Prediction of the Lotus Effect on Solid Surfaces by Machine Learning
Xiao He
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
Search for more papers by this authorKaihua Zhang
School of Chemistry, Beihang University, Beijing, 100191 P. R. China
Search for more papers by this authorXianghui Xiong
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
Search for more papers by this authorYuepeng Li
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
Search for more papers by this authorXizi Wan
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
Search for more papers by this authorZijia Chen
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
State Key Laboratory of Metastable Materials Science and Technology (MMST), Yanshan University, Qinhuangdao, 066004 P. R. China
Search for more papers by this authorYixuan Wang
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
Search for more papers by this authorXuetao Xu
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
Search for more papers by this authorMingqian Liu
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
Search for more papers by this authorCorresponding Author
Ying Jiang
School of Chemistry, Beihang University, Beijing, 100191 P. R. China
Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, 100191 P. R. China
E-mail: [email protected]; [email protected]
Search for more papers by this authorCorresponding Author
Shutao Wang
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
E-mail: [email protected]; [email protected]
Search for more papers by this authorXiao He
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
Search for more papers by this authorKaihua Zhang
School of Chemistry, Beihang University, Beijing, 100191 P. R. China
Search for more papers by this authorXianghui Xiong
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
Search for more papers by this authorYuepeng Li
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
Search for more papers by this authorXizi Wan
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
Search for more papers by this authorZijia Chen
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
State Key Laboratory of Metastable Materials Science and Technology (MMST), Yanshan University, Qinhuangdao, 066004 P. R. China
Search for more papers by this authorYixuan Wang
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
Search for more papers by this authorXuetao Xu
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
Search for more papers by this authorMingqian Liu
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
Search for more papers by this authorCorresponding Author
Ying Jiang
School of Chemistry, Beihang University, Beijing, 100191 P. R. China
Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, 100191 P. R. China
E-mail: [email protected]; [email protected]
Search for more papers by this authorCorresponding Author
Shutao Wang
CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
E-mail: [email protected]; [email protected]
Search for more papers by this authorAbstract
Superhydrophobic surfaces with the “lotus effect” have wide applications in daily life and industry, such as self-cleaning, anti-freezing, and anti-corrosion. However, it is difficult to reliably predict whether a designed superhydrophobic surface has the “lotus effect” by traditional theoretical models due to complex surface topographies. Here, a reliable machine learning (ML) model to accurately predict the “lotus effect” of solid surfaces by designing a set of descriptors about nano-scale roughness and micro-scale topographies in addition to the surface hydrophobic modification is demonstrated. Geometrical and mathematical descriptors combined with gray level cooccurrence matrices (GLCM) offer a feasible solution to the puzzle of accurate descriptions of complex topographies. Furthermore, the “black box” is opened by feature importance and Shapley-additive-explanations (SHAP) analysis to extract waterdrop adhesion trends on superhydrophobic surfaces. The accurate prediction on as-fabricated superhydrophobic surfaces strongly affirms the extensionality of the ML model. This approach can be easily generalized to screen solid surfaces with other properties.
Conflict of Interest
The authors declare no conflict of interest.
Open Research
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Supporting Information
| Filename | Description |
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| smll202203264-sup-0001-SuppMat.pdf3.3 MB | Supporting Information |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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