Transport of enzymatic activity across liquid-liquid interfaces using dynamic assemblies of magnetic particles via field-modulated interactions
Abstract
Abstract Biological systems dynamically grow high-aspect-ratio architectures from a site, enabling traversal of phase boundaries and functional execution. Emulating this growth strategy in synthetic systems could yield functional microsystems for operation across interfaces. However, engineering such bio-inspired growth to proceed out of plane from a substrate in synthetic colloidal assemblies remains challenging, as it requires overcoming gravitational collapse while maintaining structural coherence during extension. Here, we present a field-driven particle system that achieves gravity-resisting growth of high-aspect-ratio structures via frequency-modulated magnetic and hydrodynamic interactions. This growth is enabled by combining static and oscillating magnetic fields, which guide the assembly of magnetic particles into dynamic structures exhibiting a distinct segmented, seaweed-like morphology. These architectures are reconfigurable, stabilizable, programmably actuatable, and capable of penetrating a perfluorohexane–water interface. When functionalized with enzymes, the growing structures act as micro-transporters, delivering catalytic activity across the interface and triggering detectable reactions in both bulk two-phase and microfluidic chip systems. This work establishes a field-driven assembly-to-function approach that integrates structural growth, phase-boundary penetration, and triggered functionality, enabling active microsystems capable of interfacial transport and functional execution.
Article Details
Authors (12)
Shilu Zhu
Shuwei Shen
Min Ye
State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China
Yang Zhang
Zhiyuan Zheng
School of Chemistry and Chemical Engineering
Jie Gao
State Key Laboratory of Fine Chemicals, Frontiers Science Center for Smart Materials
Ru Zhang
Zhongliang Lang
Peng Yao
Mingzhai Sun
Luke P. Lee
Ronald X. Xu