatment. Moreover, rGO/CNC hybrid aerogel was endowed with ample functional groups, ultra-loose structure, and abundant micro/meso-pores, which allowed the composite exhibit excellent performance for capturing organic pollutants. With the use as solid-phase microextraction (SPME) coating to extract and determine polycyclic aromatic hydrocarbons (PAHs), the rGO/CNC composites presented superior extraction capacities for PAHs than pristine rGO and commercial SPME coatings due to the synergistic effects of 7C-7C stacking, chemical groups bonding, and fast internal transfer in thick rGO/CNC layers. The proposed analytical method presented good linearity (R2 <= 0.9988) in concentration of 0.1-2000 ng L-1, low limits of detections (0.012-0.076 ng L-1), and excellent reproducibility. Finally, the proposed method was applied to determine PAHs from real water, and obtained satisfactory recoveries. This study proposed a novel method for regulating rGO aerogel structures, and confirmed its effectiveness for efficiently capturing organic pollutants from water.

Automated summary

The ultra-loose and lightweight rGO/CNC hybrid aerogel with tunable dimensions was developed by hydrothermal method. The hybrid aerogel exhibited excellent performance for capturing organic pollutants due to its ample functional groups, ultra-loose structure, and abundant micro/meso-pores. As a solid-phase microextraction coating, the rGO/CNC composites demonstrated superior extraction capacities for PAHs with good linearity, low limits of detections, and excellent reproducibility.