Predictive Modeling and Design Automation of Inorganic Printed Electronics
Farhan Rasheed1,2,a, Michael Hefenbrock3,2,b, Rajendra Bishnoi1,c, Michael Beigl3,d, Jasmin Aghassi-Hagmann2,4,e and Mehdi B. Tahoori1,f
1Chair of Dependable Nano Computing (CDNC), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
2Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen, Germany
3Chair of Pervasive Computing Systems-TECO, Karlsruhe Institute of Technology(KIT), Karlsruhe, Germany
4Department of Electrical Engineering and Information Technology, Offenburg University of Applied Sciences, Offenburg, Germany
afarhan.rasheed@kit.edu
bmichael.hefenbrock@kit.edu
crajendra.bishnoi@kit.edu
dmichael.beigl@kit.edu
ejasmin.aghassi@kit.edu
fmehdi.tahoori@kit.edu
ABSTRACT
Printed Electronics is perceived to have a major impact in the fields of smart sensors, Internet of Things and wearables. Especially low power printed technologies such as electrolyte gated field effect transistors (EGFETs) using solutionprocessed inorganic materials and inkjet printing are very promising in such application domains. In this paper, we discuss a modeling approach to describe the variations of printed devices. Incorporating these models and design flows into our previously developed printed design system allows for robust circuit design. Additionally, we propose a reliability-aware routing solution for printed electronics technology based on the technology constraints in printing crossovers. The proposed methodology was validated on multiple benchmark circuits and can be easily integrated with the design automation tools-set.
Keywords: Additive manufacturing technology, printed electronics, process design kit, variability modeling and routing
