A solution-processable and highly flexible conductor of a fluoroelastomer FKM and carbon nanotubes with tuned electrical conductivity and mechanical performance

The Emergence of AI-Based Wearable Sensors for Digital Health Technology: A Review

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.

Improving Mechanical, Electrical and Thermal Properties of Fluororubber by Constructing Interconnected Carbon Nanotube Networks with Chemical Bonds and F-H Polar Interactions

To improve the properties of fluororubber (FKM), aminated carbon nanotubes (CNTs-NH₂) and acidified carbon nanotubes (CNTs-COOH) were introduced to modulate the interfacial interactions in FKM composites. The effects of chemical binding and F-H polar interactions between CNTs-NH₂, CNTs-COOH, and FKM on the mechanical, electrical, thermal, and wear properties of the FKM composites were systematically investigated. Compared to the pristine FKM, the tensile strength, modulus at 100% strain, hardness, thermal conductivity, carbon residue rate, and electrical conductivity of CNTs-NH₂/CNTs-COOH/FKM were increased by 112.2%, 587.5%, 44.2%, 37.0%, 293.5%, and nine orders of magnitude, respectively. In addition, the wear volume of CNTs-NH₂/CNTs-COOH/FKM was reduced by 29.9%. This method provides a new and effective way to develop and design high-performance fluororubber composites.