Machine-Learning Approach in Prediction of the Wettability of a Surface Textured with Microscale Pillars-Reference-Cited by-同舟云学术

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Machine-Learning Approach in Prediction of the Wettability of a Surface Textured with Microscale Pillars

Published:2023-11-20 Issue:48 Volume:39 Page:17471-17479
ISSN:0743-7463
Container-title:Langmuir
language:en
Short-container-title:Langmuir

Author:

Choi Seyong¹,Kim Kiduk¹^ORCID,Byun Kisang¹,Jang Joonkyung¹^ORCID

Affiliation:

1. Department of Nanoenergy Engineering, Pusan National University, Busan 46241, South Korea

Funder

National Research Foundation of Korea

Ministry of Trade, Industry and Energy

Publisher

American Chemical Society (ACS)

Subject

Electrochemistry,Spectroscopy,Surfaces and Interfaces,Condensed Matter Physics,General Materials Science

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.langmuir.3c02688

Reference50 articles.

1. Pearl drops

2. Super-Water-Repellent Fractal Surfaces

3. A Super-Hydrophobic and Super-Oleophilic Coating Mesh Film for the Separation of Oil and Water

4. Robust and Durable Superhydrophobic Cotton Fabrics for Oil/Water Separation

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1. Prediction of Femtosecond Laser Etching Parameters Based on a Backpropagation Neural Network with Grey Wolf Optimization Algorithm;Micromachines;2024-07-28

2. Two-photon lithography for customized microstructured surfaces and their influence on wettability and bacterial load;3D Printing in Medicine;2024-04-17

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