Anionic COF Aerogels for Selective Pollutant Removal and Ultrasensitive SERS Detection

Abstract The simultaneous removal and real‐time monitoring of organic pollutants in complex water matrices remains challenging due to interference from coexisting substances and limitations in detection sensitivity. Here, an anionic covalent organic framework (COF)‐based aerogel (denoted as CCGA) is presented with both excellent selectivity and ultrahigh surface‐enhanced Raman scattering (SERS) detection sensitivity. The hierarchical architecture of CCGA synergistically integrates macroporous graphene scaffolds with micro‐mesoporous COF channels, facilitating rapid and selective capture of cationic dyes (>92% removal efficiency) via π–π stacking and electrostatic interactions, while exhibiting negligible affinity for anionic counterparts. This aerogel‐based enrichment strategy enables SERS detection of trace pollutants down to 1.65 × 10 ⁻⁵ mg mL ⁻¹ for rhodamine B (RhB) and 2.27 × 10 ⁻⁶ mg mL ⁻¹ for malachite green (MG). Furthermore, the heterojunction reduces the bandgap of graphitic carbon nitride and promotes visible‐light‐driven photocatalytic degradation, allowing self‐regeneration of the aerogel across nine cycles. Demonstrating practical applicability, the CCGA exhibits versatility in addressing complex cationic pollutants and operates effectively within real wastewater matrices via a portable filtration system. This work advances multifunctional material design by integrating selective adsorption, molecular‐level detection, and solar‐driven regeneration strategies, presenting a scalable approach for next‐generation water remediation technologies.