In this work we presented a statistical method to optimize the production of conductive layers by inkjet printing. This statistical method, namely Design of Experiment (DOE), was applied to the deposition of silver nanoparticle ink on Kapton. The process optimization was conducted by a double step. In the first phase, we optimized the getting waveform assigned to the piezoelectric head to form the ink drop in order to have the drop with the smaller diameter and standard deviation. In the second step, we optimized the area covered by the deposition of a specific pattern. The deposition strategy was then optimized to best reproduce the theoretical pattern. The entire process was conducted by analyzing the images acquired with a high-resolution camera and successively using DOE to fit the data and determine empirical models linking the process parameters to the measured outcome. These models allowed us to optimize the process by solving a system of equations giving a quantification on the printing quality.

Design of experiment rational optimization of an inkjet deposition of silver on Kapton

Alessio Bucciarelli;Emanuele Olivetti;Andrea Adami;Leandro Lorenzelli
2021-01-01

Abstract

In this work we presented a statistical method to optimize the production of conductive layers by inkjet printing. This statistical method, namely Design of Experiment (DOE), was applied to the deposition of silver nanoparticle ink on Kapton. The process optimization was conducted by a double step. In the first phase, we optimized the getting waveform assigned to the piezoelectric head to form the ink drop in order to have the drop with the smaller diameter and standard deviation. In the second step, we optimized the area covered by the deposition of a specific pattern. The deposition strategy was then optimized to best reproduce the theoretical pattern. The entire process was conducted by analyzing the images acquired with a high-resolution camera and successively using DOE to fit the data and determine empirical models linking the process parameters to the measured outcome. These models allowed us to optimize the process by solving a system of equations giving a quantification on the printing quality.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/324896
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
social impact