Author: Faiz Ahmad - July 2021
Saba Ayub,Beh Hoe Guan,Muhammad Faisal Javed ,Amir Mosavi,Imre Felde
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.
The methodology of this review exhibits the extraction of those articles which were published on the composite formation via traditional methods of various materials as electromagnetic shielding materials. Popular materials such as carbon, graphene, iron and polymer were taken into consideration, as it is important to know about their manufacturing behavior which impacts significantly on shielding effectiveness. VOSviewer software (version 1.6.11, 2021, Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands) was used to make keyword analysis of graphene- and metal-based composites, and graphene-, metal- and polymer-based composites articles. Furthermore, EMI studies related to artificial intelligence were also reviewed. A summary of the review methodology is demonstrated in Figure 1.
Health Effects:Electromagnetic waves can lead to stress, anxiety, and other psychological disorders.
Environmental Effects: Electromagnetic pollution can harm wildlife, affecting their navigation, reproduction, and overall health.
Health Protection: Shielding materials can significantly reduce exposure to harmful electromagnetic waves, thereby protecting public health.
Environmental Protection: By mitigating electromagnetic pollution, shielding materials help protect wildlife and maintain ecosystem balance.
Enhanced Performance of Electronic Devices: Shielding materials prevent interference, ensuring the reliable operation of electronic equipment.
The dependency of the traditional method is mainly on the structure of the material which has been taken to form a composite material. Moreover, many new methods have been introduced which need further investigation. Although there are many methods available for the formation of shielding material, very few are effective in giving desirable results. However, the area is still unexplored in terms of methods comparison. The opinion of method selection can be biased as most researchers present their findings as extraordinary without comparison. The most suitable way to observe the efficiency of a particular method for any composite is to make the same composite with different available methods and then perform the same analysis, which will give the true picture of the adopted methods. Moreover, the inclusion of machine learning in EMI applications can bring reform. This is still a gap in this area of knowledge and the investigation will be a benchmark for new researchers as it is time-consuming and costly if a wrong method is adopted. 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. There is a research trend in using advanced forms of machine learning for comparative analysis, research and development employing hybrid and ensemble machine learning methods to deliver higher performance.
Rising Electromagnetic Pollution:Electromagnetic pollution is escalating due to the proliferation of electronic devices, wireless communication, and industrial equipment, leading to heightened awareness and need for effective shielding solutions .
Health and Environmental Concerns:The adverse effects of electromagnetic waves on human health, including psychological disorders and immune system impacts, are increasing. This raises the demand for materials that can mitigate these effects .
Technological Advancements in Shielding Materials:Significant advancements in materials science have led to the development of new and more effective shielding materials. Graphene, carbon-based materials, and conductive polymers are at the forefront, offering superior shielding properties compared to traditional metals .
Diverse Application Areas:Electromagnetic shielding materials have applications across various industries including consumer electronics, telecommunications, automotive, aerospace, and healthcare. Each of these sectors is experiencing growth, thereby expanding the market for shielding solutions .