In recent years, owing to the continuous development of polymer nanofiber manufacturing technology, various nanofibers with different structural characteristics have emerged, allowing their application in the field of sensing to continually expand. Integrating polymer nanofibers with optical sensors takes advantage of the high sensitivity, fast response, and strong immunity to electromagnetic interference of optical sensors, enabling widespread use in biomedical science, environmental monitoring, food safety, and other fields. This paper summarizes the research progress of polymer nanofibers in optical sensors, classifies and analyzes polymer nanofiber optical sensors according to different functions (fluorescence, Raman, polarization, surface plasmon resonance, and photoelectrochemistry), and introduces the principles, structures, and properties of each type of sensor and application examples in different fields. This paper also looks forward to the future development directions and challenges of polymer nanofiber optical sensors, and provides a reference for in-depth research of sensors and industrial applications of polymer nanofibers.

A novel photonic crystal fiber (PCF) sensor for refractive index detection based on polydimethylsiloxane (PDMS) is presented in this research, as well as designs for single-channel and dual-channel structures for this PDMS-PCF sensor. The proposed structures can be used to develop sensors with biocompatible polymers. The performance of the single-channel PDMS-PCF sensor was studied, and it was found that adjusting parameters such as pore diameter, lattice constant, distance between the D-shaped structure and the fiber core, and the radius of gold nanoparticles can optimize the sensor’s performance. The findings indicate that the detection range of the single-channel photonic crystal is 1.21–1.27. The maximum wavelength sensitivity is 10,000 nm/RIU with a resolution of $1\times {10}^{-5}$ RIU, which is gained when the refractive index is set to 1.27. Based on the results of the single-channel PCF, a dual-channel PDMS-PCF sensor is designed. The refractive index detection range of the proposed sensor is 1.2–1.28. The proposed sensor has a maximum wavelength sensitivity of 13,000 nm/RIU and a maximum resolution of $7.69\times {10}^{-6}$ RIU at a refractive index of 1.28. The designed PDMS-PCF holds tremendous potential for applications in the analysis and detection of substances in the human body in the future.

With the in-depth study of solid-state batteries (SSBs), various in situ and ex situ characterization technologies have been widely used to study them. The performance and reliability of SSBs are limited by the formation and evolution of lithium dendrites at the interfaces between solid electrodes and solid electrolytes. We propose a new method based on optical coherence tomography (OCT) for in situ characterization of the internal state of solid-state batteries. OCT is a low-loss, high-resolution, non-invasive imaging technique that can provide real-time monitoring of cross-sectional images of internal structures of SSBs. The morphology, growth, and evolution of lithium dendrites at different stages of cycling under various conditions can be visualized and quantified by OCT. Furthermore, we validate and correlate the OCT results with scanning electron microscopy (SEM) and XPS, proving the accuracy and effectiveness of the OCT characterization method. We reveal the interfacial phenomena and challenges in SSBs and demonstrate the feasibility and advantages of OCT as a powerful tool for in situ and operando imaging of battery interfaces. This study provides new insights into the mechanisms and factors that affect SSB performance, safety, and lifetime, and suggests possible solutions for improvement and application in the field of applied energy.

Super-resolution structured illumination microscopy (SR-SIM) is one of the important techniques that are most suitable for live-cell imaging. The reconstructed SR-SIM images are noisy once the raw images are recorded with low-light exposure. Here, we propose a new network (entitled the ND-SIM network) to denoise the SR images reconstructed using frequency-domain algorithms (FDAs). We demonstrate that ND-SIM can yield artifact-free SR images using raw images with an average photon count down to 20 per pixel while achieving comparable resolution to the ground truth (GT) obtained with high-light exposure. We can envisage that the ND-SIM will be widely applied for the long-term, super-resolution live-cell imaging of various bioprocesses in the future.