TY - JOUR
T1 - Ultimate jumping of coalesced droplets on superhydrophobic surfaces
AU - Yuan, Zhiping
AU - Gao, Sihang
AU - Hu, Zhi Feng
AU - Dai, Liyu
AU - Hou, Huimin
AU - Chu, Fuqiang
AU - Wu, Xiaomin
N1 - Publisher Copyright:
© 2020 Elsevier Inc.
PY - 2021/4
Y1 - 2021/4
N2 - Hypothesis: Jumping of coalesced droplets on superhydrophobic surfaces (SHSs) is widely used for enhanced condensation, anti-icing/frosting, and self-cleaning due to its superior droplet transport capability. However, because only a tiny fraction (about 5%) of the released excess surface energy during coalescence can be transformed into jumping kinetic energy, the jumping is very weak, limiting its application. Methods: We experimentally propose enhanced jumping methods, use machine learning to design structures that achieve ultimate jumping, and finally combine experiments and simulations to investigate the mechanism of the enhanced jumping. Finding: We find that a more orderly flow inside the droplets through the structure is the key to improve energy transfer efficiency and that the egg tray-like structure enables the droplet to jump with an energy transfer efficiency 10.6 times higher than that of jumping on flat surfaces. This energy transfer efficiency is very close to the theoretical limit, i.e., almost all the released excess surface energy is transformed into jumping kinetic energy after overcoming viscous dissipation. The ultimate jumping enhances the application of water droplet jumping and enables other low surface energy fluid such as R22, R134a, Gasoline, and Ethanol, which cannot jump on a flat surface, to jump.
AB - Hypothesis: Jumping of coalesced droplets on superhydrophobic surfaces (SHSs) is widely used for enhanced condensation, anti-icing/frosting, and self-cleaning due to its superior droplet transport capability. However, because only a tiny fraction (about 5%) of the released excess surface energy during coalescence can be transformed into jumping kinetic energy, the jumping is very weak, limiting its application. Methods: We experimentally propose enhanced jumping methods, use machine learning to design structures that achieve ultimate jumping, and finally combine experiments and simulations to investigate the mechanism of the enhanced jumping. Finding: We find that a more orderly flow inside the droplets through the structure is the key to improve energy transfer efficiency and that the egg tray-like structure enables the droplet to jump with an energy transfer efficiency 10.6 times higher than that of jumping on flat surfaces. This energy transfer efficiency is very close to the theoretical limit, i.e., almost all the released excess surface energy is transformed into jumping kinetic energy after overcoming viscous dissipation. The ultimate jumping enhances the application of water droplet jumping and enables other low surface energy fluid such as R22, R134a, Gasoline, and Ethanol, which cannot jump on a flat surface, to jump.
KW - ADAM
KW - Coalescence-induced droplet jumping
KW - Energy transfer efficiency
KW - Enhanced jumping
KW - Machine learning
KW - Superhydrophobic surface
UR - http://www.scopus.com/inward/record.url?scp=85098129906&partnerID=8YFLogxK
U2 - 10.1016/j.jcis.2020.12.007
DO - 10.1016/j.jcis.2020.12.007
M3 - Article
C2 - 33383432
AN - SCOPUS:85098129906
SN - 0021-9797
VL - 587
SP - 429
EP - 436
JO - Journal of Colloid and Interface Science
JF - Journal of Colloid and Interface Science
ER -