Drop speeds from drop-on-demand ink-jet print heads

Measured drop speeds from a range of industrial drop-on-demand (DoD) ink-jet print head designs scale with the predictions of very simple physical models and results of numerical simulations. The main drop/jet speeds at a specified stand-off depend on fluid properties, nozzle exit diameter, and print head drive amplitude for fixed waveform timescales. Drop speeds from the Xaar, Spectra Dimatix, and MicroFab DoD print heads tested with (i) Newtonian, (ii) weakly elastic, and (iii) highly shear-thinning fluids all show a characteristic linear rise with drive voltage (setting) above an apparent threshold drive voltage. Jetting, simple modeling approaches, and numerical simulations of Newtonian fluids over the typical DoD printing range of surface tensions and viscosities were studied to determine how this threshold drive value and the slope of the characteristic linear rise depend on these fluid properties and nozzle exit area. The final speed is inversely proportional to the nozzle exit area, as expected from volume conservation. These results should assist specialist users in the development and optimization of DoD applications and print head design. For a given density, the drive threshold is determined primarily by viscosity, and the constant of proportionality k linking speed with drive above a drive threshold becomes independent of viscosity and surface tension for more viscous DoD fluid jetting. © 2013 Society for Imaging Science and Technology.

Regimes of Polymer Behaviour in Drop-on-Demand Ink-Jetting

Three regimes of fast DoD jetting behaviour for solutions of mono-disperse linear polymers have been linked to the underlying polymer molecular chains and their fully extended length L in good solvents. This allows scaling laws in molecular weight to be predicted and applied to experimental jetting results from different DoD print heads. The higher extensional flows encountered in high speed jetting in viscous solvents can fully stretch linear molecules outside the nozzle, permitting jetting of higher polymer content than for purely elastic behaviour. These results are significant for DoD printing at raised jet speeds and will apply to any DoD print head jetting linear polymer solutions.

A simple criterion for filament break-up in drop-on-demand inkjet printing

Jets from drop-on-demand inkjet print-heads consist of a main drop with a trailing filament, which either condenses into the main drop, or breaks up into satellite drops. Filament behaviour is quantitatively similar to that of larger, free symmetrical filamentscan be predicted from the aspect ratio and Ohnesorge number. Symmetrical filaments generated from inkjet print-heads show the same behaviour. A simple model, based on competition between the processes of axial shortening and radial necking, predicts the critical aspect ratio below which the jet condenses into a single drop. The success of this simple criterion supports the underlying physical model. © 2013 American Institute of Physics.

Time-resolved particle image velocimetry within the nozzle of a drop-on-demand printhead

Time-resolved particle image velocimetry (PIV) has been performed inside the nozzle of a commercially available inkjet print-head to obtain the time-dependent velocity waveform. A printhead with a single transparent nozzle 80 μm in orifice diameter was used to eject single droplets at a speed of 5 m/s. An optical microscope was used with an ultra-high-speed camera to capture the motion of particles suspended in a transparent liquid at the center of the nozzle and above the fluid meniscus at a rate of half a million frames per second. Time-resolved velocity fields were obtained from a fluid layer approximately 200 μm thick within the nozzle for a complete jetting cycle. A Lagrangian finite-element numerical model with experimental measurements as inputs was used to predict the meniscus movement. The model predictions showed good agreement with the experimental results. This work provides the first experimental verification of physical models and numerical simulations of flows within a drop-on-demand nozzle. © 2012 Society for Imaging Science and Technology.

Experiments and Lagrangian simulations on the formation of droplets in drop-on-demand mode

The creation and evolution of millimeter-sized droplets of a Newtonian liquid generated on demand by the action of pressure pulses were studied experimentally and simulated numerically. The velocity response within a model, large-scale printhead was recorded by laser Doppler anemometry, and the waveform was used in Lagrangian finite-element simulations as an input. Droplet shapes and positions were observed by shadowgraphy and compared with their numerically obtained analogues. © 2011 American Physical Society.

Gene function prediction from synthetic lethality networks via ranking on demand.

MOTIVATION: Synthetic lethal interactions represent pairs of genes whose individual mutations are not lethal, while the double mutation of both genes does incur lethality. Several studies have shown a correlation between functional similarity of genes and their distances in networks based on synthetic lethal interactions. However, there is a lack of algorithms for predicting gene function from synthetic lethality interaction networks. RESULTS: In this article, we present a novel technique called kernelROD for gene function prediction from synthetic lethal interaction networks based on kernel machines. We apply our novel algorithm to Gene Ontology functional annotation prediction in yeast. Our experiments show that our method leads to improved gene function prediction compared with state-of-the-art competitors and that combining genetic and congruence networks leads to a further improvement in prediction accuracy.