A. Bucciarelli, A. Adami, Chandrakanth Reddy Chandaiahgari, L. Lorenzelli
{"title":"Multivariable optimization of inkjet printing process of Ag nanoparticle ink on Kapton","authors":"A. Bucciarelli, A. Adami, Chandrakanth Reddy Chandaiahgari, L. Lorenzelli","doi":"10.1109/FLEPS49123.2020.9239474","DOIUrl":null,"url":null,"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.","PeriodicalId":101496,"journal":{"name":"2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FLEPS49123.2020.9239474","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
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.