Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published August 2021 | public
Journal Article

Accelerated computational micromechanics and its application to polydomain liquid crystal elastomers


We present an approach to solving problems in computational micromechanics that is amenable to massively parallel calculations through the use of graphical processing units (GPUs) and other accelerators. We apply it to study microstructure evolution in polydomain liquid crystal elastomers (LCEs). LCEs are rubber-like solids where rod-like nematic molecules are incorporated into the main or a side polymer chain. They undergo isotropic to nematic phase transition accompanied by spontaneous deformation which can be exploited for actuation. Further, they display a soft behavior at low temperatures due to the reorientation of the nematic directors. The problem of understanding nematic reorientation in the presence of realistic defects (non-ideality) is computationally expensive, and we address this by efficiently exploiting GPUs. The approach is broadly applicable to various phenomena including crystal plasticity and phase transitions that are described by internal variable theories. We verify the approach against previous calculations and establish its performance by studying long wavelength instability of finite elasticity. Our numerical studies of LCEs provide insights into the director distribution and reorientation in polydomain specimens, and how these lead to soft behavior under multiaxial loading. The results show good agreement with experimental observations.

Additional Information

© 2021 Elsevier. Received 18 February 2021, Revised 21 April 2021, Accepted 22 April 2021, Available online 12 May 2021. We are delighted to acknowledge many stimulating discussions with Pierre Suquet (concerning FFT algorithms) and Kenji Urayama (concerning LCEs). The latter also generously provided us with experimental data shown in Fig. 13. We gratefully acknowledge the support of the US Air Force Office for Scientific Research through the MURI grant number FA9550-16-1-0566. The computations presented here were performed at the High Performance Computing Center of California Institute of Technology. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional details

August 22, 2023
October 23, 2023