EMI shielding applications of PANI-Ferrite nanocomposite materials: A review
Source abstract
Abstract
The issue of electromagnetic pollution, also known as electromagnetic interference (EMI), is brought on by the rapid development of electronic devices and wireless communication technology. The purpose of electromagnetic shielding interference is to shield the electronic device from interruptions and to prevent harm to the device. As a result, EMI shielding materials have been developed to address the pressing issue. In recent years, EMI shielding materials have changed from traditional single-function to multi-function designs to better accommodate diverse application contexts. Various strategies have been adopted to prevail over the limitations of metal-based EMI shielding materials. Ferrites and their composites have recently attracted the interest of researchers due to their biocompatibility, biodegradability, and variety of uses in various fields including EMI shielding. Ferrite nanocomposites are combined with Polyaniline (PANI) to form PANI-ferrite nanocomposites. In addition to having good qualities, polymer nanocomposites can be designed to display a combination of properties for multifunctional applications. When the particle size is decreased below 30 nm, the properties of ferrite particles, which are very relevant materials, perform better. Therefore, the size and distribution of the particles inside the polymer matrix play a major role in determining the superparamagnetic nature of ferrite particles and their polymer nanocomposites. In this work, we investigated ferrite-based materials for the reduction of EMI using reflection and absorption approaches. Also highlighted the popular techniques for the synthesis of ferrite composites and their EMI shielding efficiency.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Electromagnetic wave absorption materials · Advanced Energy Technologies and Civil Engineering Innovations
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (100+)
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