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Fiber-reinforced resin matrix composites are generally composed of fibers and matrix with significantly different properties, which are non-uniform and anisotropic in nature. Macro-failure criteria generally view composite plies as a uniform whole and do not accurately reflect fiber- and matrix-scale failures. In this study, the interface phase effect between fiber and matrix has been introduced into the frame of trans-scale analysis to better model the failure process, and the equivalent mechanical property characterization model of the interface phase has also been established. Combined with the macro-micro-strain transfer method, the trans-scale correlation of the mechanical response of the composite laminates between the macro scale and the fiber, matrix and interface micro scale has been achieved. Based on the micro-scale failure criterion and the stiffness reduction strategy, the trans-scale failure analysis method of composite materials incorporating the interface phase effect has been developed, which can simultaneously predict the failure modes of the matrix, fiber and interface phase. A numerical implementation of the developed trans-scale failure analysis method considering interface phase was carried out using the Python and Abaqus 2020 joint simulation technique. Case studies were carried out for three material systems, and the prediction data of the developed trans-scale failure analysis methodology incorporating interface phase effects for composite materials, the prediction data of the Linde failure criterion and the experimental data were compared. The comparison with experimental data confirms that this method has good prediction accuracy, and compared with the Linde and Hashin failure methods, only it can predict the failure mode of the fiber-matrix interface. The case analysis shows that its prediction accuracy has been improved by about 2-3%.
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http://dx.doi.org/10.3390/ma18153667 | DOI Listing |
Biomed Phys Eng Express
September 2025
electrical engineering department, Indian Institute of Technology Roorkee, Research wing, electrical department, Roorkee, uttrakhand, 247664, INDIA.
Imagined speech classification involves decoding brain signals to recognize verbalized thoughts or intentions without actual speech production. This technology has significant implications for individuals with speech impairments, offering a means to communicate through neural signals. The prime objective of this work is to propose an innovative machine learning (ML) based classification methodology that combines electroencephalogram (EEG) data augmentation using a sliding window technique with statistical feature extraction from the amplitude and phase spectrum of frequency domain EEG segments.
View Article and Find Full Text PDFJ Colloid Interface Sci
September 2025
Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Province, College of Engineering, Zhejiang Normal University, Jinhua 321004, China. Electronic address:
Developing high-performance wearable flexible sensors that can adapt well to complex environments has become a hotspot. Herein, a polyvinyl alcohol based composite hydrogel sensor with high mechanical strength, desirable frost/swelling resistance, and highly sensitive sensing performance was proposed by a multi-component collaborative design strategy. Meanwhile, an intelligent gesture recognition system was established by combining machine learning algorithm.
View Article and Find Full Text PDFJ Colloid Interface Sci
August 2025
School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China. Electronic address:
Prussian blue analogues (PBAs) have emerged as promising cathode materials for sodium-ion batteries (SIBs) due to their low cost, simple preparation, and high theoretical specific capacity. The integration of high-entropy concepts with framework-structured PBAs has pioneered a new pathway for performance optimization in SIBs cathodes. However, most scholars have only studied the five elements constituting high entropy as a whole, while challenges such as the role of each element and optimization of the proportions among constituent elements remain unresolved.
View Article and Find Full Text PDFJ Med Internet Res
September 2025
Department of Community Medicine, Faculty of Health, UiT The Arctic University of Norway, Tromsø, Norway.
Background: The ability to access and evaluate online health information is essential for young adults to manage their physical and mental well-being. With the growing integration of the internet, mobile technology, and social media, young adults (aged 18-30 years) are increasingly turning to digital platforms for health-related content. Despite this trend, there remains a lack of systematic insights into their specific behaviors, preferences, and needs when seeking health information online.
View Article and Find Full Text PDFAnal Chem
September 2025
Jiaxing Key Laboratory of Molecular Recognition and Sensing, College of Biological and Chemical Engineering, Jiaxing University, Jiaxing 314001, China.
Despite the promise of electrochemical biosensors in amplified nucleic acid diagnostics, existing high-sensitivity platforms often rely on a multilayer surface assembly and cascade amplification confined to the electrode interface. These stepwise strategies suffer from inefficient enzyme activity, poor mass transport, and inconsistent probe orientation, which compromise the amplification efficiency, reproducibility, and practical applicability. To address these limitations, we report a programmable dual-phase electrochemical biosensing system that decouples amplification from signal transduction.
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