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Parameter extraction in thin film transistors using artificial neural networks

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Abstract

This work presents a method based on supervised learning for the extraction of parameters in Indium Gallium Zinc Oxide Thin-Film Transistors with aluminium contacts, as an alternative regarding analytical and optimisation methods. The method consists of generating a set of I–V curves of the device of interest using Spice software. These curves are the input samples of the Artificial Neural Networks, from which it is intended to predict the different parameters such as threshold voltage, transconductance and contact resistance, from each sample curve. By generating the training set itself, it is possible to label each sample curve, which allows the type of learning to be supervised. The results show that ANNs provide parameters with which it is possible to model physical measurements with error rates of less than 5% when extracting the first two parameters, and errors of between 0.06% and 4.62%, when extracting the three parameters. In addition, a comparison was made between the results of the ANNs and the analytical extraction of parameters.

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Data availability

The datasets generated during the current study are available from corresponding author.

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Acknowledgements

Nanoscience, Micro and Nanotechnologies Centre of the National Polytechnic Institute is thanked for the fabrication of devices whose transferential curves were used to test the methodology proposed in this research. Thanks, are also due to the National Council of Science and Technology for the scholarship for advanced studies.

Funding

The authors have not disclosed any funding.

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Authors and Affiliations

  1. Autonomous University of the State of Mexico, Toluca, State of Mexico, Mexico

    Roberto C. Valdés, Farid García, Rodolfo Z. García & Asdrúbal López

  2. Nanoscience, Micro and Nanotechnologies Centre of the IPN, Mexico City, Mexico

    Norberto Hernández

Authors
  1. Roberto C. Valdés
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  2. Farid García
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  3. Rodolfo Z. García
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  4. Asdrúbal López
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  5. Norberto Hernández
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Contributions

RCV performed the parameter extraction using NNs and drafted the manuscript, NHC manufactured the transistors with which the method proposed in this work was tested, RZG performed the parameter extraction using the analytical method, FGL and ALC analysed the proposed method and improved the form and wording of the manuscript.

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Correspondence to Roberto C. Valdés.

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Valdés, R.C., García, F., García, R.Z. et al. Parameter extraction in thin film transistors using artificial neural networks. J Mater Sci: Mater Electron 34, 555 (2023). https://doi.org/10.1007/s10854-023-09953-z

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