Publication: Modeling and simulation of organic field effect transistor (ofet) using artificial neural networks for flexible electronics
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Date
2024-07
Authors
Sundraj Neemal a/l Retnakumar
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Abstract
Nowadays, the Organic Field Effect Transistors (OFETs) have emerged as promising candidates for low-cost, lightweight, and flexible electronic devices.
However, the choice of dielectric material significantly influences their electrical performance, particularly in reducing operational voltage for potential applications. The primary objective is to explore the potential applications and ensure the reliable performance of OFETs in the realm of flexible electronics through modeling and simulation using Artificial Neural Networks. The research problem lies in the lack of precise understanding of how dielectric constants affect OFET performance, hindering the development of optimized device configurations. Traditional numerical methods often lack accuracy and flexibility in simulating dielectric effects. To address this, the project progresses through six stages: designing and simulating OFET components including gate dielectrics, extracting key electrical parameters, and comparing performance between different dielectric materials. Utilizing Silvaco ATLAS, simulations are conducted on p-type pentacene-based OFETs with silicon dioxide (SiO2) and Poly(vinyl alcohol) (PVA) dielectrics. Key findings include the analysis of output and transfer characteristics for both SiO2 and PVA dielectrics. The implications of this research are significant for the design and optimization of OFETs for potential
device applications. By understanding the influence of dielectric materials, engineers can enhance device performance and efficiency, paving the way for advancements in flexible electronics, biosensing, and display technologies.