Data-Driven Analysis of Droplet Morphology in Inkjet Systems: Toward Generating Stable Single-Drop Regimes

Abstract

The growing demand for new microelectronic devices and pharmaceutical advancements has heightened interest in inkjet printing as a means of high-precision manufacturing technique. This study leverages data-driven analyses to optimize droplet generation processes in a drop-on-demand dispensing system. A three-voltage pulse scheme was employed to produce droplets, with high-resolution images captured and processed to extract geometric features of the principal droplet. This resulted in a comprehensive, openly published dataset, along with a detailed, reproducible image processing pipeline. By analyzing this data, we identified key operational parameters and established correlations between inputs and outputs, providing insights into consistent single-droplet generation. These findings offer practical guidelines for controlling droplet morphology and advancing applications in inkjet printing.