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Description
Gas Dynamic Virtual Nozzles (GDVN) produce microscopic flow-focused liquid jets and are widely used for sample delivery in serial femtosecond crystallography (SFX) and time-resolved solution scattering. Recently, 2-photon polymerization (2PP) made it possible to produce 3D-printed GDVNs with submicron printing

Gas Dynamic Virtual Nozzles (GDVN) produce microscopic flow-focused liquid jets and are widely used for sample delivery in serial femtosecond crystallography (SFX) and time-resolved solution scattering. Recently, 2-photon polymerization (2PP) made it possible to produce 3D-printed GDVNs with submicron printing resolution. Comparing with hand- fabricated nozzles, reproducibility, and less developing effort, and similarity of the performance of different 3D printed nozzles are among the advantages of using 3D printing techniques to develop GDVN’s. Submicron printing resolution also makes it possible to easily improve GDVN performance by optimizing the design of nozzles. In this study, 3D printed nozzles were developed to achieve low liquid and gas flow rates and high liquid jet velocities. A double-pulsed nanosecond laser imaging system was used to perform Particle Tracking Velocimetry (PTV) in order to determine jet velocities and assess jet stability/reproducibility. The testing results of pure water jets focused with He sheath gas showed that some designs can easily achieve stable liquid jets with velocities of more than 80 m/s, with pure water flowing at 3 microliters/min, and helium sheath gas flowing at less than 5 mg/min respectively. A numerical simulation pipeline was also used to characterize the performance of different 3D printed GDVNs. The results highlight the potential of making reproducible GDVNs with minimum fabrication effort, that can meet the requirements of present and future SFX and time-resolved solution scattering research.


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Details

Title
  • 3D Printed Gas Dynamic Virtual Nozzles for X-Ray Laser Sample Deliveryand Optical Characterization of Microjets and Microdroplets
Contributors
Date Created
2020
Resource Type
  • Text
  • Collections this item is in
    Note
    • Doctoral Dissertation Mechanical Engineering 2020

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