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Review

Preparation Methods for Graphene Metal and Polymer Based Composites for EMI Shielding Materials: State of the Art Review of the Conventional and Machine Learning Methods

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Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Malaysia
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Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Malaysia
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Department of Civil Engineering, COMSATS University Islamabad Abbottabad Campus, Abbottabad 22060, Pakistan
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John von Neumann Faculty of Informatics, Obuda University, 1034 Budapest, Hungary
*
Authors to whom correspondence should be addressed.
Academic Editor: Jacek Trzaska
Metals 2021, 11(8), 1164; https://doi.org/10.3390/met11081164
Received: 10 June 2021 / Revised: 16 July 2021 / Accepted: 17 July 2021 / Published: 22 July 2021
Advancement of novel electromagnetic inference (EMI) materials is essential in various industries. The purpose of this study is to present a state-of-the-art review on the methods used in the formation of graphene-, metal- and polymer-based composite EMI materials. The study indicates that in graphene- and metal-based composites, the utilization of alternating deposition method provides the highest shielding effectiveness. However, in polymer-based composite, the utilization of chemical vapor deposition method showed the highest shielding effectiveness. Furthermore, this review reveals that there is a gap in the literature in terms of the application of artificial intelligence and machine learning methods. The results further reveal that within the past half-decade machine learning methods, including artificial neural networks, have brought significant improvement for modelling EMI materials. We identified a research trend in the direction of using advanced forms of machine learning for comparative analysis, research and development employing hybrid and ensemble machine learning methods to deliver higher performance. View Full-Text
Keywords: electromagnetic inferences; shielding; graphene; metal; polymer; traditional methods; machine learning; artificial intelligence; data science; materials design electromagnetic inferences; shielding; graphene; metal; polymer; traditional methods; machine learning; artificial intelligence; data science; materials design
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MDPI and ACS Style

Ayub, S.; Guan, B.H.; Ahmad, F.; Javed, M.F.; Mosavi, A.; Felde, I. Preparation Methods for Graphene Metal and Polymer Based Composites for EMI Shielding Materials: State of the Art Review of the Conventional and Machine Learning Methods. Metals 2021, 11, 1164. https://doi.org/10.3390/met11081164

AMA Style

Ayub S, Guan BH, Ahmad F, Javed MF, Mosavi A, Felde I. Preparation Methods for Graphene Metal and Polymer Based Composites for EMI Shielding Materials: State of the Art Review of the Conventional and Machine Learning Methods. Metals. 2021; 11(8):1164. https://doi.org/10.3390/met11081164

Chicago/Turabian Style

Ayub, Saba, Beh H. Guan, Faiz Ahmad, Muhammad F. Javed, Amir Mosavi, and Imre Felde. 2021. "Preparation Methods for Graphene Metal and Polymer Based Composites for EMI Shielding Materials: State of the Art Review of the Conventional and Machine Learning Methods" Metals 11, no. 8: 1164. https://doi.org/10.3390/met11081164

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