Modeling of Electrolyte-Gated Organic Thin-Film Transistors for Sensing Applications
In this paper, we present a modeling framework suited for the theoretical study of electrolyte-gated organic thin-film transistors. Employing a novel, fully self-consistent, coupled Poisson-Boltzmann/drift-diffusion simulator, we analyze the response of biosensors for varying bias conditions and ion...
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Published in | IEEE transactions on electron devices Vol. 62; no. 12; pp. 4206 - 4212 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.12.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | In this paper, we present a modeling framework suited for the theoretical study of electrolyte-gated organic thin-film transistors. Employing a novel, fully self-consistent, coupled Poisson-Boltzmann/drift-diffusion simulator, we analyze the response of biosensors for varying bias conditions and ion concentrations in the electrolyte. Our model considers the diffusive nature of ions in the electrolyte region, the formation of a Helmholtz layer at the electrolyte/organic semiconductor interface and the particular charge transport mechanisms of organic semiconductors, such as field-dependent mobility and the presence of defect states. We calibrate our model on a set of current-voltage measurements for a fabricated device. Once validated, our simulation model offers useful insights in the underlying physics and helps us quantify the impact of the electrolyte solution on the surface potential at the electrolyte/semiconductor interface. A sensitivity analysis is performed to determine the inaccuracy of simpler models, such as the Helmholtz approximation, on the response of our biosensor. Improving our understanding of the working principle and charge transport in such novel electrolyte-gated Organic Thin Film Transistors is an indispensable step toward performance optimization and can pave the way for the design of new, more sensitive biosensor devices. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0018-9383 1557-9646 |
DOI: | 10.1109/TED.2015.2485160 |