Results 111 to 120 of about 413,989 (373)
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source
3D‐Printed Architected Material for the Generation of Foam‐Based Protective Equipment
This study investigates 3D‐printed architected structures as alternatives to traditional foams in protective gear. It focuses on customizing impact strength and damping through design and manufacturing integration. Testing shows these structures outperform conventional foams, offering enhanced customizability, lower weight, and tunable performance ...
Ali Zolfagharian +5 more
wiley +1 more source
Exploration of the High Entropy Alloy Space as a Constraint Satisfaction Problem [PDF]
High Entropy Alloys (HEAs), Multi-principal Component Alloys (MCA), or Compositionally Complex Alloys (CCAs) are alloys that contain multiple principal alloying elements. While many HEAs have been shown to have unique properties, their discovery has been
Abu-Odeh, Anas +7 more
core +1 more source
In this research, ZrC coatings are evaluated against various counterprobes at the microscale using novel super‐stiff atomic force microscopy cantilevers. The chemical composition of the coating is shown to be an important factor influencing coating hardness and Young's modulus, while surface roughness, counterprobe hardness, and surface energy are the ...
Piotr Jenczyk +4 more
wiley +1 more source
High-entropy alloys have attracted widespread attention from researchers worldwide due to their unique microstructure and outstanding mechanical properties, making them a prominent focus in the field of metallurgy.
Fachang Zhao +4 more
doaj +1 more source
Discovery of high-entropy ceramics via machine learning [PDF]
Although high-entropy materials are attracting considerable interest due to a combination of useful properties and promising applications, predicting their formation remains a hindrance for rational discovery of new systems.
Curtarolo, Stefano +9 more
core +1 more source
Ni‐base superalloys produced using additive manufacturing (AM) have a different response to heat treatments when compared to their conventional counterparts. Due to such unpredictability, various alloys with industrial interest are currently overlooked in most prior AM research.
Guilherme Maziero Volpato +6 more
wiley +1 more source
Current status and prospects in machine learning-driven design for refractory high-entropy alloys
Due to excellent comprehensive properties such as high strength, high hardness, and excellent high-temperature oxidation resistance, the refractory high-entropy alloys have broad application prospects and research value in the fields of aerospace and ...
GAO Tianchuang +3 more
doaj +1 more source
This study presents a 3D representative volume element‐based simulation approach to predict mesoscopic residual stress and strain fields in silicon solid solution‐strengthened ductile cast iron. By modeling phase transformation kinetics with an enhanced Johnson–Mehl–Avrami–Kolmogorov model, the effects of varying cooling rates on residual stresses are ...
Lutz Horbach +6 more
wiley +1 more source
Recent Advances of High Entropy Alloys: High Entropy Superalloys
This study reviews the recent technological advancements in manufacturing technique; laser surface modification and material; High Entropy Superalloys. High Entropy Superalloys are current potential alternatives to nickel superalloys for gas turbine applications and these superalloys are presented as the most promising material for gas turbine engine ...
Sisa Pityana +8 more
openaire +4 more sources

