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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Composition design of high-entropy alloys with deep sets learning

High entropy alloys (HEAs) are an important material class in the development of next-generation structural materials, but the astronomically large composition space cannot be efficiently explored by experiments or first-principles calculations. Machine learning (ML) methods might address this challenge, but ML of HEAs has been hindered by the scarcity of HEA property data. In this work, the EMTO-CPA method was used to generate a large HEA dataset (spanning a composition space of 14 elements) containing 7086 cubic HEA structures with structural properties, 1911 of which have the complete elastic tensor calculated. The elastic property dataset was used to train a ML model with the Deep Sets architecture. The Deep Sets model has better predictive performance and generalizability compared to other ML models. Association rule mining was applied to the model predictions to describe the compositional dependence of HEA elastic properties and to demonstrate the potential for data-driven alloy design.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Guided Design of Alloys, Strengthened via Precipitation

Using theoretical and computational guidance, we are designing stronger middle and high-entropy alloys and superalloys for the airspace applications. We focus on improving mechanical properties of materials at cryogenic and elevated temperatures. Here we discuss basic science and fundamental theory that are being used for guided design of next-generation alloys. As examples, we consider the medium-entropy NiCoCr alloy and precipitated superalloys with a local phase transformation strengthening. This research is funded by NASA’s Aeronautics Research Mission Directorate (ARMD) via Transformational Tools and Technologies (TTT) Project.

Alloys↗
DOE OSTI2020

Design of a V–Ti–Ni alloy with superelastic nano-precipitates

Stress-induced martensitic transformations enable metastable alloys to exhibit enhanced strain hardening capacity, leading to improved formability and toughness. As is well-known from transformation-induced plasticity (TRIP) steels, however, the resulting martensite can limit ductility and fatigue life due to its intrinsic brittleness. In this work, we explore an alloy design strategy that utilizes stress-induced martensitic transformations but does not retain the martensite phase. This strategy is based on the introduction of superelastic nano-precipitates, which exhibit reverse transformation after initial stress-induced forward transformation. To this end, utilizing ab-initio simulations and thermodynamic calculations we designed and produced a V 45 Ti 30 Ni 25 (at%) alloy. In this alloy, TiNi is present as nano-precipitates uniformly distributed within a ductile V-rich base-centered cubic (bcc) β matrix, as well as being present as a larger matrix phase. We characterized the microstructure of the produced alloy using various scanning electron microscopy (SEM) and transmission electron microscopy (TEM) methods. Furthermore, the bulk mechanical properties of the alloy are demonstrated through tensile tests, and the reversible transformation in each of the TiNi morphologies were confirmed by in-situ TEM micro-pillar compression experiments, in-situ high-energy diffraction synchrotron cyclic tensile tests, indentation experiments, and differential scanning calorimetry experiments. The observed transformation pathways and variables impacting phase stability are critically discussed.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Design for Oxidation Resistance

Alloys intended for use in high-temperature environment rely on the formation of a continuous, compact, slow-growing oxide layer for oxidation and hot corrosion resistance. To be protective, this oxide layer must be chemically, thermodynamically stable. Successful alloy design for oxidative environment is best achieved by developing alloys that are capable of forming adherent scales of either alumina (Al2O3), chromia (Cr2O3), or silica (SiO2). In this article, emphasis has been placed on the issue related to high-temperature oxidation of superalloys used in gas turbine engine application. Despite the complexity of these alloys, optimal performance has been associated with protective alumina scale formation. As will be described below, both compositional makeup and protective coatings play key role in providing oxidation protection. Other high-temperature materials described include nickel and titanium aluminide intermetallics, refractory metal, and ceramics.

