Results 141 to 150 of about 7,485,527 (252)
Binder‐free laser powder bed fusion of 8YSZ with a femtosecond laser is used to map process windows linking scan strategy, heat accumulation, and grain growth. Time‐resolved thermography and simulations reveal thermal regimes that enable continuous, vitrified, and fine‐grained 8YSZ surface layers without absorptive additives and demonstrate ...
Markus Kühn +5 more
wiley +1 more source
Annotated dataset for surface defect detection on ceramic substrates in manufacturing. [PDF]
Liang Y, Yang C, Liu C, Li W, Xie Z.
europepmc +1 more source
CT‐based finite element simulations combined with in situ X‐ray computed tomography are used to analyze insert pull‐out in nickel‐coated polymer foams. Despite variations in material parameters, deformation consistently concentrates within a narrow annular region around the insert.
Yannik Bautz +4 more
wiley +1 more source
EMamba: A MoE-enhanced state space network for robust steel surface defect detection. [PDF]
Yang H, Wang P, Liu Y.
europepmc +1 more source
Fabrication Routes for Ionic Conducting Fiber Strain Sensors
Ionic conducting fiber strain sensors (ICFSs) offer compliant, textile‐integrable sensing. Thus far, the commercialization of ICFSs has been constrained by fiber fabrication routes. This review provides a fabrication‐centric analysis of ICFSs correlating processing strategies with material properties and scalability.
Leo John Kershaw +3 more
wiley +1 more source
Edge-Enhance YOLO for Steel Surface Defect Detection. [PDF]
Li R, Lin M.
europepmc +1 more source
This study examines Invar composites reinforced with titanium carbide (TiC) and titanium nitride (TiN) using laser powder bed fusion (LPBF). It presents the influence of reinforcements on microstructure, tensile properties, and thermal expansion. Results show that TiC effectively strengthens Invar while maintaining low thermal expansion, whereas TiN ...
Ayodeji Nathaniel Oyedeji +3 more
wiley +1 more source
CCP-YOLO: An Improved YOLOv11n Algorithm for Steel Surface Defect Detection. [PDF]
Xiao L, Li P, Wang C, Zheng H, Xu Y.
europepmc +1 more source
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
A prototype-aligned multi-scale attention network for few-shot industrial surface defect detection. [PDF]
Huang R, Zhao L.
europepmc +1 more source

