Preparation of Fibrous Three-Dimensional Porous Materials and Their Research Progress in the Field of Stealth Protection.

Intelligent and diversified development of modern detection technology greatly affects the battlefield survivability of military targets, especially infrared, acoustic wave, and radar detection expose targets by capturing their unavoidable infrared radiation, acoustic wave, and electromagnetic wave information, greatly affecting their battlefield survival and penetration capabilities. Therefore, there is an urgent need to develop stealth-protective materials that can suppress infrared radiation, reduce acoustic characteristics, and weaken electromagnetic signals. Fibrous three-dimensional porous materials, with their high porosity, excellent structural adjustability, and superior mechanical properties, possess strong potential for development in the field of stealth protection. This article introduced and reviewed the characteristics and development process of fibrous three-dimensional porous materials at both the micrometer and nanometer scales. Then, the process and characteristics of preparing fibrous three-dimensional porous materials through vacuum forming, gel solidification, freeze-casting, and impregnation stacking methods were analyzed and discussed. Meanwhile, their current application status in infrared, acoustic wave, and radar stealth fields was summarized and their existing problems and development trends in these areas from the perspectives of preparation processes and applicability were analyzed. Finally, several prospects for the current challenges faced by fibrous three-dimensional porous materials were proposed as follows: functionally modifying fibers to enhance their applicability through self-cross-linking; establishing theoretical models for the transmission of thermal energy, acoustic waves, and electromagnetic waves within fibrous porous materials; constructing fibrous porous materials resistant to impact, shear, and fracture to meet the needs of practical applications; developing multifunctional stealth fibrous porous materials to confer full-spectrum broadband stealth capability; and exploring the relationship between material size and mechanical properties as a basis for preparing large-scale samples that meet the application's requirement. This review is very timely and aims to focus researchers' attention on the importance and research progress of fibrous porous materials in the field of stealth protection, so as to solve the problems and challenges of fibrous porous materials in the field of stealth protection and to promote the further innovation of fibrous porous materials in terms of structure and function.

Synovial fluid research based on SERS and SERRS for enhanced detection of biomarkers in staged osteoarthritis.

Surface-enhanced (resonance) Raman scattering (SER(R)S) can extremely enhance Raman intensity of samples, which is helpful for detecting synovial fluid (SF) that does not show Raman activity under normal conditions. In this study, SER(R)S spectra of SF from three different osteoarthritis (OA) stages were collected and analyzed for OA progress, finding that the content of collagen increased throughout the disease, while non-collagen proteins and polysaccharides decreased sharply at advanced OA stage accompanied by the increase of phospholipid. The spectral features and differences were enhanced by salting-out and centrifugation. Much more information on biomolecules at different OA stages was disclosed by using SERRS for the first time, these main trace components (ß-carotene, collagen, hyaluronic acid, nucleotide, and phospholipid) can be used as potential biomarkers. It indicates that SERRS has a more comprehensive ability to assist SERS in seeking micro(trace) biomolecules as biomarkers and facilitating accurate and efficient diagnosis and mechanism research of OA.

An improved Autogram and MOMEDA method to detect weak compound fault in rolling bearings.

When weak compound fault occurs in rolling bearing, the faint fault features suffer from serious noise interference, and different type faults are coupled together, making it a great challenge to separate the fault features. To solve the problems, a novel weak compound fault diagnosis method for rolling bearing based on improved Autogram and multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) is proposed. Firstly, the kurtosis index in Autogram is modified with multi-scale permutation entropy, and improved Autogram finds the optimal resonance frequency band to preliminarily denoise the weak compound fault signal. Then, MOMEDA is performed to deconvolute the denoised signal to decouple the features of compound fault. Finally, square envelope analysis is applied on the separated deconvoluted signals to identify different type faults according to the fault characteristic frequencies in the spectrums. The proposed method is performed to analyze the simulated signal and experimental datasets of different types of rolling bearing weak compound faults. The results indicate that the proposed method can accurately diagnose the weak compound faults, and comparison with the analysis results of parameter-adaptive variational mode decomposition algorithm verifies its effectiveness and superiority.