Precise dot inkjet printing thought multifactorial statistical optimization of the piezoelectric actuator waveform

InkJet printing is a technique that in the last decades has attracted the attention of the scientific community because it allows producing customized patterns with a variety of inks and substrates, making it suitablemethod for the production of flexible circuits. However, the optimization of this technique is still problematic due to a large number of process variables. Among them the modification of the waveform parameters of the piezoelectric actuator that allows the ejections of the ink can be effective in tuning the printing quality. This work reports a study by a statistical method, namely Design of Experiments (DOE), to optimize the inkjet printing parameters for a nanoparticle-based silver (Ag) ink. This method showed the interplay of the waveform parameters into the definition of optimal drop reproducibility and the achievement of the optimal resolution. In particular, it is shown that mixed terms of the model have a statistical significance and therefore the proposed multifactorial approach provides a benefit in the optimization with respect to the more commonly used one-factor-at-a-time models (OFAT). For the first time, empirical equations have been reported within the corresponding 95% confidence intervals. These equations can be used as a tool to directly tune the properties of the printed dot by modifying the waveform parameters. As case study, we proposed the combinations of a commercial Ag nanoparticles ink with Kapton, a commonly used substrate for flexible electronics.