Results 41 to 50 of about 9,420 (187)
Application of Machine Learning in Heat Treatment Process Design of Carburized Steel
Materials Genome Engineering Advances, EarlyView.To accelerate heat treatment design, we constructed a closed‐loop machine learning strategy involving multi‐source datasets and feature screening. The optimized model accurately predicts hardness and friction coefficients, successfully guiding the process optimization for two typical carburized steels with high experimental consistency.
Di Jiang +5 more
wiley +1 more source
Materials Genome Engineering Advances, EarlyView.This research proposes a physics‐informed generative machine learning framework to design SHA800, a crack‐free γ′‐strengthened nickel‐based superalloy for laser powder bed fusion, achieving a 43% γ′ volume fraction and 587 HV0.2 hardness. ABSTRACT Fabricating γ′‐strengthened nickel‐based superalloys via laser powder bed fusion (LPBF) faces significant ...
Kai Guo +11 more
wiley +1 more source
The Structure and Stability of High Temperature Intermetallic Phases for Application within Coating Systems [PDF]
, 2009 The reduction of noise and emissions is becoming increasingly important in civil aircraft jet engines as well as requirements for reduced fuel consumption and improved efficiency.
Roberts, Tracey
core
Small Methods, EarlyView.Differential phase contrast (DPC) imaging in STEM is demonstrated as a rapid, versatile segmentation tool for advanced aluminum alloys. Decomposition of false‐color DPC micrographs resolves nanoclusters, precipitate variants, dislocation strain fields, nanostructures, and grain boundaries ‐ all within a single and fast acquisition.
Matheus A. Tunes +7 more
wiley +1 more source
Mechanical Properties of Graphene Reinforced Nickel-based P/M Superalloy
, 2017 The graphene nanosheets were dispersed in the superalloy powder by using the wet mixing method, and then the nickel based FGH96 P/M superalloy was prepared with hot isostatic pressing(HIP)+hot extrusion(HEX)+hot isothermal forging(HIF)+heat treating(HT ...
YANG Jie +3 more
core +1 more source
Micro‐Mechanism Informed Neural Networks for Process‐Property Prediction in Laser Powder Bed Fusion
Artificial Intelligence for Engineering, EarlyView.Hard physics embedding, where neural networks learn residuals relative to analytical baselines, substantially outperforms soft loss‐function constraints for extrapolation in LPBF process–property prediction. Physics integration architecture determines generalization capability more than constraint quantity.
Yo‐Lun Yang
wiley +1 more source
Advanced Engineering Materials, Volume 28, Issue 12, 17 June 2026.This study investigates the effects of milling parameters, including rotational speed, milling duration, and ball‐to‐powder ratio, on TiAl particle size and morphology in an XHV‐equivalent atmosphere. The creation of oxide‐free surfaces enhances the mechanical properties of green bodies.
Jytte Möckelmann +4 more
wiley +1 more source
Development of Coatings for Gas Turbines Burning Biomass and Waste-Fuels [PDF]
, 2009 Worldwide, carbon dioxide emission reductions are in progress following the Kyoto Protocol implementation programme to mitigate climate change. More stringent reductions are expected to follow the present programme which ends in 2012.
Bradshaw, A.
core
Advanced Engineering Materials, Volume 28, Issue 11, 3 June 2026.Nickel‐based alloys are widely used in high‐temperature applications due to their excellent mechanical strength and oxidation resistance. However, properties such as high‐temperature strength and pronounced work‐hardening make them difficult to machine.
Soheil Rooein +2 more
wiley +1 more source
, 2010 Powder metallurgy (PM) nickel-based superalloy is regarded as one of the most important aerospace industry materials. A series of turning tests in a wide range of speeds with different inserts were carried out to select the proper tool material.
Xing Ai, Zhan Qiang Liu, Yang Qiao
core +1 more source