Technologies including (3D-) (bio-)printing, diesel engines, laser-induced forward transfer, and spray cleaning require optimization and therefore understanding of micrometer-sized droplets impacting at velocities beyond 10 m s ⁻¹ .

Designer microparticles and multiscale materials can be fabricated in one step by microfluidic processing in the air.

Biofabrication commonly involves the use of liquid droplets to transport cells to the printed structure. However, the viability of the cells after impact is poorly controlled and understood, hampering applications including cell spraying, inkjet bioprinting and laser-assisted cell transfer. Here, we present an analytical model describing the cell viability after impact as a function of the cell-surrounding droplet characteristics. The model connects (1) the cell survival as a function of cell membrane elongation, (2) the membrane elongation as a function of the cell-containing droplet size and velocity and (3) the substrate properties. The model is validated by cell viability measurements in cell spraying, which is a method for biofabrication and used for the treatment of burn wounds. The results allow for rational optimization of any droplet-based cell deposition technology and we include practical suggestions to improve the cell viability in cell spraying.

Water microdroplet impact at velocities up to 100 m s⁻¹ for droplet diameters ranging from 12 to 100 μm is studied. This parameter range covers the transition from capillary-limited to viscosity-limited spreading of the impacting droplet. Splashing is absent for all measurements; the droplets always gently spread over the surface. The maximum spreading radius is compared to several existing models. The model by Pasandideh-Fard et al. agrees well with the measured data, indicating the importance of a thin boundary layer just above the surface, in which most of the viscous dissipation in the spreading droplet takes place. As explained by the initial air layer under the impacting droplet, a contact angle of 180 degrees is used as the model input.