Prediction of water transport properties on an anisotropic wetting surface <i>via</i> deep learning-Reference-Cited by-同舟云学术

Prediction of water transport properties on an anisotropic wetting surface via deep learning

Published:2023 Issue:30 Volume:15 Page:12737-12747
ISSN:2040-3364
Container-title:Nanoscale
language:en
Short-container-title:Nanoscale

Author:

Guo Yuting¹^ORCID,Sun Haiyi²,An Meng³,Mabuchi Takuya²⁴^ORCID,Zhao Yinbo²^ORCID,Li Gaoyang²

Affiliation:

1. Department of Mechanical Engineering and Science, Kyoto University, Nishikyo-ku, Kyoto 615-8540, Japan

2. Institute of Fluid Science, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan

3. Department of Mechanical Engineering, Graduate School of Engineering, The University of Tokyo, 7-3-1, Bunkyo-ku, Tokyo 113-8656, Japan

4. Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, 2-1-1 Katahira Aoba-ku, Sendai, Miyagi 980-8577, Japan

Abstract

Understanding the water flow behavior on an anisotropic wetting surface is of practical significance in nanofluidic devices for their performance improvement.

Funder

Japan Science and Technology Agency

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science

Link

http://pubs.rsc.org/en/content/articlepdf/2023/NR/D3NR02709K

Reference57 articles.

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5. Water in nanotubes: The surface effect

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