Dynamical Adsorption Behavior Prediction of Dried Tobacco Leaf Heterogeneous Interfaces through Simulation and Image Recognition Techniques

The process of spraying water and flavorings on dry tobacco is an important factor in the industrial environment and product quality. Tobacco as a complex porous fiber material, the interfacial transfer process of water is complex. In this study, machine learning and image recognition techniques were utilized to quickly obtain the structural parameters of the tobacco surface and construct a cellular structure model of the tobacco surface. In situ observation of the droplet impact spreading process was carried out using a high-speed camera to explore the droplet dissipation dynamics on different surfaces. And the competing processes of droplet wetting and evaporation under the influence of surface microstructure were determined by combining experimental studies and finite element simulation calculations. Based on the characteristics of tobacco pore size distribution, the infiltration under gas-liquid two-phase action was transformed into single-phase flow transfer under capillary force, and the continuous droplet infiltration process was simulated. A parallel artificial membrane permeability measurement method of bionic tobacco waxy layer was constructed for the screening of spray dosing copenetrant. This study brings new insights into the wetting of porous fibrous materials and is important for exploring the wetting process and additive development process influenced by the microstructure.