As a surface functional material,super-hydrophobic coating has great application potential in wind turbine blade anti-icing,self-cleaning and drag reduction.In this study,ZnO and SiO2 multi-scale superhydrophobic coat...As a surface functional material,super-hydrophobic coating has great application potential in wind turbine blade anti-icing,self-cleaning and drag reduction.In this study,ZnO and SiO2 multi-scale superhydrophobic coatings with mechanical flexibility were prepared by embedding modified ZnO and SiO2 nanoparticles in PDMS.The prepared coating has a higher static water contact angle(CA is 153°)and a lower rolling angle(SA is 3.3°),showing excellent super-hydrophobicity.Because of its excellent superhydrophobic ability and micro-nano structure,the coating has good anti-icing ability.Under the conditions of−10C and 60%relative humidity,the coating can delay the freezing time by 1511S,which is 10.7 times slower than the normal freezing time.More importantly,due to the mechanical properties provided by SiO2 and the synergistic effect of micro-nano particles,the coating has excellent mechanical durability.After 10 wear tests,the contact angle of the coating is still as high as 141°and the rolling angle is 6.8°.This research provides a theoretical reference for the preparation of a mechanically stable coating with a simple preparation process,as well as a basic research on the anti-icing behavior of the coating.展开更多
Crystal structure prediction algorithms have become powerful tools for materials discovery in recent years, however, they are usually limited to relatively small systems. The main challenge is that the number of local...Crystal structure prediction algorithms have become powerful tools for materials discovery in recent years, however, they are usually limited to relatively small systems. The main challenge is that the number of local minima grows exponentially with the system size. In this work, we proposed two crossover-mutation schemes based on graph theory to accelerate the evolutionary structure searching by automatic decomposition methods. These schemes can detect molecules or clusters inside periodic networks using quotient graphs for crystals, and the decomposition can dramatically reduce the searching space. Sufficient examples for test, including the high-pressure phases of methane, ammonia, MgAl2O4 and boron, show that these new evolution schemes can significantly improve the success rate and searching efficiency compared with the standard method in both isolated and extended systems.展开更多
基金funded by the Changsha University of Science and Technology Research and Innovation Project(CX2019SS21)the National Energy Group Technology Innovation Project(HJLFD-QTHT-2019-09).
文摘As a surface functional material,super-hydrophobic coating has great application potential in wind turbine blade anti-icing,self-cleaning and drag reduction.In this study,ZnO and SiO2 multi-scale superhydrophobic coatings with mechanical flexibility were prepared by embedding modified ZnO and SiO2 nanoparticles in PDMS.The prepared coating has a higher static water contact angle(CA is 153°)and a lower rolling angle(SA is 3.3°),showing excellent super-hydrophobicity.Because of its excellent superhydrophobic ability and micro-nano structure,the coating has good anti-icing ability.Under the conditions of−10C and 60%relative humidity,the coating can delay the freezing time by 1511S,which is 10.7 times slower than the normal freezing time.More importantly,due to the mechanical properties provided by SiO2 and the synergistic effect of micro-nano particles,the coating has excellent mechanical durability.After 10 wear tests,the contact angle of the coating is still as high as 141°and the rolling angle is 6.8°.This research provides a theoretical reference for the preparation of a mechanically stable coating with a simple preparation process,as well as a basic research on the anti-icing behavior of the coating.
基金support from the National Natural Science Foundation of China (Grant Nos. 11974162 and 11834006)the National Key R&D Program of China (Grant Nos. 2016YFA0300404)the Fundamental Research Funds for the Central Universities.
文摘Crystal structure prediction algorithms have become powerful tools for materials discovery in recent years, however, they are usually limited to relatively small systems. The main challenge is that the number of local minima grows exponentially with the system size. In this work, we proposed two crossover-mutation schemes based on graph theory to accelerate the evolutionary structure searching by automatic decomposition methods. These schemes can detect molecules or clusters inside periodic networks using quotient graphs for crystals, and the decomposition can dramatically reduce the searching space. Sufficient examples for test, including the high-pressure phases of methane, ammonia, MgAl2O4 and boron, show that these new evolution schemes can significantly improve the success rate and searching efficiency compared with the standard method in both isolated and extended systems.