Synthesis and investigation of chemomechanical gels driven by the Belousov–Zhabotinsky reaction: insights into ligand influence
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Olga V. Lagunova
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Pavel S. Smelov
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Alexander V. Sychev
Abstract
Self-oscillating chemomechanical gels powered by the Belousov–Zhabotinsky (BZ) reaction represent a promising class of smart materials for soft robotics and autonomous systems; however, a comprehensive understanding of how the catalyst’s chemical structure governs their performance is still lacking. This work investigates the relationship between ligand hydrophobicity in immobilized iron-based BZ catalysts and the resultant chemomechanical response of poly(N-isopropylacrylamide) hydrogels. A series of heteroleptic iron complexes with systematically varied ligand hydrophobicity – bis(1,10-phenanthroline)(5-acrylamido-1,10-phenanthroline) iron(II) sulfate, bis(4,4′-dimethyl-2,2′-bipyridine)(5-acrylamido-1,10-phenanthroline) iron(II) sulfate, and bis(2,2′-bipyridine)(5-acrylamido-1,10-phenanthroline) iron(II) sulfate, as well as bis(bathophenanthroline)(1,10-phenanthroline) iron(II) sulfate – were synthesized and incorporated into the polymer network. The gels’ self-oscillating behavior, morphological structure (via SEM), and elastic properties were characterized. It was found that increasing ligand hydrophobicity significantly enhances the amplitude of chemomechanical oscillations while concurrently reducing the elastic modulus of the gel. These results demonstrate that ligand hydrophobicity is a critical design parameter for tuning the performance of self-oscillating gels, paving the way for optimizing next-generation autonomous soft actuators and pumps.
Acknowledgments
The authors would like to thank Koroleva Yulia for her support of the detection iron by inductively coupled plasma optical emission spectrometry in this study.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: All other authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Not applicable.
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