Sensing system with an artificial neural network based on floating-gate metal oxide semiconductor transistors

• J.L. González Vidal ^[1] ; M.A. Reyes-Barranca ^[2] ; E.N. Vázquez-Acosta ^[2] ; J.J. Raygoza Panduro ^[3]
  1. [1] Universidad Autónoma del Estado de Hidalgo

     Universidad Autónoma del Estado de Hidalgo

     México

     
  2. [2] Instituto Politécnico Nacional

     Instituto Politécnico Nacional

     México

     
  3. [3] Universidad de Guadalajara

     Universidad de Guadalajara

     México

     

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• Localización: Revista Mexicana de Física, ISSN-e 0035-001X, Vol. 66, Nº. 1, 2020, págs. 91-97
• Idioma: inglés
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• Resumen

  • This paper shows a novel design of a gas sensor system based on artificial neural networks and floating-gate metal oxide semiconductor transistors. Two types of circuits with floating-gate metal oxide semiconductor transistors of minimum dimensions were designed and simulated by Simulink of Matlab; simulations and experimental measurements results were compared, obtaining good expectations. The reason for using floating-gate metal oxide semiconductor is that artificial neural networks can also be implemented with these kinds of devices, since artificial neural networks based on floating-gate metal oxide semiconductors are able to produce pseudo-Gaussian-functions. These functions give a reliable option to determine gas concentration. A sensitive thin film can be deposited on the floating-gate metal oxide semiconductor floating gate, which produces a charge variation due to the chemical reaction between the sensitive layer and the gas species, modifying the threshold voltage thereby a correlation of drain current of the floating-gate metal oxide semiconductor with gas concentration can be obtained. Therefore, a generator circuit was implemented for the pseudo Gaussian signal with the floating-gate metal oxide semiconductor. This system can be applied in environments with dangerous species such as CO_(2), CO, methane, propane, among others. Simulations demonstrated that the implemented proposal has a good performance as an alternative method for sensing gas concentrations, compared with conventional sensors.