Experimental Investigation of High-Viscosity Conductive Pastes and the Optimization of 3D Printing Parameters

Abstract

Traditional contact printing technology is primarily controlled by the shape of the mask to form the size, while for the more popular non-contact printing technologies, in recent years, adjusting the print parameters has become a direct way to control the result of the printing. High-viscosity conductive pastes are generally processed by screen printing, but this method has limited accuracy and wastes material. Direct-write printing is a more material-efficient method, but the printing of high-viscosity pastes has extrusion difficulties, which affects the printed line width. In this paper, we addressed these problems by studying the method of printing high-viscosity conductive paste with a self-made glass nozzle. Then, by parameter optimization, we achieved the minimum line width printing. The results showed that the substrate moving speed, the print height, and the feed pressure were the key factors affecting the line width and stability. The combination of the printing parameters of 0.6 MPa feed pressure, 200 mm/s substrate moving speed, and 150 μm print height can achieve a line width of approximately 30 μm. In addition, a mathematical model of the line width and parameters was established, and the prediction accuracy was within 5%. The results and the prediction model of the parameters provide an important reference for the printing of high-viscosity pastes, which have immense potential applications in electronics manufacturing and bioprinting.

Material Extrusion Filament Width and Height Prediction via Design of Experiment and Machine Learning

“…This processing method shows good material compatibility, simple operation, and an economical equipment cost [13][14][15]. It has also been widely applied in the processing of flexible robots [16,17], wearable sensors [18,19], tissue engineering [20,21], electronic components [22,23], and food materials [24,25], exhibiting its huge application potential across diverse domains.…”

“…As a statistical analysis method, factorial design can reveal the degree of influence of printing parameters on response variables through statistical results [31]. Zhang et al [22] investigated the effects of extrusion pressure, nozzle head height, and substrate moving speed on printed filament width by orthogonal experimental design. The results of the range analysis unveiled a descending hierarchy of effects for these three factors: printing speed, extrusion pressure, and nozzle height.…”