A polyethylene oxide-based composite solid polymer electrolyte filled with one-dimensional ceramic Li0.33La0.557TiO3 nanofibers was designed and prepared.

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Lithium–sulfur (Li‐S) batteries have been considered as a promising next‐generation energy storage system. However, practical application of Li‐S batteries is hindered by the nonconductive nature of sulfur (S) and continuous capacity fading during cycling. Here, a simple but effective strategy is proposed to fabricate high‐performance Li‐S batteries by in situ polymerization of polyaniline (PANi)/S/carbon nanofiber (CNF) cathode. Compared to traditional carbon black/S cathodes and other cathode materials with PANi polymer, this effective three‐dimensional (3D) cathode design has several advantages: (i) the interconnected and highly conductive CNF/PANi network structure facilitates the electron transfer between the insulating S and conductive CNF mat; (ii) the CNF/PANi network structure, with abundant oxygen and nitrogen heteroatoms, offers strong adsorption for the polysulfides; (iii) the 3D architecture of CNF/S/PANi helps accommodate the volume change of S during cycling and maintain the structural integrity of the cathode; (iv) the easy and simple fabrication process minimizes the time and energy costs; and (v) the freestanding composite cathode without additional polymer binder contributes to higher energy density of Li‐S batteries. With all the advantages mentioned above, Li‐S cells present a high S utilization with stable cycling performance for over 300 cycles with a low capacity decay rate of 0.08% cycle−1.

Due to the high surface area, porosity, and rigidity, applications of nanofibers and nanosurfaces have developed in recent years. Nanofibers and nanosurfaces are typically produced by electrospinning method. In the production process, determination of average fiber diameter is crucial for quality assessment. Average fiber diameter is determined by manually measuring the diameters of randomly selected fibers on scanning electron microscopy (SEM) images. However, as the number of the images increases, manual fiber diameter determination becomes a tedious and time consuming task as well as being sensitive to human errors. Therefore, an automated fiber diameter measurement system is desired. In the literature, this task is achieved by using image analysis algorithms. Typically, these methods first isolate each fiber in the image and measure the diameter of each isolated fiber. Fiber isolation is an error-prone process. In this study, automated calculation of nanofiber diameter is achieved without fiber isolation using image processing and analysis algorithms. Performance of the proposed method was tested on real data. The effectiveness of the proposed method is shown by comparing automatically and manually measured nanofiber diameter values.

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