@article{3283fe19675f4e348fd5f791d9fdba10,
title = "Magttice: a lattice model for hard-magnetic soft materials",
abstract = "Magnetic actuation has emerged as a powerful and versatile mechanism for diverse applications, ranging from soft robotics, biomedical devices to functional metamaterials. This highly interdisciplinary research calls for an easy to use and efficient modeling/simulation platform that can be leveraged by researchers with different backgrounds. Here we present a lattice model for hard-magnetic soft materials by partitioning the elastic deformation energy into lattice stretching and volumetric change, so-called {\textquoteleft}magttice{\textquoteright}. Magnetic actuation is realized through prescribed nodal forces in magttice. We further implement the model into the framework of a large-scale atomic/molecular massively parallel simulator (LAMMPS) for highly efficient parallel simulations. The magttice is first validated by examining the deformation of ferromagnetic beam structures, and then applied to various smart structures, such as origami plates and magnetic robots. After investigating the static deformation and dynamic motion of a soft robot, the swimming of the magnetic robot in water, like jellyfish's locomotion, is further studied by coupling the magttice and lattice Boltzmann method (LBM). These examples indicate that the proposed magttice model can enable more efficient mechanical modeling and simulation for the rational design of magnetically driven smart structures.",
author = "Huilin Ye and Ying Li and Teng Zhang",
note = "Funding Information: H. Y. and Y. L. would like to acknowledge the support by the National Science Foundation under grant no. OAC-1755779. T. Z. acknowledges the support of the National Science Foundation under grant no. CMMI-1847149. H. Y. and Y. L. are grateful for the support from the Department of Mechanical Engineering at the University of Connecticut. Y. L. is partially supported by ASME Robert M. and Mary Haythornthwaite Research Initiation Award. T. Z. acknowledges the support from the Department of Mechanical and Aerospace Engineering at Syracuse University. H. Y. was partially supported by a fellowship grant from GE{\textquoteright}s Industrial Solutions Business Unit under a GE–UConn partnership agreement. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of Industrial Solutions or UConn. This research also benefited in part from the computational resources and staff contributions provided by the Booth Engineering Center for Advanced Technology (BECAT) at the University of Connecticut. The authors also acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin (Frontera project and the National Science Foundation award 1818253) and Comet cluster at San Diego Supercomputer Center (National Science Foundation award 1341698) (SDSC) for providing HPC resources that have contributed to the research results reported within this paper. Funding Information: H. Y. and Y. L. would like to acknowledge the support by the National Science Foundation under grant no. OAC-1755779. T. Z. acknowledges the support of the National Science Foundation under grant no. CMMI-1847149. H. Y. and Y. L. are grateful for the support from the Department of Mechanical Engineering at the University of Connecticut. Y. L. is partially supported by ASME Robert M. and Mary Haythornthwaite Research Initiation Award. T. Z. acknowledges the support from the Department of Mechanical and Aerospace Engineering at Syracuse University. H. Y. was partially supported by a fellowship grant from GE's Industrial Solutions Business Unit under a GE-UConn partnership agreement. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of Industrial Solutions or UConn. This research also benefited in part from the computational resources and staff contributions provided by the Booth Engineering Center for Advanced Technology (BECAT) at the University of Connecticut. The authors also acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin (Frontera project and the National Science Foundation award 1818253) and Comet cluster at San Diego Supercomputer Center (National Science Foundation award 1341698) (SDSC) for providing HPC resources that have contributed to the research results reported within this paper. Publisher Copyright: {\textcopyright} The Royal Society of Chemistry 2020.",
year = "2021",
month = apr,
day = "7",
doi = "10.1039/d0sm01662d",
language = "English (US)",
volume = "17",
pages = "3560--3568",
journal = "Soft Matter",
issn = "1744-683X",
publisher = "Royal Society of Chemistry",
number = "13",
}