Evaluating and predicting the stickiness regime of drying droplets across drying conditions

One of the key reasons spray drying yields high-quality powders is that it promotes particle agglomeration. This occurs thanks to sticking collisions between drying droplets and/or dry fine particles. Unfortunately, the effect of drying conditions on the stickiness regime is not yet studied in detail, which makes it harder to steer agglomeration in practice. This research therefore aims to unravel the effect of relative humidity and temperature on the stickiness regime and to predict the stickiness regime across these drying conditions. A sessile single droplet drying platform was employed to perform drying and binary collision studies at different relative humidities and temperatures. Subsequently, a predictive diffusion model was verified with high-speed imaging and high-resolution thermography and used for connecting surface properties and the stickiness regime. Increased relative humidity and decreased temperature led to an increase in drying time and thus later locking point. The stickiness regime shifted with locking point at higher relative humidities but was not prolonged. Finally, the model could successfully correlate droplet surface properties (T_g/T) to collision outcomes and could thus predict the stickiness regime based on locking point and surface properties. This approach provides a new general framework for determining the stickiness regime of single droplets.