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Proceedings Papers

Deep Learning for Prediction of Print Parameters and Realized Electrical Performance and Geometry on Inkjet Platform

Pradeep Lall, Shriram Kulkarni, Ved Soni, Kartik Goyal, Scott Miller
Proc. ASME. InterPACK2022, ASME 2022 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems, V001T03A008, October 25–27, 2022
Paper No: IPACK2022-97437
DOI: https://doi.org/10.1115/IPACK2022-97437
... is necessary to print reliable and fine conductive traces. The inks used for this analysis are both particle and particle-free silver inks, and the comparison of the same is also studied. A closed-loop control algorithm is used to attain the desired electrical and geometrical values by changing the print...
View Paper titled, Deep Learning for Prediction of Print Parameters and Realized Electrical Performance and Geometry on Inkjet Platform
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Topics: Artificial neural networks, Geometry, Inks, Printing, Dimensions, Particulate matter, Computer software, Control algorithms, Electronics, Regression models