Search for: All records

We introduce a hardware–software system for rapidly characterizing liquid microjets for x-ray diffraction experiments. An open-source python-based software package allows for programmatic and automated data collection and analysis. We show how jet speed, length, and diameter are influenced by nozzle geometry, gas flow rate, liquid viscosity, and liquid flow rate. We introduce “jet instability” and “jet probability” metrics to help quantify the suitability of a given nozzle for x-ray diffraction experiments. Among our observations were pronounced improvements in jet stability and reliability when using asymmetric needle-tipped nozzles, which allowed for the production of microjects smaller than 250 nm in diameter, traveling faster than 120 m/s. 

Gas dynamic virtual nozzles (GDVNs) produce microscopic flow-focused liquid jets and droplets and play an important role at X-ray free-electron laser (XFEL) facilities where they are used to steer a stream of hydrated biomolecules into an X-ray focus during diffraction measurements. Highly stable and reproducible microjet and microdroplets are desired, as are flexible fabrication methods that enable integrated mixing microfluidics, droplet triggering mechanisms, laser illumination, and other customized features. In this study, we develop the use of high-resolution 3D nano-printing for the production of monolithic, asymmetric GDVN designs that are difficult to fabricate by other means. We also develop a dual-pulsed nanosecond image acquisition and analysis platform for the characterization of GDVN performance, including jet speed, length, diameter, and directionality, among others. We show that printed GDVNs can form microjets with very high degree of reproducibility, down to sub-micron diameters, and with water jet speeds beyond 170 m/s.