Smialek, James L.↗
DOE OSTI2024

Development of PWHT-Free, Reduced Activation Creep-Strength Enhanced Bainitic Ferritic Steel for Large-Scale Fusion Reactor Components

A compositional modification has been proposed to validate an alloy design which potentially eliminates the requirement of post-weld heat treatment (PWHT) while preserving the advantage of mechanical properties in a reduced activation bainitic ferritic steel based on Fe-3Cr-3W-0.2V- 0.1Ta-Mn-Si-C, in weight percent, developed at Oak Ridge National Laboratory in 2007. The alloy design includes reducing the hardness in the as-welded condition for improving toughness, while increasing the hardenability for preserving the high-temperature mechanical performance such as creep-rupture resistance in the original steel. To achieve such a design, a composition range with a reduced C content combining with an increased Mn content has been proposed and investigated. Newly proposed “modified” steel successfully achieved an improved impact toughness in the as- welded condition, while the creep-rupture performance across the weldments without PWHT demonstrated ~50% improvement of the creep strength compared to that of the original steel weldment after PWHT. The obtained results strongly support the validity of the proposed alloy design.

Yamamoto, Yukinori↗
DOE OSTI2020

Interactions and immobilization of lanthanides with dopants in uranium-based metallic fuels

In uranium-based fuels, production and migration of lanthanide fission products and subsequent chemical interactions with cladding constituents lead to fuel–cladding chemical interaction (FCCI), limiting fuel performance. In general, dopant addition to the fuel matrix to arrest lanthanides within the fuel by forming intermetallics is found to be effective in mitigating FCCI. Recently, we proposed ab-initio based alloy-design principles, which can be useful in identifying dopant(s) that can bind a lanthanide (Nd) inside the fuel matrix. Here, we demonstrate the robustness of such principles by performing a systematic study to choose dopants to form compounds with a range of experimentally-observed lanthanide fission products. Results reveal that for a given dopant, lanthanide Ce and La exhibit similar behavior in their compound-forming tendencies compared to Nd and Pr, which is linked to lanthanide intrinsic characteristics such as the electronic configurations. Our predicted lanthanide-dopant intermetallic formation is verified experimentally in selective cases. Finally, we showed alloy design principles that accurately identify previously known dopants like Pd, and also predict new dopants As and Se, that can be effective in binding all lanthanides within the uranium matrix. Altogether, this research helps to develop generic alloy-design principles for complex multi-component systems based on lanthanide and dopant intrinsic characteristics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Chemical trends favoring interstitial cluster formation in bcc high-entropy alloys from first-principles calculations

Achieving high strength and ductility is a common goal in structural alloy design. Body-centered cubic high-entropy alloys (HEAs) commonly highlight the conflict between these properties, with stronger alloys being brittle and vice versa. Recent reports suggest interstitial solutes can be used to overcome this trade-off, in some cases providing both strength and ductility enhancements. This effect has been correlated with interstitial cluster formation, although the conditions favoring their formation remain incompletely understood. Using first-principles calculations of solution energies and diffusivities, we provide insights into thermodynamic and kinetic factors favoring interstitial solute clusters. Among C, N and O solutes, O interstitials display most desirable diffusion kinetics. Further, the results highlight the importance of local composition fluctuations in the HEAs to enable the formation of clusters of appreciable size. The results are explained in terms of bonding and distortion trends across solutes and HEA compositions to provide guidelines for alloy design.

Borges, Pedro P P O↗
NASA NTRS2002

Experimental Verification of the Theoretical Prediction of the Phase Structure of a Ni-Al-Ti-Cr-Cu Alloy

The Bozzolo-Ferrante-Smith (BFS) method for alloys was applied to the study of NiAl-based materials to assess the effect of alloying additions on structure. Ternary, quaternary and even pentalloys based on NiAl with additions of Ti, Cr and Cu were studied and experimental verification of the theoretical predictions including the phase structure of a Ni-Al-Ti-Cr-Cu alloy is presented. Two approaches were used, Monte Carlo simulations to determine low energy structures, and analytical calculations of the energy of high symmetry configurations which give physical insight into preferred structures. The energetics for site occupancy in ternary and quaternary systems were calculated leading to an indirect determination of solubility limits at 0 K. Precipitate formation with information concerning structure and lattice parameter were also 'observed' computationally and the general characteristics of a Ni-Al-Ti-Cr-Cu alloy were correctly predicted. The results indicate that the BFS method for alloys can be a useful tool for alloy design and can be used to complement experimental alloy design programs.

