Ti/TiBCN composite coatings were prepared on a 7075 aluminum alloy surface by laser cladding. The relation between the main processing parameters (i.e., laser power, scanning speed, and powder feeding rate) and the geometrical characteristics (i.e., height, width, penetration depth, dilution and wetting angle) of single clad tracks is studied by linear regression analysis. The microstructure, micro-hardness and electrochemical corrosion were investigated by scanning electron microscopy, a Vickers micro-hardness machine, and a standard three-electrode cell, respectively. The results showed that all geometrical track characteristics are observed with high values of the correlation coefficient (R > 0.95). In addition, the average hardness value (750 HV) was obtained of the Ti/TiBCN composite coating, and polarization curves indicated that the composite coatings were harder to corrode than the substrate.
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http://dx.doi.org/10.3390/ma11091551 | DOI Listing |
Phys Chem Chem Phys
January 2025
Department of Energy and Refrigerating Air-Conditioning Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan.
This study employs first-principles calculations to investigate the geometric and electronic properties of hydrogenated silicon nanotubes (SiNTs). SiNTs, particularly in their gear-like configuration, demonstrate unique semiconducting behavior; however, their relatively small intrinsic band gaps limit their applicability in fields requiring moderate band gaps. Significant changes in electronic properties are observed by hydrogenating SiNTs at various levels of adsorption-either full or partial-and different surface configurations (exterior, interior, or dual-sided).
View Article and Find Full Text PDFJ Neural Eng
January 2025
Center for Complex Systems and Brain Sciences, Universidad Nacional de San Martin Escuela de Ciencia Y Tecnologia, 25 de Mayo y Francia, San Martín, Buenos Aires, 1650, ARGENTINA.
Objective Magnetic resonance imaging (MRI), functional MRI (fMRI) and other neuroimaging techniques are routinely used in medical diagnosis, cognitive neuroscience or recently in brain decoding. They produce three- or four-dimensional scans reflecting the geometry of brain tissue or activity, which is highly correlated temporally and spatially. While there exist numerous theoretically guided methods for analyzing correlations in one-dimensional data, they often cannot be readily generalized to the multidimensional geometrically embedded setting.
View Article and Find Full Text PDFBMC Med Imaging
January 2025
Department of Information, Third Affiliated Hospital of Naval Medical University, No. 225 Changhai Road, Yangpu District, 200438, Shanghai, China.
Purpose: To develop an end-to-end convolutional neural network model for analyzing hematoxylin and eosin(H&E)-stained histological images, enhancing the performance and efficiency of nuclear segmentation and classification within the digital pathology workflow.
Methods: We propose a dual-mechanism feature pyramid fusion technique that integrates nuclear segmentation and classification tasks to construct the HistoNeXt network model. HistoNeXt utilizes an encoder-decoder architecture, where the encoder, based on the advanced ConvNeXt convolutional framework, efficiently and accurately extracts multi-level abstract features from tissue images.
Polymers (Basel)
December 2024
Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Universitaetsstrasse 9, 95447 Bayreuth, Germany.
High Speed Sintering (HSS) is an additive manufacturing process with great potential to produce complex, high-quality polymer parts on an industrial scale. However, little information is currently available on the characteristics of the powder materials used and the part properties that can be achieved. This is also the case for the standard material polyamide 12 (PA 12) and the first commercially available HSS machine, the VX200 HSS.
View Article and Find Full Text PDFMicromachines (Basel)
December 2024
Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control, School of Automation, Guangdong University of Technology, Guangzhou 510006, China.
Serpentine microstructures offer excellent physical properties, making them highly promising in applications in stretchable electronics and tissue engineering. However, existing fabrication methods, such as electrospinning and lithography, face significant challenges in producing microscale serpentine structures that are cost-effective, efficient, and controllable. These methods often struggle with achieving precise control over fiber morphology and scalability.
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