Quantitative nanoscopic imaging of adsorbent-aggregation-state dependent molecular binding cooperativity

Abstract

Adsorbent aggregation significantly influences the adsorption efficiency in applications such as pollutant removal in water treatment processes. However, elucidation of the fundamental relationship between the aggregation state of nanoscale adsorbents and their pollutant removal efficacy remains highly challenging using conventional ensemble-averaged measurements due to ubiquitous structural heterogeneities of bulk systems. This study investigates the impact of adsorbent clustering on the adsorption of a model water pollutant, Rhodamine B (RhB), on graphitic carbon nitride (GCN) using a quantitative super-resolution imaging technique, point accumulation for imaging in nanoscale topography (PAINT). By quantifying adsorption kinetics and thermodynamics of GCN particles categorized into individual nanoflakes, clusters, and large aggregates, we uncover distinct adsorption behaviors induced by the varying degrees of graphitization and π-conjugation in different aggregation state. Clusters exhibit slower desorption kinetics and higher adsorption affinity for RhB compared to small nanoflakes. Furthermore, we discover the existence and heterogeneity of binding cooperativity among RhB molecules, which are dependent on the adsorbent morphologies. These findings highlight the importance of controlling the aggregation behavior of adsorbent materials in the optimization of water treatment processes. The quantitative super-resolution imaging technique and associated analysis framework developed here can be extended to study other molecular binding processes beyond water treatment, with broad implications in various fields, ranging from catalyst poisoning and biological sensing to energy transport and conversion.