Tuning Electro-Magnetic Interference Shielding Efficiency of Customized Polyurethane Composite Foams Taking Advantage of rGO/Fe3O4 Hybrid Nanocomposites

Nanomaterials(2022)

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摘要
Electromagnetic interference (EMI) has been recognized as a new sort of pollution and can be considered as the direct interference of electromagnetic waves among electronic equipment that frequently affects their typical efficiency. As a result, shielding the electronics from this interfering radiation has been addressed as critical issue of great interest. In this study, different hybrid nanocomposites consisting of magnetite nanoparticles (Fe3O4) and reduced graphene oxide (rGO) as (conductive/magnetic) fillers, taking into account different rGO mass ratios, were synthesized and characterized by XRD, Raman spectroscopy, TEM and their magnetic properties were assessed via VSM. The acquired fillers were encapsulated in the polyurethane foam matrix with different loading percentages (wt%) to evaluate their role in EMI shielding. Moreover, their structure, morphology, and thermal stability were investigated by SEM, FTIR, and TGA, respectively. In addition, the impact of filler loading on their final mechanical properties was determined. The obtained results revealed that the Fe3O4@rGO composites displayed superparamagnetic behavior and acceptable electrical conductivity value. The performance assessment of the conducting Fe3O4@rGO/PU composite foams in EMI shielding efficiency (SE) was investigated at the X-band (8–12) GHz, and interestingly, an optimized value of SE −33 dBw was achieved with Fe3O4@rGO at a 80:20 wt% ratio and 35 wt% filler loading in the final effective PU matrix. Thus, this study sheds light on a novel optimization strategy for electromagnetic shielding, taking into account conducting new materials with variable filler loading, composition ratio, and mechanical properties in such a way as to open the door for achieving a remarkable SE.
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关键词
radiation interference,shielding,polyurethane foam,magnetite decorated rGO,mechanical optimization
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