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

TL;DR

This paper uses data-driven methods to analyze droplet shapes in inkjet systems, providing insights and guidelines for stable single-drop production in high-precision manufacturing.

Contribution

It introduces a comprehensive dataset and reproducible image processing pipeline to understand and optimize droplet morphology in inkjet printing.

Findings

Identified key operational parameters for droplet stability

Established correlations between input voltages and droplet shape

Provided practical guidelines for consistent single-droplet generation

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.