Results 171 to 180 of about 2,435,277 (388)
Advanced Engineering Materials, Volume 27, Issue 14, July 2025.Developing process parameters for the laser‐based Powder Bed Fusion of metals can be a tedious task. Based on melt pool depth, the process parameters are transferable to different laser scan speeds. For this, understanding the melt pool scaling behavior is essential, particularly for materials with high thermal diffusivity, as a change in scaling ...
Markus Döring +2 more
wiley +1 more source
Electrochemical plating of Sn – Ag alloy applicable as a solder
Журнал Белорусского государственного университета: Химия, 2018 The additions of hydroquinone, 1,4-butandiol and citrate ions to the known strongly acidic sulfate-thiourea solution for electrochemical deposition of Sn – Ag low-melting alloy are proposed, which provide to obtain the alloys of composition near to the ...
Olga N. Vrublevskaya +5 more
doaj
Carbothermal shock synthesis of high-entropy-alloy nanoparticles
Science, 2018 Yonggang Yao +15 more
semanticscholar +1 more source
Advanced Engineering Materials, EarlyView.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
White-metal bearing alloys: mechanical properties at different temperatures and service tests
, 1933 H.K. Herschman, John L. Basil
openalex +1 more source
Advanced Engineering Materials, Volume 27, Issue 14, July 2025.This perspective article explores an innovative powder metallurgical approach to producing high‐nitrogen steels by utilizing a mixture of stainless steel and Si3N4. This mixture undergoes hot isostatic pressing followed by direct quenching. The article also examines adapting this method to laser powder bed fusion (PBF‐LB/M) to overcome nitrogen ...
Louis Becker +5 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.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