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Updated: Nov 29, 2025

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Published on: July 19, 2024
A hyperelastic model for simulating cells in flow
Sebastian J Müller1, Franziska Weigl2, Carina Bezold3
1Theoretical Physics VI, Biofluid Simulation and Modeling, University of Bayreuth, Universitätsstraße 30, Bayreuth, 95440, Germany. sjmueller@uni-bayreuth.de.
This study introduces a numerical model to simulate cell deformation in 3D bioprinting, crucial for preventing cell damage and loss of function during printing. The model accurately predicts cell behavior under hydrodynamic stress, improving bioprinting outcomes.
Area of Science:
- Biophysics
- Biomaterials Engineering
- Computational Biology
Background:
- Cell damage during 3D bioprinting is a major challenge, leading to cell death and loss of functionality.
- This damage is linked to cell deformation caused by hydrodynamic stresses during the printing process.
- Understanding the mechano-elastic response of cells is critical for mitigating these issues.
Purpose of the Study:
- To develop and validate a numerical model for simulating biological cell deformation in arbitrary 3D flows.
- To accurately predict cell behavior under hydrodynamic stresses encountered during 3D bioprinting.
- To improve the fidelity and success rate of 3D bioprinting applications.
Main Methods:
- Modeling cells as elastic continua using the hyperelastic Mooney-Rivlin model.
- Employing force calculations on a tetrahedralized volume mesh.
- Integrating the cell deformation model into Lattice Boltzmann simulations via an Immersed-Boundary algorithm.
Main Results:
- Model calibration using FluidFM compression experiments on REF52 cells confirmed the necessity of all three Mooney-Rivlin parameters for large deformations (up to 80%).
- Validation against AFM experiments on endothelial cells and hydrogel particles demonstrated model accuracy.
- Simulations in linear shear flows showed excellent agreement with analytical calculations and prior simulation data.
Conclusions:
- The developed numerical model accurately simulates cell deformation in 3D flows, crucial for 3D bioprinting.
- The model's ability to capture large deformations and its validation provide a robust tool for bioprinting research.
- This work contributes to reducing cell damage and enhancing the functionality of 3D bioprinted constructs.
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