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Fibrous wearable and implantable devices have emerged as a promising technology, offering a range of new solutions for minimally invasive monitoring of human health. Compared to traditional biomedical devices, fibers offer a possibility for a modular design compatible with large-scale manufacturing and a plethora of advantages including mechanical compliance, breathability, and biocompatibility. The new generation of fibrous biomedical devices can revolutionize easy-to-use and accessible health monitoring systems by serving as building blocks for most common wearables such as fabrics and clothes. Despite significant progress in the fabrication, materials, and application of fibrous biomedical devices, there is still a notable absence of a comprehensive and systematic review on the subject. This review paper provides an overview of recent advancements in the development of fibrous wearable and implantable electronics. We categorized these advancements into three main areas: manufacturing processes, platforms, and applications, outlining their respective merits and limitations. The paper concludes by discussing the outlook and challenges that lie ahead for fiber bioelectronics, providing a holistic view of its current stage of development.

 

This study employs all-atomistic (AA) molecular dynamics (MD) simulations to investigate the crystallization and melting behavior of polar and nonpolar polymer chains on monolayers of graphene and graphene oxide (GO). Polyvinyl alcohol (PVA) and polyethylene (PE) are used as representative polar and nonpolar polymers, respectively. A modified order parameter is introduced to quantify the degree of two-dimensional (2D) crystallization of polymer chains. Our results show that PVA and PE chains exhibit significantly different crystallization behavior. PVA chains tend to form a more rounded, denser, and folded-stemmed lamellar structure, while PE chains tend to form an elongated straight pattern. The presence of oxidation groups on the GO substrate reduces the crystallinity of both PVA and PE chains, which is derived from the analysis of modified order parameter. Meanwhile, the crystallization patterns of polymer chains are influenced by the percentage, chemical components, and distribution of the oxidation groups. In addition, our study reveals that 2D crystalized polymer chains exhibit different melting behavior depending on their polarity. PVA chains exhibit a more molecular weight-dependent melting temperature than PE chains, which have a lower melting temperature and are relatively insensitive to molecular weight. These findings highlight the critical role of substrate and chain polarity in the crystallization and melting of polymer chains. Overall, our study provides valuable insights into the design of graphene-based polymer heterostructures and composites with tailored properties. 

In this paper, we develop a mixed stochastic approximation expectation‐maximization (MSAEM) algorithm coupled with a Gibbs sampler to compute the marginalized maximum a posteriori estimate (MMAPE) of a confirmatory multidimensional four‐parameter normal ogive (M4PNO) model. The proposed MSAEM algorithm not only has the computational advantages of the stochastic approximation expectation‐maximization (SAEM) algorithm for multidimensional data, but it also alleviates the potential instability caused by label‐switching, and then improved the estimation accuracy. Simulation studies are conducted to illustrate the good performance of the proposed MSAEM method, where MSAEM consistently performs better than SAEM and some other existing methods in multidimensional item response theory. Moreover, the proposed method is applied to a real data set from the 2018 Programme for International Student Assessment (PISA) to demonstrate the usefulness of the 4PNO model as well as MSAEM in practice.