Results 271 to 280 of about 997,096 (396)
Hydrostatic bearings excel in high‐precision applications, but their performance hinges on a continuous external supply. This study evaluates various material combinations for sliding surfaces to mitigate damage during supply failures or misalignment and to discover the most effective materials identified for enhancing the reliability and efficiency of
Michal Michalec+6 more
wiley +1 more source
Effect of Oxidation and Silane Modifications Applied to the Bonded Material and Fibers in Carbon-Fiber-Reinforced Composite Adhesive Joints. [PDF]
Akpinar IA, Koçyiğit ÖF, Atasoy S.
europepmc +1 more source
Adhesive Interface of Adhesive Products
Yutaka Tosaki, Tadatoshi Nakanishi
openaire +3 more sources
A Different Perspective on the Solid Lubrication Performance of Black Phosphorous: Friend or Foe?
Researchers investigate black phosphorous (BP) as a standalone solid lubricant coating through ball‐on‐disc linear‐reciprocating sliding experiments in dry conditions. Testing on different metals shows BP doesn't universally reduce friction and wear. However, it achieves 33% friction reduction on rougher iron surfaces and 23% wear reduction on aluminum.
Matteo Vezzelli+5 more
wiley +1 more source
Effects of Aging on Mode I Fatigue Crack Growth Characterization of Double Cantilever Beam Specimens with Thick Adhesive Bondline for Marine Applications. [PDF]
Iyer Kumar R, De Waele W.
europepmc +1 more source
Hybrid materials enable high‐performance components but are challenging to process. This study explores an inductive heating concept with spray cooling for steel–aluminum specimens in a two‐step process including friction welding and cup backward extrusion.
Armin Piwek+7 more
wiley +1 more source
Synthesis, Characterization, and Adhesion on Galvanized Steel of Original Thermoset Adhesive Films Based on Aza-Michael Addition Reaction. [PDF]
Cavodeau F+3 more
europepmc +1 more source
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi+4 more
wiley +1 more source