Programmable responsive hydrogels inspired by classical conditioning algorithm

Hang Zhang, Hao Zeng, Arri Priimagi () and Olli Ikkala ()
Additional contact information
Hang Zhang: Aalto University
Hao Zeng: Tampere University
Arri Priimagi: Tampere University
Olli Ikkala: Aalto University

Nature Communications, 2019, vol. 10, issue 1, 1-8

Abstract: Abstract Living systems have inspired research on non-biological dynamic materials and systems chemistry to mimic specific complex biological functions. Upon pursuing ever more complex life-inspired non-biological systems, mimicking even the most elementary aspects of learning is a grand challenge. We demonstrate a programmable hydrogel-based model system, whose behaviour is inspired by associative learning, i.e., conditioning, which is among the simplest forms of learning. Algorithmically, associative learning minimally requires responsivity to two different stimuli and a memory element. Herein, nanoparticles form the memory element, where a photoacid-driven pH-change leads to their chain-like assembly with a modified spectral behaviour. On associating selected light irradiation with heating, the gel starts to melt upon the irradiation, originally a neutral stimulus. A logic diagram describes such an evolution of the material response. Coupled chemical reactions drive the system out-of-equilibrium, allowing forgetting and memory recovery. The findings encourage to search non-biological materials towards associative and dynamic properties.

Date: 2019
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DOI: 10.1038/s41467-019-11260-3

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