Multivariable optimization of inkjet printing process of Ag nanoparticle ink on Kapton
Alessio Bucciarelli, Andrea Adami, Chandrakanth Reddy Chandaiahgari, Leandro Lorenzelli
Abstract
This work reports a study by Design of Experiments (DOE) to optimize the inkjet printing parameters for a nanoparticle-based 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 multivariate approach provides a benefit in the optimization with respect to the more commonly used one-factor-at-a-time models.
Topics & Concepts
KaptonMultivariable calculusInkwellNanoparticleProcess (computing)FuzeInkjet printingDesign of experimentsReproducibilityComputer scienceMultivariate statisticsWaveformMaterials scienceDrop (telecommunication)NanotechnologyEngineeringMachine learningMathematicsControl engineeringStatisticsPolyimideTelecommunicationsOperating systemLayer (electronics)Speech recognitionMetallurgyRadarNanomaterials and Printing TechnologiesInnovative Microfluidic and Catalytic Techniques InnovationMicrofluidic and Bio-sensing Technologies