Gravity‐Driven Inclination Sensor Based on Liquid Metal Interface Migration in Anisotropic Microchannels for Information Transmission and Continuous Surface Topography Scanning

ABSTRACT With the continuous advancement of materials science and technology, the rare metal gallium has increasingly emerged as a promising alternative to the toxic metal mercury. Although existing research has predominantly focused on the high electrical conductivity and excellent deformability of liquid metal (LM), its intrinsic fluidic property, known as wettability, has received comparatively less attention. In this study, we utilize the inherent wettability of LM to construct an inclination sensor by directly injecting the LM into internally microstructured microchannels. These are fabricated by replicating the surface morphology of Stipa lessingiana using polydimethylsiloxane. Upon tilting, the LM at the three‐phase interface within the microchannel exhibits dynamic wetting behavior driven by Laplace pressure, which induces measurable changes in electrical resistance. The proposed inclination sensor exhibits a high angular resolution of 2°, a fast response time of 0.5 s, and a wide detection range from −90° to 90°. It also demonstrates excellent cyclic stability over 500 operation cycles and maintains functional integrity over a service life of up to 20 days. Furthermore, we combined it with a 3D mobile platform to construct a surface topography scanning system. This innovative design offers strong potential for transformative applications in advanced manufacturing, soft robotics, information transmission, and flexible sensing technologies, paving the way for broader implementation and adoption.

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Publication Details

Journal
Rare Metals
Published
2025-12-27
DOI
https://doi.org/10.1002/rar2.70075
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.00

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article

Gravity‐Driven Inclination Sensor Based on Liquid Metal Interface Migration in Anisotropic Microchannels for Information Transmission and Continuous Surface Topography Scanning

G Wang, Feifan Guo, Min Mao, Fei Zhan et al.
Rare Metals
Advanced Sensor and Energy Harvesting Materials
article

Gravity‐Driven Inclination Sensor Based on Liquid Metal Interface Migration in Anisotropic Microchannels for Information Transmission and Continuous Surface Topography Scanning

G Wang, Feifan Guo, Min Mao, Fei Zhan, Lei Wang, Xuedong Qiang
article en

Abstract

ABSTRACT With the continuous advancement of materials science and technology, the rare metal gallium has increasingly emerged as a promising alternative to the toxic metal mercury. Although existing research has predominantly focused on the high electrical conductivity and excellent deformability of liquid metal (LM), its intrinsic fluidic property, known as wettability, has received comparatively less attention. In this study, we utilize the inherent wettability of LM to construct an inclination sensor by directly injecting the LM into internally microstructured microchannels. These are fabricated by replicating the surface morphology of Stipa lessingiana using polydimethylsiloxane. Upon tilting, the LM at the three‐phase interface within the microchannel exhibits dynamic wetting behavior driven by Laplace pressure, which induces measurable changes in electrical resistance. The proposed inclination sensor exhibits a high angular resolution of 2°, a fast response time of 0.5 s, and a wide detection range from −90° to 90°. It also demonstrates excellent cyclic stability over 500 operation cycles and maintains functional integrity over a service life of up to 20 days. Furthermore, we combined it with a 3D mobile platform to construct a surface topography scanning system. This innovative design offers strong potential for transformative applications in advanced manufacturing, soft robotics, information transmission, and flexible sensing technologies, paving the way for broader implementation and adoption.

Rare MetalsVol. 45(2)
Nantong University (CN), Beijing Forestry University (CN), Grinm Advanced Materials (China) (CN)
Beijing Forestry University, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 39%
Advanced Sensor and Energy Harvesting Materials
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