In many real-world problems, it is essential to predict the binding rate of small molecules or particles in the bulk solution to an immobilized target binding site at an interface, a typical scenario in biosensing, cell biology, drug delivery, heterogeneous catalysis, reactions on electrodes and membranes, etc. Collision theory, transition-state theory, quantum mechanics, molecular dynamic simulations, and recently machine learning have been applied in predicting reaction kinetics. However, it remains challenging to predict reaction kinetics in diluted solutions such as biomolecular binding in water . In diluted solutions, molecules display continuous and random Brownian motion , a phenomenon referred to as diffusion, a fundamental process of reaction kinetics and fluid dynamics in biosensing , cell biology , environmental , industrial chemical manufacturing , and drug delivery . Recent methods and instrument developments such as single-molecule fluorescence microscopy have enabled studying diffusion at the single-molecule level . It is a good time to develop and test new theories to predict the reaction kinetics of diffusive interactions in solutions.