Wilson, A.↗
DOE OSTI2022

Thermodynamics-guided alloy and process design for additive manufacturing

In conventional processing, metals go through multiple manufacturing steps including casting, plastic deformation, and heat treatment to achieve the desired property. In additive manufacturing (AM) the same target must be reached in one fabrication process, involving solidification and cyclic remelting. The thermodynamic and kinetic differences between the solid and liquid phases lead to constitutional undercooling, local variations in the solidification interval, and unexpected precipitation of secondary phases. These features may cause many undesired defects, one of which is the so-called hot cracking. The response of the thermodynamic and kinetic nature of these phenomena to high cooling rates provides access to the knowledge-based and tailored design of alloys for AM. Here, we illustrate such an approach by solving the hot cracking problem, using the commercially important IN738LC superalloy as a model material. The same approach could also be applied to adapt other hot-cracking susceptible alloy systems for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Computational Design of Alloys for Energy Technologies

Advanced materials that maintain their mechanical performance under elevated temperatures, corrosive environments, and a range of static and evolving stresses are needed to improve the efficiency and reduce the environmental impact of a wide spectrum of energy technologies. For instance, cost-efficient alloys that can withstand high temperatures (e.g., 700 °C) have a critical role in improving the efficiency and economics of power generation to support decarbonization of the energy sector; such is true of both the nuclear and fossil energy sectors. Considering both the threats of the energy crisis, namely soaring costs of greenhouse gas emission-producing energy and climate change, it is essential to increase the pace of material discovery and enable rapid paths for material qualification to advance clean energy technologies. Conventionally, alloy development has followed a slow Edisonian process that uses repeated cycles of making, characterizing, and modifying to arrive at optimum composition and processing conditions to achieve the desired component performance. This optimization is followed by the necessary stepwise materials qualification. Furthermore, the increasing adoption of sound data management and physics-informed machine learning represents the next step in the acceleration of materials design and development. In the integrated computational materials engineering (ICME) approach, computational modeling and simulation data from different length and time scales can be combined with complex microstructural details from multimodal experimental characterization and selective property testing to close the design loop for rapid alloy development.

Computational Design Of Materials↗
DOE OSTI2022

Assessment of Outliers in Alloy Datasets Using Unsupervised Techniques

We report advancements in data analytics techniques have enabled complex, disparate datasets to be leveraged for alloy design. Identifying outliers in a dataset can reduce noise, identify erroneous and/or anomalous records, prevent overfitting, and improve model assessment and optimization. In this work, two alloy datasets (9-12% Cr ferritic martensitic steels, and austenitic stainless steels) have been assessed for outliers using unsupervised techniques and supplemented with domain knowledge. Principal component analysis and k-means clustering were applied to the data, and points were assessed as outliers based on their distance away from other points in the cluster and from other points in the dataset. The outlier characteristics were investigated to determine both cluster-specific and overall trends in the properties of the outlier points. The approach demonstrated here is extensible to other alloy datasets for outlier identification and evaluation to improve the reliability of machine learning and modeling predictions for advanced alloy design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

System Integration of Rationally Designed Dilute Alloy Catalysts for Energy-Efficient Electrochemical CO 2 -To-Fuel Conversion

