Viewpoint: Pavlovian Materials—Functional Biomimetics Inspired by Classical Conditioning
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Viewpoint : Pavlovian Materials—Functional Biomimetics Inspired by Classical Conditioning. / Zhang, Hang; Zeng, Hao; Priimägi, Arri; Ikkala, Olli.
In: Advanced Materials, 2020.Research output: Contribution to journal › Article › Scientific › peer-review
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TY - JOUR
T1 - Viewpoint
T2 - Pavlovian Materials—Functional Biomimetics Inspired by Classical Conditioning
AU - Zhang, Hang
AU - Zeng, Hao
AU - Priimägi, Arri
AU - Ikkala, Olli
PY - 2020
Y1 - 2020
N2 - Herein, it is discussed whether the complex biological concepts of (associative) learning can inspire responsive artificial materials. It is argued that classical conditioning, being one of the most elementary forms of learning, inspires algorithmic realizations in synthetic materials, to allow stimuli-responsive materials that learn to respond to a new stimulus, to which they are originally insensitive. Two synthetic model systems coined as “Pavlovian materials” are described, whose stimuli-responsiveness algorithmically mimics programmable associative learning, inspired by classical conditioning. The concepts minimally need a stimulus-triggerable memory, in addition to two stimuli, i.e., the unconditioned and the originally neutral stimuli. Importantly, the concept differs conceptually from the classic stimuli-responsive and shape-memory materials, as, upon association, Pavlovian materials obtain a given response using a new stimulus (the originally neutral one); i.e., the system evolves to a new state. This also enables the functionality to be described by a logic diagram. Ample room for generalization to different stimuli and memory combinations is foreseen, and opportunities to develop future adaptive materials with ever-more intelligent functions are expected.
AB - Herein, it is discussed whether the complex biological concepts of (associative) learning can inspire responsive artificial materials. It is argued that classical conditioning, being one of the most elementary forms of learning, inspires algorithmic realizations in synthetic materials, to allow stimuli-responsive materials that learn to respond to a new stimulus, to which they are originally insensitive. Two synthetic model systems coined as “Pavlovian materials” are described, whose stimuli-responsiveness algorithmically mimics programmable associative learning, inspired by classical conditioning. The concepts minimally need a stimulus-triggerable memory, in addition to two stimuli, i.e., the unconditioned and the originally neutral stimuli. Importantly, the concept differs conceptually from the classic stimuli-responsive and shape-memory materials, as, upon association, Pavlovian materials obtain a given response using a new stimulus (the originally neutral one); i.e., the system evolves to a new state. This also enables the functionality to be described by a logic diagram. Ample room for generalization to different stimuli and memory combinations is foreseen, and opportunities to develop future adaptive materials with ever-more intelligent functions are expected.
KW - adaptation
KW - associative learning
KW - biomimetics
KW - classical conditioning
KW - stimuli-responsive materials
U2 - 10.1002/adma.201906619
DO - 10.1002/adma.201906619
M3 - Article
JO - Advanced Materials
JF - Advanced Materials
SN - 0935-9648
M1 - 1906619
ER -