Inkjet bioprinting is an additive manufacturing approach for creating 3D tissue constructs using cell suspensions and hydrogels as bioinks. Many hydrogels and cell suspensions can be mixed to prepare cell-laden bioinks for traditional mixing-then-printing applications. However, some hydrogels are chemically reactive with cell suspensions upon mixing. Bioinks prepared by mixing these hydrogels and cell suspensions have significantly deteriorated printability and even are not printable at all. This GOALI award supports fundamental research on a mixing-while-printing approach to print reactive hydrogels and cell suspensions. Results from this research will expand the versatility of 3D inkjet bioprinting with reactive biomaterials. Printed heterogeneous tissue constructs can be used as organ models for various biomedical applications such as drug screening, and might be used for organ transplantation in the future.
With the mixing-while-printing approach, reactive hydrogels and cell suspensions are printed as two individual jets; the jets break up, intersect, and mix with each other due to droplet collision and coalescence, resulting in a gelled heterogeneous building block. The research objectives are two-fold: (1) to understand the effects of printing conditions on droplet formation, impingement, collision, and coalescence processes when using intersecting jets; and (2) to elucidate the influences of droplet impingement, collision, and coalescence on the material mixing performance during mixing-while-printing biofabrication. To achieve the first objective, cell-laden droplet formation process will be modeled using a volume of fluid-based computational approach to predict the droplet morphology, size, and velocity under different nozzle diameters and exciting voltages. Droplet impingement, collision, and coalescence processes will be modeled using a meshfree smooth particle hydrodynamic method under different intersecting angles and standoff distances. Some model predictions will be compared with experimental results, and the droplet morphology, size, and velocity before and after jet intersecting will be measured using high speed imaging. To achieve the second objective, material mixing performance will be evaluated in terms of how living cells are distributed in a printed structure. The mixing performance will be modeled using a set of material property and printing condition-related dimensionless numbers based on a scale analysis of governing conservation equations and interfacial conditions. Predicted mixing performance will be compared with the measured cell distribution of deposited droplets and fabricated tissue constructs using particle image velocimetry and optical imaging, respectively, under different droplet impingement, collision, and coalescence scenarios.