Department of Applied Physics, Aalto University, P.O. Box 15100, FI 02150, Espoo, Finland.
Smart Photonic Materials, Faculty of Engineering and Natural Sciences, Tampere University, P.O. Box 541, FI-33101, Tampere, Finland.
Nat Commun. 2019 Jul 22;10(1):3267. doi: 10.1038/s41467-019-11260-3.
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.
生命系统激发了对非生物动态材料和系统化学的研究,以模拟特定的复杂生物学功能。在追求越来越复杂的受生命启发的非生物系统时,即使是最基本的学习方面也具有很大的挑战性。我们展示了一种可编程水凝胶模型系统,其行为受到联想学习(即条件作用)的启发,而联想学习是最简单的学习形式之一。从算法上讲,联想学习至少需要对两种不同的刺激和记忆元件有响应能力。在这里,纳米颗粒形成记忆元件,其中光致酸驱动的 pH 值变化导致它们与具有修饰的光谱行为的链状组装。通过将选定的光照射与加热相结合,凝胶在照射时开始融化,而最初的刺激是中性刺激。逻辑图描述了这种材料响应的演变。耦合化学反应使系统远离平衡状态,从而允许遗忘和记忆恢复。这些发现鼓励寻找具有联想和动态特性的非生物材料。