Towards life-inspired soft matter dynamics and functionalities Olli Ikkala Aalto University, Department of Applied Physics, Finland Soft matter properties have extensively been promoted by stimulus-responsiveness, shape-memory effects, and bio-inspiration towards ever more multifunctional properties. 1-3 Beyond the equilibrium and kinetically trapped static states, adaptive and dynamic dissipative feedback-controlled properties inspired by living matter would be among the next attractive functionalities, however, involving complexity. 4-7 Herein, we describe soft matter approaches inspired by selected functions of living systems. Classical (Pavlovian) conditioning, habituation, and sensitization are among the simplest "learning" concepts in behaviour. 8 Artificial Pavlovian condition has, not surprisingly, already been described in biosynthetic articifial systems. 9 We consider light and magnetic field as feasible stimuli because they can applied remotely. We show concepts algorithmically inspired by Pavlovian conditioning in common manmade soft matter systems. 10-11 We further show electrical conduction bistability, response plasticity, and adaptation based on soft ferromagnetic particle assemblies using magnetic stimulus, inspired by sensitization. 12 Finally, we show dynamic light-driven systems to allow feedback-controlled homeostasis and dissipative signal transduction. 13 Life-inspired soft materials can provide the next generation of out-of-equilibrium dissipative platforms for embedded materials intelligence. 14 References 1. K. M. Herbert, S. Schrettl, S. J. Rowan, C. Weder, 50th anniversary perspective: Solid-state multistimuli, multiresponsive polymeric materials. Macromolecules 2017, 50, 8845. 2. A. Lendlein, O. E. C. Gould, Reprogrammable recovery and actuation behaviour of shape-memory polymers. Nat. Rev. Mater. 2019, 4, 116. 3. B. Bhushan, Biomimetics: lessons from nature-an overview, Phil. Trans. R. Soc. A 2009 367, 1445. 4. J. L. England, Dissipative adaptation in driven self-assembly. Nat. Nanotechnol. 2015, 10, 919. 5. M. M. Lerch, A. Grinthal, J. Aizenberg, Viewpoint: homeostasis as inspiration—toward interactive materials. Adv. Mater. 2020, 32, 1905554. 6. A. Walther, Viewpoint: From Responsive to Adaptive and Interactive Materials and Materials Systems: A Roadmap, Adv. Mater. 2020, 32, 1905111. 7. B. Novák, J.J. Tyson, Design principles of biochemical oscillators. Nat. Rev. Mol. Cell Biol. 2008, 9, 981. 8. E. R. Kandel, In search of memory: the emergence of a new science of mind, W.W. Norton &Co., New York, 2006. 9. H. Zhang, et al, Programming a Pavlovian-like conditioning circuit in Escherichia coli. Nat. Commun. 2014, 5, 3102. 10. H. Zhang, H. Zeng, A. Priimagi, O. Ikkala, Programmable responsive hydrogels with classical conditioning algorithm, Nat. Commun. 2019, 10, 3267. 11. H. Zeng, H. Zhang, O. Ikkala, A. Priimagi, Associative Learning by Classical Conditioning in Liquid Crystal Network Actuators, Matter 2019, 2, 194. 12. X. Liu, H. Tan, C. Rigoni, T. Hartikainen, N. Asghar, S. van Dijken, J. V. I. Timonen, B. Peng, O. Ikkala, Magnetic field–driven particle assembly and jamming for bistable memory and response plasticity, Sci Adv. 2022, 8, eadc9394. 13. H. Zhang, H. Zeng, A. Eklund, H. Guo, A. Priimagi, O. Ikkala, Feedback-controlled hydrogels with homeostatic oscillations and dissipative signal transduction, Nat. Nanotechnol. 2022, 17, 1303. 14. C. Kaspar, B. J. Ravoo, W. G. van der Wiel, S. V. Wegner, W. H. P. Pernice, The rise of intelligent matter, Nature 2021, 594, 345.
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