In-Line Diagnostics for Inkjet Printed Electronics

The development of solution processed thin film circuits involves various process stages. One of the key parameters that decides the performance of the circuit is the semiconductor-insulator interface and the quality of the insulator. Usually, the performance of the transistor is ascertained only after all layers are deposited and the transistor is characterized. This work is an attempt to guess the performance of the transistor after the dielectric deposition by using optical methods to extract dielectric quality. The technique can become a part of the manufacturing process to provide feedback and warnings at an early stage of the process flow thereby improving reliability and reducing costs.

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Publication Details

Published
2024-09-15
DOI
https://doi.org/10.1109/ifetc61155.2024.10771855
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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In-Line Diagnostics for Inkjet Printed Electronics

Jaya Prakash, Piyush Ranjan, Sanjiv Sambandan, Poojari Naga Pradeep et al.
Industrial Vision Systems and Defect Detection
article

In-Line Diagnostics for Inkjet Printed Electronics

Jaya Prakash, Piyush Ranjan, Sanjiv Sambandan, Poojari Naga Pradeep, Omkar Deokinandan Nayak Shinkre
article en

Abstract

The development of solution processed thin film circuits involves various process stages. One of the key parameters that decides the performance of the circuit is the semiconductor-insulator interface and the quality of the insulator. Usually, the performance of the transistor is ascertained only after all layers are deposited and the transistor is characterized. This work is an attempt to guess the performance of the transistor after the dielectric deposition by using optical methods to extract dielectric quality. The technique can become a part of the manufacturing process to provide feedback and warnings at an early stage of the process flow thereby improving reliability and reducing costs.

Indian Institute of Science Bangalore (IN)
Openalex Percentile: Top 63%
Industrial Vision Systems and Defect Detection
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