Energy effiecient electrochemical conversion of CO 2 to high-demand chemicals and transportation fuels using renewable solar and wind energy is a key technology needed for a high-productivity, low-carbon future. However, the development of scalable, low-cost, active, selective, and stable electrocatalysts remains a key challenge that needs to be overcome to enable high-volume conversion of CO 2 to feedstock chemicals for the chemical industry. In previous work, Lawrence Livermore National Laboratory (LLNL) has developed a rational design platform for dilute alloy transition metal electrocatalysts that promise to make electrochemical CO 2 conversion more energy efficient and selective. In this project, we worked with our industrial partners, Twelve and TotalEnergies, to improve scale up, integration, and stability of LLNL’s dilute alloy catalyst technology into an industry-relevant zero gap electrolyzer platform. Through virtual experiments and data analysis, we designed efficient and cost-effective copper-based catalysts. The catalyst was specifically designed to streamline the slowest and most energy-intensive step of the electrochemical chemical transformation of CO 2 to multi-carbon products – that is making the carbon-carbon bond by dimerization of the reaction intermediate carbon monoxide - resulting in up to 10% improvement in energy efficiency for C 2 products while simultaneously increasing the selectivity towards C 2 products. We tested two different scalable catalyst coating technologies and down-selected magnetron sputtering as the technique that provided the best control over catalyst loading, composition, and morphology. Using this technology, we successfully demonstrated integration of our dilute alloy catalysts into a 100 cm 2 electrolyzer platform with Faradaic efficiencies for ethylene production reaching 40% at a current density of 200 mA/cm 2 . We also developed the technology to integrate a well-defined nanoscale porosity by depositing alloy compositions that were compatible with dealloying, that is, selective leaching of an alloy component to generate nanoscale porosity. We observed that integration of the dealloying-derived nanoporosity improved catalyst performance and stability by leading to a more hydrophobic catalyst/anion exchange membrane interface. Unsolved problems that still need to be addressed are corrosion of the Cu catalyst -specifically if the used catalyst is exposed to air - as well as long term stability do to salt formation/deposition and flooding of the catalyst/electrolyzer flow channels, especially at higher current densities. As we only worked on optimization of catalyst composition, coating thickness, and morphology, further performance optimization will require a system level approach that includes optimization of electrolyzer design and membrane technology.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Perspectives on novel refractory amorphous high-entropy alloys in extreme environments

Two new refractory amorphous high-entropy alloys (RAHEAs) within the W–Ta–Cr–V and W–Ta–Cr–V–Hf systems were herein synthesized using magnetron-sputtering and tested under high-temperature annealing and displacing irradiation using in situ Transmission Electron Microscopy. While the 14W-41Ta-26Cr-19V in at.% RAHEA (defined as WTaCrV RAHEA) was found to be unstable under such tests, additions of Hf in this system composing a new quinary 24W-40Ta-18Cr-5V-13Hf in at.% RAHEA (defined as WTaCrVHf RAHEA) was found to be a route to achieve stability both under annealing and irradiation. A new effect of nanoprecipitate reassembling observed to take place within the WTaCrVHf RAHEA under irradiation indicates that a duplex microstructure composed of an amorphous matrix with crystalline nanometer-sized precipitates enhances the radiation response of the system. Further, it is demonstrated that tunable chemical complexity arises as a new alloy design strategy to foster the use of novel RAHEAs within extreme environments. New perspectives for the alloy design and application of chemically-complex amorphous metallic alloys in extreme environments are presented with focus on their thermodynamic phase stability when subjected to high-temperature annealing and displacing irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Achieving strong and stable nanocrystalline Al alloys through compositional design

Abstract Al alloys often suffer from low mechanical strength and lack high-temperature microstructural and mechanical robustness. A series of binary and ternary nanocrystalline (NC) Al transition metal alloys with supersaturated solid solution and columnar nanograins have been recently developed by using magnetron sputtering, manifesting a new realm of mechanical properties and thermal stability. Distinct solutes cause evident differences in the phase transformations and efficiencies for grain refinement and crystalline-to-amorphous transition. Certain sputtered Al-TM alloys have shown room-temperature mechanical strengths greater than 2 GPa and outstanding thermal stability up to 400 °C. In addition, the NC Al alloys show mechanical anisotropy and tension–compression asymmetry, revealed by micromechanical tests. Through the process encapsulating various compositionally distinct systems, we attempt to illuminate the solute effects on grain refinement and properties and more importantly, tentatively unravel the design criteria for high-strength and yet thermally stable NC Al alloys. Graphic Abstract

