Multimodal liquid transport enabled by <i>Crassula muscosa</i> shoot inspired ratchet-shaped leaves channel

Z Zehang Cui L Liang Chen G Guoqiang Li (School of Materials Science and Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China) D Dongxu Xiao (School of Manufacturing Science and Engineering, Key Laboratory of Testing Technology for Manufacturing Process, Ministry of Education, Southwest University of Science and Technology 1 , Mianyang 621010,) H Haojie Xu (Department of Medical Ultrasound) Y Yiyu Chen Y Yaoxia Li (School of Intelligent Manufacturing, Mianyang Ploytechnic 2 , Mianyang 621010,) H Haoyu Bai (School of Materials Science and Engineering, Smart Sensing Interdisciplinary Science Center, Nankai University 3 , Tianjin 300350,) J Jiaxin Yu M Moyuan Cao (School of Materials Science and Engineering, Smart Sensing Interdisciplinary Science Center, Nankai University 3 , Tianjin 300350,)

Abstract

Despite advances in bioinspired liquid transport systems, most reported surfaces relying on static wettability gradients or asymmetric structures are limited to single-mode transport, while multimodal transport within a single channel remains largely unexplored. Inspired by Crassula muscosa shoots, we propose a multimodal liquid transport channel (MLTC) that integrates asymmetric curvature and tilt features to enable on-demand switching among four liquid transport modes: (I) unidirectional transport in channel, (II) bidirectional transport in channel, (III) unidirectional transport with a protruding liquid film on channel, and (IV) transport failure. The surface-tension responsiveness mechanism is elucidated, where the synergy between curvature-induced Laplace pressure asymmetry and tilt-driven meniscus dynamics governs transport behavior, allowing liquids with surface tensions ranging from 22.8 to 72.8 mN/m to autonomously select transport modes. Leveraging the tunable flow direction and liquid height differences among modes, a real-time surface-tension sensor is demonstrated, capable of distinguishing liquids within three ranges: 22.8–31.5, 35–42.5, and ∼55 mN/m. Furthermore, assembled MLTCs further function as droplet separators, achieving &amp;gt;95% efficiency for both oil–water and oil–oil separations. This work introduces a multimodal liquid manipulation strategy, offering new opportunities for adaptive microfluidics, smart diagnostics, and precise liquid separation.

Article Details

Volume / Issue Vol. 128, Issue 24
Published June 15, 2026
ISSN 0003-6951
Publisher American Institute of Physics

Journal Info

Applied Physics Letters

American Institute of Physics

ISSN: 0003-6951 Physical Sciences

Authors (10)

Z

Zehang Cui

L

Liang Chen

G

Guoqiang Li

School of Materials Science and Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China

D

Dongxu Xiao

School of Manufacturing Science and Engineering, Key Laboratory of Testing Technology for Manufacturing Process, Ministry of Education, Southwest University of Science and Technology 1 , Mianyang 621010,

H

Haojie Xu

Department of Medical Ultrasound

Y

Yiyu Chen

Y

Yaoxia Li

School of Intelligent Manufacturing, Mianyang Ploytechnic 2 , Mianyang 621010,

H

Haoyu Bai

School of Materials Science and Engineering, Smart Sensing Interdisciplinary Science Center, Nankai University 3 , Tianjin 300350,

J

Jiaxin Yu

M

Moyuan Cao

School of Materials Science and Engineering, Smart Sensing Interdisciplinary Science Center, Nankai University 3 , Tianjin 300350,