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A replacement model to simulate the nonlinear dynamics of electro-responsive liquid crystal coatings

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Abstract

An electric circuit replacement model is proposed to simulate the key nonlinear dynamics of electro-responsive liquid crystal polymer networks (LCNs). LCNs are known for having great potential to be integrated into smart functional surfaces due to their ability to generate various surface patterns. However, due to their complex molecular dynamics, low-order dynamic models that can accurately describe and predict their dynamic behavior are still lacking. In light of this research gap, we develop a lumped-parameter replacement model based on the observed dynamics in the experimental data and the physics of LCN dielectric properties. The unique assembly of lumped parameters in its simplest form describes the transformation of a high-frequency input voltage to a relatively slow increase in the local height of the LCN coating in between the electrodes, serving as an excitation mechanism to induce height change. The nonlinear dynamics of this height increase, as a function of both excitation frequency and voltage, is described by the proposed model. Furthermore, the comparison of the simulation results with the experimental data from LCN shows that key LCN response characteristics are captured well by the model. This model makes it possible to accurately predict and control the response of the electro-responsive LCN surfaces to obtain a predefined desired deformation pattern, which is a vital requirement for integrating them in haptic and smart surface devices.

Original languageEnglish
Article number035203
Number of pages7
JournalAIP Advances
Volume13
Issue number3
DOIs
Publication statusPublished - Mar 2023

Bibliographical note

Funding Information:
This work was financially supported by the Institute for Complex Molecular Systems (ICMS). In addition, we would like to thank Dick Broer for his valuable contribution in improving the physics-based model, as well as his engagement in active editing of the manuscript. Also, we appreciate Fahim Shakib contribution to the simulation section and we thank Danqing Liu for providing us with the experimental data.

Funding

This work was financially supported by the Institute for Complex Molecular Systems (ICMS). In addition, we would like to thank Dick Broer for his valuable contribution in improving the physics-based model, as well as his engagement in active editing of the manuscript. Also, we appreciate Fahim Shakib contribution to the simulation section and we thank Danqing Liu for providing us with the experimental data.

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