Nonlinear statistical mechanics drives intrinsic electrostriction and volumetric torque in polymer networks

Matthew Grasinger, Carmel Majidi, and Kaushik Dayal
Phys. Rev. E 103, 042504 – Published 27 April 2021

Abstract

Statistical mechanics is an important tool for understanding polymer electroelasticity because the elasticity of polymers is primarily due to entropy. However, a common approach for the statistical mechanics of polymer chains, the Gaussian chain approximation, misses key physics. By considering the nonlinearities of the problem, we show a strong coupling between the deformation of a polymer chain and its dielectric response, that is, its net dipole. When chains with this coupling are cross linked in an elastomer network and an electric field is applied, the field breaks the symmetry of the elastomer's elastic properties and, combined with electrostatic torque and incompressibility, leads to intrinsic electrostriction. Conversely, deformation can break the symmetry of the dielectric response, leading to volumetric torque and asymmetric actuation. Both phenomena have important implications for designing high-efficiency soft actuators and soft electroactive materials, and the presence of mechanisms for volumetric torque, in particular, can be used to develop higher degree of freedom actuators and to achieve bioinspired locomotion.

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  • Received 18 December 2020
  • Revised 8 March 2021
  • Accepted 8 April 2021

DOI:https://doi.org/10.1103/PhysRevE.103.042504

©2021 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied Physics

Authors & Affiliations

Matthew Grasinger1,2,3,4,*, Carmel Majidi2,5,6, and Kaushik Dayal1,2,6,7

  • 1Pittsburgh Quantum Institute, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
  • 2Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
  • 3UES, Inc., Dayton, Ohio 45432, USA
  • 4Materials and Manufacturing Directorate, Air Force Research Laboratory, Dayton, Ohio 45433, USA
  • 5Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
  • 6Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
  • 7Center for Nonlinear Analysis, Department of Mathematical Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA

  • *matthew.grasinger.ctr@afresearchlab.com

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Issue

Vol. 103, Iss. 4 — April 2021

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