Enabling Technologies for Obtaining Desired Stiffness Gradients in GelMA Hydrogels Constructs
This work presents enabling technologies for the optimization of the manufacturing of GelMA‐based hydrogels constructs with desired stiffness gradients. The manufacturing technique combines dynamic mixing for gradient generation and a passive micromixer for efficient hydrogel blending. A digital rep...
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Veröffentlicht in: | Macromolecular chemistry and physics 2022-01, Vol.223 (2), p.n/a |
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Sprache: | eng |
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Zusammenfassung: | This work presents enabling technologies for the optimization of the manufacturing of GelMA‐based hydrogels constructs with desired stiffness gradients. The manufacturing technique combines dynamic mixing for gradient generation and a passive micromixer for efficient hydrogel blending. A digital replica of the fabrication process is developed, integrating theoretical and computational models, as well as experimental data, in order to predict and control the stiffness profile obtained within the constructs. The workflow for the development of the in silico framework, based on rigorous verification, validation, and uncertainty quantification steps, is presented. The validation of the digital replica is based on reference settings of process variables, which result in constructs with an exponential stiffness profile. The developed in silico model has been employed for optimizing process variables in order to obtain a linear stiffness profile in the extruded construct without the need of expensive and time‐consuming trial‐and‐error procedures. The developed digital replica is now a powerful tool for the creation of hydrogel gradient constructs for tissue engineering applications or for the screening of optimal 3D cell culture conditions.
This work presents enabling technologies for optimizing the manufacturing of GelMA‐based hydrogels constructs with desired stiffness gradients. A digital replica of the fabrication process is developed, allowing to predict and control the stiffness profile obtained within the constructs. The workflow for the development of the in silico framework, based on rigorous verification, validation, and uncertainty quantification steps, is presented. |
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ISSN: | 1022-1352 1521-3935 |
DOI: | 10.1002/macp.202100326 |