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Crossover-aware placement and routing for inkjet printed circuits

  • Printed Electronics technology is a key-enabler for smart sensors, soft robotics, and wearables. The inkjet printed electrolyte-gated field effect transistor (EGFET) technology is a promising candidate for such applications due to its low-power operation, high field-effect mobility, and on-demand fabrication. Unlike conventional silicon-based technologies, inkjet printed electronics technology isPrinted Electronics technology is a key-enabler for smart sensors, soft robotics, and wearables. The inkjet printed electrolyte-gated field effect transistor (EGFET) technology is a promising candidate for such applications due to its low-power operation, high field-effect mobility, and on-demand fabrication. Unlike conventional silicon-based technologies, inkjet printed electronics technology is an additive manufacturing process where multiple layers are printed on top of each other to realize functional devices such as transistors and their interconnections. Due to the additive manufacturing process, the technology has limited routing layers. For routing of complex circuits, insulating crossovers are printed at the intersection of routing paths to isolate them. The crossover can alter the electrical properties of a circuit based on specific location on a routing path. In this work, we propose a crossover-aware placement and routing (COPnR) methodology for inkjet-printed circuits by integrating the crossover constraints in our design framework. Our proposed placement methodology is based on a state-of-the-art evolutionary algorithm while the routing optimization is done using a genetic algorithm. The proposed methodology is compared with the industrial standard placement and routing (PnR) tools. On average, the proposed methodology has 38% fewer crossovers and 94% fewer failing paths compared to the industrial PnR tools applied to printed circuit designs.‚Ķshow moreshow less

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Metadaten
Author:Farhan Rasheed, Michael Hefenbrock, Rajendra Bishnoi, Michael Beigl, Jasmin Aghassi-HagmannORCiDGND, Mehdi Baradaran Tahoori
Creating Corporation:Association for Computing Machinery
Place of publication:New York
Year of Publication:2020
Language:English
Parent Title (English):ACM Journal on Emerging Technologies in Computing Systems
Volume:16
Issue:2
ISSN:1550-4832 (Print)
ISSN:1550-4840 (Online)
First Page:19:1
Last Page:19:22
Document Type:Article (reviewed)
Institutes:Bibliografie
Open Access:Zugriffsbeschränkt
Release Date:2020/12/15
Licence (German):License LogoEs gilt das UrhG
DOI:https://doi.org/10.1145/3375461