Rational Design of Field-Effect Sensors Using Partial Differential Equations, Bayesian Inversion, and Artificial Neural Networks

Research output: Contribution to journalArticleResearchpeer review

Authors

  • Amirreza Khodadadian
  • Maryam Parvizi
  • Mohammad Teshehlab
  • Clemens Heitzinger

External Research Organisations

  • K.N. Toosi University of Technology
  • TU Wien (TUW)
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Details

Original languageEnglish
Article number4785
Number of pages18
JournalSensors
Volume22
Issue number13
Early online date24 Jun 2022
Publication statusPublished - 1 Jul 2022

Abstract

Silicon nanowire field-effect transistors are promising devices used to detect minute amounts of different biological species. We introduce the theoretical and computational aspects of forward and backward modeling of biosensitive sensors. Firstly, we introduce a forward system of partial differential equations to model the electrical behavior, and secondly, a backward Bayesian Markov-chain Monte-Carlo method is used to identify the unknown parameters such as the concentration of target molecules. Furthermore, we introduce a machine learning algorithm according to multilayer feed-forward neural networks. The trained model makes it possible to predict the sensor behavior based on the given parameters.

Keywords

    Bayesian inversion, biosensors, charge transport, field-effect sensors, inverse modeling, neural networks

ASJC Scopus subject areas

Cite this

Rational Design of Field-Effect Sensors Using Partial Differential Equations, Bayesian Inversion, and Artificial Neural Networks. / Khodadadian, Amirreza; Parvizi, Maryam; Teshehlab, Mohammad et al.
In: Sensors, Vol. 22, No. 13, 4785, 01.07.2022.

Research output: Contribution to journalArticleResearchpeer review

Khodadadian A, Parvizi M, Teshehlab M, Heitzinger C. Rational Design of Field-Effect Sensors Using Partial Differential Equations, Bayesian Inversion, and Artificial Neural Networks. Sensors. 2022 Jul 1;22(13):4785. Epub 2022 Jun 24. doi: 10.3390/s22134785
Khodadadian, Amirreza ; Parvizi, Maryam ; Teshehlab, Mohammad et al. / Rational Design of Field-Effect Sensors Using Partial Differential Equations, Bayesian Inversion, and Artificial Neural Networks. In: Sensors. 2022 ; Vol. 22, No. 13.
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