The complexity in droplet evaporation
Date: Thu 9 Jul 2015, 14:00 - 15:00
Location: SEMS Seminar Room, 3rdfloor
Guest Speaker: Dr. Fei Duan, NanyangTechnological University, Singapore
Droplet evaporation has received more attention since it is related to the general natural process to balance the water transport in our environment, and the applications including concentrating chemicals, coating, printing, spraying, drying, painting, biomedical sampling, etc. As a droplet changes from liquid phase to its vapor phase, there are issues that we cannot exactly understand. A
recent review study shows that liquid evaporation rates, occurring at nominally the same experimental conditions, have been reported by the different investigators to differ several orders of magnitude. The variation suggests the complexity in the droplet evaporation. In our single droplet steady-state evaporation, the temperature discontinuity was found at the interfacial liquid and vapor sides while the temperature gradient was found along the evaporation interface if the evaporation rate was high. The Marangoni flow can be introduced by the interfacial temperature variation. The surface flow can transport and redistribute the energy at the free interface. The local evaporation can also be affected accordingly. We have developed the statistical rate theory approach to predict the evaporation flux from liquid phase to vapor phase. The approach introduces the concept of transition probabilities defined in quantum mechanics and the Boltzmann definition of entropy. The theory was managed to predict the evaporation conditions and some thermodynamic properties. The Marangoni flow pattern has been measured with the correction method we developed. Additionally, the drying of nanofluids droplets has been investigated. The interesting spreading and evaporation dynamics were found in the nanofluid droplets. The experiments demonstrated the dried patterns such as finger, coffee ring, uniform coverage and the combined structures. We have applied the kinetic Monte Carlo model and the diffusion-limited aggregation simulation to explain the self- assemble processes.
|Contact:||Dr Ettore Barbieri & Dr Yury Korolev|