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Hybrid polymer nanocomposites based on polyvinylidene fluoride (PVDF) as the matrix, carbon nanotubes (CNTs) as the primary conductive filler, and metal nanoparticles as secondary fillers were fabricated by melt mixing. Secondary nanofillers with different geometry and properties (nickel nanowire (NiNW), silver nanowire (AgNW), nickel nanoparticle (NiNP), and silver nanoparticle (AgNP) were selected to investigate the effect of geometry and properties of secondary filler on the hybrid polymer nanocomposites' properties. Electrical conductivity, electromagnetic interference (EMI) shielding effectiveness, and complex microwave properties of the fabricated hybrid nanocomposites were studied in X-band frequency (8.2-12.4 GHz). The hybrid nanocomposites containing CNT/AgNW demonstrated superior conductivity and EMI shielding compared to individual fillers such as CNT, AgNW, NiNW, AgNP, NiNP, or hybrid system such as CNT/NiNW. The novelty of the present study lies in the unique synergy arising from the combination of nanofillers with similar geometry and high electrical conductivity, which resulted EMI shielding effectiveness as high as 27 dB for a shield with only 1.1 mm thickness. The EMI shielding mechanisms, including negative permittivity were studied and explained in details in the manuscript. KEYWORDS dielectric properties, electrical conductivity, EMI shielding, hybrid polymer nanocomposites, negative permittivity, 1 | INTRODUCTION Because of surprising rapid advances in wireless technology, and the ongoing miniaturization of electronic devices, there is a great demand for flexible, light, and thin electromagnetic interference [...]

It is our pleasure to serve as editors for this special issue of Polymer Engineering & Science in honor of the scientific contributions of Christopher W. Macosko, Professor of Chemical [...]

The use of plastics in automobiles is increasing dramatically due to their advantages of low weight and cost-effectiveness. Various products can be manufactured by recycling end-of-life vehicle (ELV) plastic waste, enhancing sustainability within this sector. This study presents the development of an electromagnetic interference (EMI) shield that can be used for protecting electronic devices in vehicles by recycling waste bumpers of ethylene propylene diene monomer (EPDM) rubber from ELVs. EPDM waste was added to a unique combination of  40 / 60 : PP/CaCO 3  master batch and conductive nanofiller of carbon nanotubes using an internal melt mixing process. This nanocomposite was highly conductive, with an electrical conductivity of  5.2 × 10 − 1 S · cm − 1  for 5 vol% CNT in a 30 wt% EPDM/70 wt% PP/CaCO 3  master batch and showed a high EMI shielding effectiveness of 30.4 dB. An ultra-low percolation threshold was achieved for the nanocomposite at 0.25 vol% CNT. Waste material in the composite improved the yield strain by about 46% and strain at break by 54% in comparison with the same composition without waste. Low cost and light-weight fabricated composite from ELV waste shows high EMI SE for application in electronic vehicles and opens a new path to convert waste to wealth. [ABSTRACT FROM AUTHOR]

Disease diagnosis and monitoring using conventional healthcare services is typically expensive and has limited accuracy. Wearable health technology based on flexible electronics has gained tremendous attention in recent years for monitoring patient health owing to attractive features, such as lower medical costs, quick access to patient health data, ability to operate and transmit data in harsh environments, storage at room temperature, non-invasive implementation, mass scaling, etc. This technology provides an opportunity for disease pre-diagnosis and immediate therapy. Wearable sensors have opened a new area of personalized health monitoring by accurately measuring physical states and biochemical signals. Despite the progress to date in the development of wearable sensors, there are still several limitations in the accuracy of the data collected, precise disease diagnosis, and early treatment. This necessitates advances in applied materials and structures and using artificial intelligence (AI)-enabled wearable sensors to extract target signals for accurate clinical decision-making and efficient medical care. In this paper, we review two significant aspects of smart wearable sensors. First, we offer an overview of the most recent progress in improving wearable sensor performance for physical, chemical, and biosensors, focusing on materials, structural configurations, and transduction mechanisms. Next, we review the use of AI technology in combination with wearable technology for big data processing, self-learning, power-efficiency, real-time data acquisition and processing, and personalized health for an intelligent sensing platform. Finally, we present the challenges and future opportunities associated with smart wearable sensors. [ABSTRACT FROM AUTHOR]