Antagonistic Effect Between Deformation and Magnetism in Liquid Metal Coils Smart Architecture for Multi‐Mode Sensing
Nan Li, Fei Zhan, Jun Su, Yuqing Li, Xueqing Chen, Minghui Guo, Lei Wang, Jing Liu
- Year
- 2025
- Citations
- 2
Abstract
Abstract Addressing the growing demand for advanced smart materials in complex operational environments, the Antagonistic Liquid Metal Architecture (ALMA), a novel system exhibiting sophisticated multi‐responsivity and robustness is introduced. ALMA uniquely integrates temperature‐induced deformation and magnetically modulated liquid metal coils within a PDMS@Fe matrix to achieve tunable inductance. By varying the Fe‐to‐PDMS weight ratio (WR), the temperature coefficient of inductance is precisely controlled from positive (0.032%/K) to negative (−0.052%/K), demonstrating exceptional linearity ( R 2 ≈ 0.999). Notably, at WR = 1.4, ALMA enables temperature‐insensitive pressure sensing, minimizing temperature‐induced inductance error to <0.01875%/K. This, combined with intrinsic resistance changes, facilitates decoupled pressure and temperature multimodal sensing. Furthermore, a biomimetic superhydrophobic surface (>150° contact angle) imparts remarkable environmental robustness, ensuring visible protection against acid‐induced corrosion. Long‐term monitoring confirms ALMA's reliability and sensitivity to subtle temperature variations. ALMA presents a versatile and robust smart material platform, promising significant advancements in flexible sensors for diverse applications including industrial monitoring, advanced robotics, and extreme environment exploration.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992