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An Analytical Approach to Calculate the Charge Density of Biofunctionalized Graphene Layer Enhanced by Artificial Neural Networks

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Abstract

Graphene, a purely two-dimensional sheet of carbon atoms, as an attractive substrate for plasmonic nanoparticles is considered because of its transparency and atomically thin nature. Additionally, its large surface area and high conductivity make this novel material an exceptional surface for studying adsorbents of diverse organic macromolecules. Although there are plenty of experimental studies in this field, the lack of analytical model is felt deeply. Comprehensive study is done to provide more information on understanding of the interaction between graphene and DNA bases. The electrostatic variations occurring upon DNA hybridization on the surface of a graphene-based field-effect DNA biosensor is modeled theoretically and analytically. To start with modeling, a liquid field effect transistor (LGFET) structure is employed as a platform, and graphene charge density variations in the framework of linear Poisson– Boltzmann theories are studied under the impact induced by the adsorption of different values of DNA concentration on its surface. At last, the artificial neural network is used for improving the curve fitting by adjusting the parameters of the proposed analytical model.

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Acknowledgments

The authors would like to acknowledge the financial support from the Research University grant of the Ministry of Higher Education (MOHE), Malaysia, under project vot number: 4J011. Also thanks to the Research Management Centre (RMC) of Universiti Teknologi Malaysia (UTM) for providing an excellent research environment in which to complete this work.

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Authors and Affiliations

  1. Malaysia -Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, 54100, Kuala Lumpur, Malaysia

    Hediyeh Karimi & Mohd Fauzi Othman

  2. Faculty of Science, Engineering and Technology, Swinburne University of Technology, Hawthorn, VIC 3122, Australia

    Rasoul Rahmani

  3. Centre for Artificial Intelligence Technology, Faculty of Information Science and Technology,, Universiti Kebangsaan Malaysia, 43600 Bangi Selangor, Malaysia

    Bahareh Zohoori

  4. Department of Computer Engineering, Malard Branch, Islamic Azad University, Malard, Iran

    Mohsen Mahrami

  5. Centre for Environmental Sustainability and Water Security (IPASA), Faculty of Civil Engineering, Department of Environmental Engineering, Universiti Teknologi Malaysia, 81310 Johor, Malaysia

    Hesam Kamyab

  6. Information Systems Department, Faculty of Information and communication Technology, International Islamic University Malaysia, Kuala Lumpur, 53100, Selangor, Malaysia

    Seyed Ebrahim Hosseini

Authors
  1. Hediyeh Karimi
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  2. Rasoul Rahmani
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  3. Mohd Fauzi Othman
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  4. Bahareh Zohoori
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  5. Mohsen Mahrami
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  6. Hesam Kamyab
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  7. Seyed Ebrahim Hosseini
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Correspondence to Mohd Fauzi Othman.

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Karimi, H., Rahmani, R., Othman, M.F. et al. An Analytical Approach to Calculate the Charge Density of Biofunctionalized Graphene Layer Enhanced by Artificial Neural Networks. Plasmonics 11, 95–102 (2016). https://doi.org/10.1007/s11468-015-9998-y

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  • DOI: https://doi.org/10.1007/s11468-015-9998-y

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