The mechanics of fluid jetting for droplet deposition

Recent research has demonstrated that droplet ejection angles in acoustofluidic jetting can exceed ±45°, surpassing the Rayleigh angle limit when surface tension is considered alongside acoustic streaming and inertia. Building on this foundation, we investigate the final accuracy of droplet deposition by quantifying lateral deviations (∆x, ∆y) from the anticipated centerline impact. In this study, we systematically vary input asymmetry—through adjustments in vibrational velocity ratio and burst duration ratio—while maintaining constant average energy. Experiments were conducted using a focused interdigital transducer (FIDT) operating at 40 MHz, enabling high-resolution, nozzle-free jetting from sessile droplets. Our results show that increasing asymmetry leads to distinct, directional deposition errors. For a collection substrate positioned 5.20 mm from the jetting site, a velocity ratio of 0.2 produces lateral deviations of up to 800 µm in ∆x, while the corresponding vertical deviation in ∆y remains relatively modest at 180 µm. These deviations originate from force imbalance: the asymmetric input alters the net momentum direction of the jet, and droplets traveling farther before impact exhibit greater lateral drift. High-speed imaging and statistical analysis of more than 50 trials per condition confirm these trends across ejection angles ranging from 0° to ±45°. We extend a theoretical force vector model—incorporating acoustic streaming, inertia, and surface tension—to predict the resulting droplet landing locations. The model shows strong agreement with experimental averages across both input control methods, supporting the use of a quasi-static force summation framework for predicting droplet trajectory. We present deposition error maps for both velocity and duration ratio approaches, showing how deviations increase nonlinearly as input ratios diverge from unity. These findings clarify how trajectory drift emerges purely from signal asymmetry and offer a predic tive foundation for controlling lateral droplet placement in SAW jetting systems. This work advances the fluid dynamics of acoustically driven free-surface flows and provides a quantitative tool for deposition control.