Chalcogenide glasses have the advantages of a wide transparency window (over 20 μm) and high optical nonlinearity (up to a thousand times greater than that of silica glasses), making them good candidates for mid-infrared supercontinuum generation. In this review, we describe both the history and recent developments in mid-infrared supercontinuum generation from chalcogenide fibers according to three kinds of fiber structures: step-index, microstructured and tapered fibers. We also review the coherence properties of mid-infrared supercontinuum generation and all-fiber supercontinuum sources based on chalcogenide fibers.

We reported a highly coherent broadband supercontinuum (SC) generation in As-S chalcogenide tapered fibers pumped at 3.75 μm. The fiber preforms based on As-S glasses with a core/cladding diameter ratio of 1:25 were fabricated via isolated stacked extrusion. The waist diameters of tapered fibers can be changed by controlling the parameter of homemade tapering platform to realize all-normal dispersion (ANDi) characteristic. A broadband SC generation spanning from 1.5 to 8.3 μm was obtained in a 15-cm-long tapered fiber with waist core diameter of 4.8 μm. And high coherence property of the generated SC spectrum was investigated and verified by the simulation. The effect of different waist core diameters on SC spectra coherence properties was also investigated by numerical simulation.

Polymer fibers are considered ideal transmission media for all-optical networks, but their high intrinsic loss significantly limits their practical use. Quantum dot-doped polymer fiber amplifiers are emerging as a promising solution to this issue and are becoming a significant focus of research in both academia and industry. Based on the properties of CdSe/ZnS quantum dots and PMMA material, this study experimentally explores three fabrication methods for CdSe/ZnS quantum dots-doped PMMA fibers: hollow fiber filling, melt-drawing, and melt extrusion. The advantages and disadvantages of each method and key issues in fiber fabrication are analyzed. Utilizing the CdSe/ZnS quantum dots-doped PMMA fibers that were fabricated, we theoretically analyzed the key factors affecting gain performance, including fiber length, quantum dots doping concentration, and signal light intensity. Under the conditions of 1.5 W power and 445 nm laser pumping, a maximum on-off gain of 16.2 dB was experimentally achieved at 635 nm. Additionally, using a white light LED as the signal source, a broadband on-off gain with a bandwidth exceeding 70 nm and a maximum gain of 12.4 dB was observed in the 580–650 nm range. This research will contribute to the development of quantum dots-doped fiber devices and broadband optical communication technology, providing more efficient solutions for future optical communication networks.

The emission features of Cdse/ZnS quantum dots doped step-index polymer optical fibers are computationally analyzed in this paper. Spontaneous emission and amplified spontaneous emission were calculated by a theoretical model based on the rate equations in terms of time, fiber length, and wavelength. All the calculated parameters are derived from experiments. Through the comparative analysis of the calculated and experimental results of spontaneous emission, we found that the pump power and overlap between the emission and absorption cross-sections may be the two main reasons for the red shift of the output spectra. When the pump power exceeds the threshold of amplified spontaneous emission, the width of the output spectra will rapidly decrease, the output wavelength will fall back toward the maximum emission cross-section, and the final output wavelength will still be affected by the doping concentration and pump power, while amplified spontaneous emission will not be generated when the total number of doped quantum dots is less than 1.27 × 10¹².

We fabricated a core-cladding Ge–Sb–Se glass fiber with a Ge_12.5Sb₁₅Se_72.5 core and Ge₁₅Sb₁₀Se₇₅ cladding, achieved a supercontinuum spectrum spanning from 2 μm to 9 μm by pumping the Ge–Sb–Se fiber with a core diameter of 11 μm using a femtosecond laser pump at 3.8 μm, and numerically simulated the supercontinuum generation using the generalized nonlinear Schrödinger equation. In particular, we investigate the effect of the different Raman response functions that were calculated using the traditional single Lorentzian model and a multiple vibrational mode model on the evolution of the supercontinuum by comparing the supercontinua obtained from simulation and experimental results. We demonstrate that the Raman response function generated by the multiple vibrational mode model captures the actual response behavior of the material, and the supercontinuum generated using this model has more accuracy. To the best of our knowledge, this is the first reported study on supercontinuum generation in Ge–Sb–Se fiber utilizing a Raman response function calculated using the multiple vibrational mode model. This significant advancement enables more accurate simulation of supercontinuum generation in fibers with a multi-peaked structured Raman gain spectrum and holds great potential for optimizing the performance of various mid-infrared supercontinuum sources.

In this study, we focus on the relevance of remaining life prediction of randomly degraded equipment in the context of big data monitoring and the core issue of quantifying uncertainty in remaining life prediction. We analyze the limitations and common problems of current research. To address the limitations and common problems, a solution for predicting the remaining life of randomly degraded devices with multisource sensing monitoring in the context of big data is proposed, and the feasibility and effectiveness of the idea are verified using battery data. Finally, multiple machine learning methods, such as support vector machines, random forests, recurrent neural networks, and convolutional neural networks, are combined to predict the remaining life of batteries, and these four machine learning methods perform well in the work of battery remaining life prediction and solve the key scientific problems.