This work presented the results of an experimental study of dynamics of emulsion complex composition droplets under laser irradiation. The oil-in-water emulsion consisted of liquid paraffin droplets containing magnetite nanoparticles and was placed in an aqueous solution of the surfactant. The magnetite nanoparticles had characteristic dimensions of 10−8 m, which correspond to the dimensions of molecular motors in living cells. For all emulsion droplets, motion in transitional and normal diffusive modes was observed. The effective kinetic temperature of emulsion droplets was 3.5 × 103 eV and was exceeded the temperature of thermal motion of the medium molecules, 0.03 eV. Experimentally observed active Brownian motion of emulsion droplets was a result of intra-droplet motion of magnetite nanoparticles absorbing laser irradiation. Laser irradiation caused the magnetite nanoparticle heating, which generated a thermophoretic force. As a result of viscous friction forces, the nanoparticles transferred momentum to the emulsion droplet, causing its motion.

A physics-based mathematical model is developed for interfacial mass transfer in turbulent gas–liquid media. The formulation derives characteristic bubble-scale quantities governing the volumetric mass-transfer coefficient $k_{L}a$ from the bubble response to turbulent velocity fluctuations. Bubble translation is described by a reduced equation of motion that retains the added-mass contribution and quasi-steady drag. Kolmogorov-type estimates are used to characterize turbulent fluctuations, and the fluctuation length governing the mean bubble–liquid slip velocity is selected by maximizing the bubble response. A characteristic bubble diameter is estimated from a turbulent–capillary balance, while the liquid-side coefficient is evaluated using a Higbie-based finite-exposure formulation, with the characteristic exposure time related to the bubble diameter and the critical slip velocity. The resulting analytical relation expresses $k_{L}a$ in terms of gas holdup, molecular diffusivity, drag coefficient, liquid density, surface tension, turbulent energy dissipation rate, and a bubble-size factor. In its bubble-size-based form, the model predicts the scaling $k_{L}a\propto {\epsilon }^{7/10}$, providing a mechanistic interpretation of the approximately $0.7$ power-input exponent encountered in established empirical correlations. Consistency is assessed through comparison with representative literature correlations. The same analytical relation is additionally evaluated using hydrodynamic quantities supplied by an illustrative CFD calculation, demonstrating how spatially non-uniform flow information can be converted into distributed mass-transfer estimates. The proposed formulation provides a compact and physically interpretable route from bubble-scale dynamics to apparatus-scale mass-transfer prediction in gas–liquid contactors, bioreactors, and related non-equilibrium dispersed systems.