Exploiting photopolymerization to modulate liquid crystalline network actuation
Marco Turriani, Niccolò Cosottini, Neri Fuochi, Diederik S. Wiersma, Daniele Martella, Camilla Parmeggiani
- Year
- 2025
- Citations
- 7
- Access
- Open access
Abstract
Liquid Crystalline Networks (LCNs) are widely investigated to develop actuators, from soft robots to artificial muscles. Indeed, they can produce forces and movements in response to a plethora of external stimuli, showing kinetics up to the millisecond time-scale. One of the most explored preparation technique involves the photopolymerization of an aligned layer of reactive mesogens. Following this approach, side-chain polymers are widely described, while a detailed comparison of light-responsive LCNs with different architectures is not properly addressed. In this paper, two synthetic approaches are exploited leading to photoresponsive LCNs with different architectures. Mixed main-chain/side-chain LCNs are obtained in one-pot through a thiol-acrylate chain-transfer reaction, while main-chain LCNs are achieved by a two-step approach involving an aza-Michael addition followed by acrylate crosslinking. Comparison among the two materials highlighted the superior performances in terms of tension developed upon light-activation of the former one, showing muscle-like force production comparable to standard side-chain LCNs combined with the greater ability to contract from common main-chain LCNs.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992