A Coupled FEM-SPH Modeling Technique to Investigate the Contractility of Biohybrid Thin Films

Lorenzo Vannozzi, Tommaso Mazzocchi, Arihiro Hasebe, Shinji Takeoka, Toshinori Fujie*, Leonardo Ricotti

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Biohybrid actuators have the potential to overcome the limitations of traditional actuators employed in robotics, thanks to the unique features of living contractile muscle cells, which can be used to power artificial elements. This paper describes a computational approach for the estimation of the contractile capabilities of skeletal muscle cell-powered biohybrid actuators based on polymeric thin films. The proposed model grounds on the coupling between finite element modeling and smooth particle hydrodynamics. This allows describing the overall condition, including the viscous forces caused by the surrounding liquid medium, in which biohybrid systems are normally immersed. The model is calibrated by analyzing the contractile behavior of polydimethylsiloxane films coupled with skeletal muscle cells, reported in the literature as muscular thin films. Afterward, it is applied to poly (D, L-lactic acid) thin films to explore the behavior of these systems, due to myotubes cultured on them, evaluating the role of thickness, tissue maturation status, and hydrostatic pressure on the contractile performance. These results pave the way toward a novel optimization approach of biohybrid robot design relying on the simulation of all the boundary conditions, thus reducing the need for extensive trial-and-error efforts.

Original languageEnglish
Article number1900306
JournalAdvanced Biosystems
Issue number8
Publication statusPublished - 2020 Aug 1


  • bio-hybrid robots
  • bioactuators
  • finite element modeling
  • living machines
  • smooth particle hydrodynamics
  • soft microrobots
  • thin films

ASJC Scopus subject areas

  • Biomaterials
  • Biomedical Engineering
  • Biochemistry, Genetics and Molecular Biology(all)


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