Results 211 to 220 of about 5,032,170 (262)

Controlling Grain Growth in Powder Bed Fusion of Yttria‐Stabilized Zirconia Using Femtosecond Lasers: Challenges and Methodological Insights

Advanced Engineering Materials, EarlyView.
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, Sarah Kaden, Andrea Barz, Daniel Störzner, Jens Bliedtner, Andrés Fabián Lasagni   +5 more
wiley   +1 more source

Graph Topology-Guided Multi-Task Learning for Fall Detection. [PDF]

Sensors (Basel)
Zhao X, Jin P.
europepmc   +1 more source

Simulation‐Based Analysis of Insert Pull‐Out in Nickel‐Polyurethane Hybrid Foams Using CT‐Derived Geometries

Advanced Engineering Materials, EarlyView.
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, Jonas Fell, Hendrik Jost, Stefan Diebels, Hans‐Georg Herrmann   +4 more
wiley   +1 more source

ContiTE: continuous manifold MoE for few-shot cross-tissue mRNA translation efficiency prediction. [PDF]

Brief Bioinform
Wei Y, Zhang Q, Huo S, Zhou X.
europepmc   +1 more source

Influence of TiC and TiN Ceramic Reinforcements on the Microstructure, Thermal Expansion Behavior, and Tensile Properties of Invar 36 Manufactured by Laser Powder Bed Fusion

Advanced Engineering Materials, EarlyView.
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, Natasha Sacks, Johannes Pötschke, Björn Matthey   +3 more
wiley   +1 more source

Multi-Dimensional Behavioral Signature Analysis for Video Bullet Comment Steganography Detection. [PDF]

Entropy (Basel)
Liu Y, Zhao H.
europepmc   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
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, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Fault Diagnosis of Ship Chilled Water Units Based on a Hybrid Attention Domain-Adaptive Network. [PDF]

Entropy (Basel)
Feng Q, Li Y, Liu Y, Liang X, Liu M, Qu D, Cen Y.   +6 more
europepmc   +1 more source

Rapidly Solidified High‐Strength Invar 36 Prepared by Planar‐Flow Melt Spinning

Advanced Engineering Materials, EarlyView.
The Invar 36 alloy was rapidly solidified using the planar‐flow melt‐spinning technique. Ribbon samples with thicknesses ranging from 20 to 160 mm were produced. As the grain size of the ribbon decreased to sub‐micron levels, the hardness increased by more than 2 times.
Bekir Akgül, Mehmet Kul
wiley   +1 more source