A5013816173- High Temperature Alloys and Creep
- Advanced materials and composites
- Metal Alloys Wear and Properties
- High-Temperature Coating Behaviors
- Microstructure and Mechanical Properties of Steels
- Intermetallics and Advanced Alloy Properties
- High Entropy Alloys Studies
- Metallurgy and Material Forming
- Hydrogen embrittlement and corrosion behaviors in metals
- Advanced Materials Characterization Techniques
- Aluminum Alloys Composites Properties
- Fatigue and fracture mechanics
- Advanced ceramic materials synthesis
- Metal and Thin Film Mechanics
- Aluminum Alloy Microstructure Properties
- Metallurgical Processes and Thermodynamics
- Machine Learning in Materials Science
- MXene and MAX Phase Materials
- Welding Techniques and Residual Stresses
- Material Properties and Failure Mechanisms
- Additive Manufacturing Materials and Processes
- Non-Destructive Testing Techniques
- Metallurgical and Alloy Processes
- Nuclear Materials and Properties
- Corrosion Behavior and Inhibition
National Energy Technology Laboratory
2015-2024
United States Air Force Research Laboratory
2018
United States Department of Energy
1999-2018
Taiyuan University of Technology
2018
Albany Research Institute
1997-2002
Office of Fossil Energy
2001-2002
American Ceramic Society
1996
United States Department of the Interior
1994
United States Bureau of Reclamation
1993
Oak Ridge National Laboratory
1993
High-entropy alloys (HEAs) are a new class of solid-solution that have attracted worldwide attention for their outstanding properties. Owing to the demand from transportation and defense industries, light-weight HEAs also garnered widespread interest scientists use as potential structural materials. Great efforts been made study phase-formation rules accelerate refine discovery process. In this paper, many proposed assessed, based on series known newly-designed HEAs. The results indicate...
Abstract Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed still exhibit low strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method design light, strong, low-cost high-entropy alloys for elevated-temperature applications. Through screening, precipitation-strengthened lightweight are...
Abstract The empirical rules for the prediction of solid solution formation proposed so far in literature usually have very compromised predictability. Some with seemingly good predictability were, however, tested using small data sets. Based on an unprecedented large dataset containing 1252 multicomponent alloys, machine-learning methods showed that solutions can be accurately predicted (93%). results help identify most important features, such as molar volume, bulk modulus, and melting...
Guided by CALPHAD (Calculation of Phase Diagrams) modeling, the refractory medium-entropy alloy MoNbTaV was synthesized vacuum arc melting under a high-purity argon atmosphere. A body-centered cubic solid solution phase experimentally confirmed in as-cast ingot using X-ray diffraction and scanning electron microscopy. The measured lattice parameter (3.208 Å) obeys rule mixtures (ROM), but Vickers microhardness (4.95 GPa) yield strength (1.5 are about 4.5 4.6 times those estimated from ROM,...
This paper reviews the status of technology in design and manufacture new wrought polycrystalline Ni-base superalloys for critical engineering applications. There is a strong motivation to develop alloys that are capable operating at higher temperatures realize improvements thermal efficiency, which necessary achieve environmental targets reduced emissions harmful green-house gases. From aerospace sector, development powder metallurgy ingot discussed disk rotor static New compositions...
The corrosion behavior of high‐entropy alloys (HEAs) CoCrFeNi 2 and Mo 0.25 was investigated in 3.5 wt. percent sodium chloride (NaCl) at 25°C by electrochemical methods. Their parameters were compared to those HASTELLOY® C‐276 (UNS N10276) stainless steel 316L 31600) assess the suitability HEAs for potential industrial applications NaCl simulating seawater type environments. rates calculated using current determined from experiments each alloys. In addition, potentiodynamic polarization...
Metallurgy and material design have thousands of years' history played a critical role in the civilization process humankind. The traditional trial-and-error method has been unprecedentedly challenged modern era when number components phases novel alloys keeps increasing, with high-entropy as representative. New opportunities emerge for alloy artificial intelligence era. Here, successful machine-learning (ML) developed to identify microstructure images eye-challenging morphology martensitic...
The formation of octonary DyErGdHoLuScTbY and senary DyGdHoLaTbY ErGdHoLaTbY high-entropy alloys (HEAs) with the hexagonal close-packed (HCP) structure was reported in this study. Experiments using scanning electron microscopy x-ray diffraction confirmed single HCP solid solution as-cast state for these three HEAs if presence minor rare-earth oxides due to contamination from processing is ignored. measured compressive yield stress values at room temperature are 245, 205, 360 MPa ErGdHoLaTbY,...
High-temperature alloy design requires a concurrent consideration of multiple mechanisms at different length scales. We propose workflow that couples highly relevant physics into machine learning (ML) to predict properties complex high-temperature alloys with an example the 9-12 wt.% Cr steels yield strength. have incorporated synthetic features capture microstructure and phase transformations dataset. Identified high impact affect strength 9Cr from correlation analysis agree well generally...
Abstract The Larson–Miller parameter (LMP) offers an efficient and fast scheme to estimate the creep rupture life of alloy materials for high-temperature applications; however, poor generalizability dependence on constant C often result in sub-optimal performance. In this work, we show that direct parameterization without intermediate LMP parameterization, using a gradient boosting algorithm, can be used train ML models very accurate prediction variety alloys (Pearson correlation coefficient...