36 MATERIALS SCIENCE↗
DOE OSTI2024

Design and Development of Stable Nanocrystalline High‐Entropy Alloy: Coupling Self‐Stabilization and Solute Grain Boundary Segregation Effects

Abstract Grain growth is prevalent in nanocrystalline (NC) materials at low homologous temperatures. Solute element addition is used to offset excess energy that drives coarsening at grain boundaries (GBs), albeit mostly for simple binary alloys. This thermodynamic approach is considered complicated in multi‐component alloy systems due to complex pairwise interactions among alloying elements. Guided by empirical and GB‐segregation enthalpy considerations for binary‐alloy systems, a novel alloy design strategy, the “ pseudo‐binary thermodynamic ” approach, for stabilizing NC‐high entropy alloys (HEAs) and other multi‐component‐alloy variants is proposed. Using Al 25 Co 25 Cr 25 Fe 25 as a model‐HEA to validate this approach, Zr, Sc, and Hf, are identified as the preferred solutes that would segregate to HEA‐GBs to stabilize it against growth. Using Zr, NC‐Al 25 Co 25 Cr 25 Fe 25 HEAs with minor additions of Zr are synthesized, followed by annealing up to 1123 K. Using advanced characterization techniques— in situ X‐ray diffraction (XRD), scanning/transmission electron microscopy (S/TEM), and atom probe tomography, nanograin stability due to coupling self‐stabilization and solute‐GB segregation effects is reported in HEAs up to substantially high temperatures. The self‐stabilization effect originates from the preferential GB‐segregation of constituent HEA‐elements that stabilizes NC‐Al 25 Co 25 Cr 25 Fe 25 up to 0.5 T m ( T m –melting temperature). Meanwhile, solute‐GB segregation originates from Zr segregation to NC‐Al 25 Co 25 Cr 25 Fe 25 GBs; this results in further stabilization of the phase and grain‐size (≈14 nm) up to ≈0.58 and ≈0.64 T m , respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Machine-Learning Microstructure for Inverse Material Design

Metallurgy and material design have thousands of years’ history and have played a critical role in the civilization process of humankind. The traditional trial-and-error method has been unprecedentedly challenged in the modern era when the number of components and phases in novel alloys keeps increasing, with high-entropy alloys as the representative. New opportunities emerge for alloy design in the artificial intelligence era. Here a successful machine-learning (ML) method is developed to identify the microstructure images with eye-challenging morphology for a number of martensitic and ferritic steels. Assisted by it, a new neural-network method is proposed for the inverse design of alloys with 20 components, which can accelerate the design process based on microstructure. The method is also readily applied to other material systems given sufficient microstructure images. This work lays the foundation for inverse alloy design based on microstructure images with extremely similar features.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Superior High-Temperature Strength in a Supersaturated Refractory High-Entropy Alloy

Refractory high-entropy alloys (RHEA) show promising applications at high temperatures. However, achieving high strengths at elevated temperatures above 1,173K is still challenging due to heat softening. Using intrinsic material characteristics as the alloy-design principles, a single-phase body-centered-cubic (BCC) CrMoNbV RHEA with high-temperature strengths (beyond 1,000 MPa at 1,273 K) is designed, superior to other reported RHEAs as well as conventional superalloys. The origin of the high-temperature strength is revealed by in-situ neutron scattering, transmission-electron microscopy, and first-principles calculations. The CrMoNbV’s elevated-temperature strength retention up to 1,273 K arises from its large atomic-size and elastic-modulus mismatches, the insensitive temperature dependence of elastic constants, and the dominance of non-screw character dislocations caused by the strong solute pinning, which makes the solid-solution strengthening pronounced. The alloy-design principles and the insights in this study pave the way to design RHEAs with outstanding high-temperature strength.

36 MATERIALS SCIENCE↗