Search NASA⌕ Search

SEARCH · Search NASA

Results for “Solid Solution Alloys”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

Fast and Accurate Predictions of Total Energy for Solid Solution Alloys with Graph Convolutional Neural Networks

We use graph convolutional neural networks (GCNNs) to produce fast and accurate predictions of the total energy of solid solution binary alloys. GCNNs allow us to abstract the lattice structure of a solid material as a graph, whereby atoms are modeled as nodes and metallic bonds as edges. This representation naturally incorporates information about the structure of the material, thereby eliminating the need for computationally expensive data pre-processing which would be required with standard neural network (NN) approaches. We train GCNNs on ab-initio density functional theory (DFT) for copper-gold (CuAu) and iron-platinum (FePt) data that has been generated by running the LSMS-3 code, which implements a locally self-consistent multiple scattering method, on OLCF supercomputers Titan and Summit. GCNN outperforms the ab-initio DFT simulation by orders of magnitude in terms of computational time to produce the estimate of the total energy for a given atomic configuration of the lattice structure. We compare the predictive performance of GCNN models against a standard NN such as dense feedforward multi-layer perceptron (MLP) by using the root-mean-squared errors to quantify the predictive quality of the deep learning (DL) models. We find that the attainable accuracy of GCNNs is at least an order of magnitude better than that of the MLP.

Lupo Pasini, Massimiliano↗

Temperature effects on damage evolution in ion-irradiated NiCoCr concentrated solid-solution alloy

In this work, the damage evolution in equiatomic NiCoCr single crystals irradiated at 138 and 500 K with 1.5 MeV Ni+ ions has been investigated using ion channeling analysis and compared with previous results obtained at 300 K under identical irradiation conditions. As expected, irradiation temperature has a major influence on damage evolution and long-range effects in ion-irradiated NiCoCr. A change in relative irradiation resistance as a function of temperature is revealed when the ion channeling data are compared with previous ion channeling results from Ni-irradiated NiFe at 150, 300 and 500 K. Additionally, NiCoCr has superior irradiation resistance than NiFe under ion irradiation at ≤ 300 K; surprisingly, the relative irradiation resistance is reversed under ion irradiation performed at > 300 K (i.e., 500 K), which may be attributed to local chemical ordering. These observations indicate that the NiFe alloy exhibits a more favorable chemical environment for suppressing deleterious microstructural degradation under high temperature irradiation than the NiCoCr alloy.

36 MATERIALS SCIENCE↗

Microstructural evolution of compositionally complex solid-solution alloys under in-situ dual-beam irradiation

Here, this work attempts to link the microstructural evolution of single-phase compositionally complex alloy (CCA) compositions under dual-beam irradiation to their Mn-content via the stacking-fault energy (SFE) and vacancy migration energies. Two alloys, Cr 18 Fe 27 Mn 27 Ni 28 and Cr 15 Fe 35 Mn 15 Ni 35 , along with less compositionally complex pure Ni and Fe 56 Ni 44 binary were irradiated at 500 and 600 °C under dual-beam 1 MeV Kr 2+ and 16 keV He + heavy-ions up to 7 displacements per atom (dpa) with a He/dpa ratio of 0.75 %/dpa using in situ transmission electron microscopy (TEM). Due to the bubble-stabilizing effect of implanted He, bubbles were observed in all irradiations, and populations of faulted interstitial loops were characterized in Cr 18 Fe 27 Mn 27 Ni 28 and Cr 15 Fe 35 Mn 15 Ni 35 . A reduction in swelling was observed in the two CCAs compared to pure Ni and Fe 56 Ni 44 . Although swelling increased from 500 to 600 °C in Fe 56 Ni 44 , Cr 15 Fe 35 Mn 15 Ni 35 and Cr 18 Fe 27 Mn 27 Ni 28 both swelled slightly more at 500 °C. This was attributed to the difference in vacancy mobility, stronger pinning effect of vacancies on He, and the sink strength of faulted dislocation loops. Faulted interstitial loops nucleated with a higher number density and dislocation line density in Cr 15 Fe 35 Mn 15 Ni 35 at both temperatures, and at 600 °C in both materials. The differences in faulted loop population and temperature effect on swelling are correlated to the Mn-content and the measured SFE (20.2 ± 6.7 mJ/m 2 for Cr 18 Fe 27 Mn 27 Ni 28 and 9.2 ± 3.4 mJ/m 2 for Cr 15 Fe 35 Mn 15 Ni 35 ).

36 MATERIALS SCIENCE↗

A Modified Embedded-Atom Method Potential for a Quaternary Fe-Cr-Si-Mo Solid Solution Alloy

Ferritic-martensitic steels, such as T91, are candidate materials for high-temperature applications, including superheaters, heat exchangers, and advanced nuclear reactors. Considering these alloys’ wide applications, an atomistic understanding of the underlying mechanisms responsible for their excellent mechano-chemical properties is crucial. Here, we developed a modified embedded-atom method (MEAM) potential for the Fe-Cr-Si-Mo quaternary alloy system—i.e., four major elements of T91—using a multi-objective optimization approach to fit thermomechanical properties reported using density functional theory (DFT) calculations and experimental measurements. Elastic constants calculated using the proposed potential for binary interactions agreed well with ab initio calculations. Furthermore, the computed thermal expansion and self-diffusion coefficients employing this potential are in good agreement with other studies. This potential will offer insightful atomistic knowledge to design alloys for use in harsh environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Graph neural networks predict energetic and mechanical properties for models of solid solution metal alloy phases

Here, we developed a PyTorch-based architecture called HydraGNN that implements graph convolutional neural networks (GCNNs) to predict the formation energy and the bulk modulus for models of solid solution alloys for various atomic crystal structures and relaxed volumes. We trained the GCNN surrogate model on a dataset for nickel–niobium (NiNb) generated by the embedded atom model (EAM) empirical interatomic potential for demonstration purposes. The dataset was generated by calculating the formation energy and the bulk modulus as a prototypical elastic property for optimized geometries starting from initial body-centered cubic (BCC), face-centered cubic (FCC), and hexagonal compact packed (HCP) crystal structures, with configurations spanning the possible compositional range for each of the three types of initial crystal structures. Numerical results show that the GCNN model effectively predicts both the formation energy and the bulk modulus as function of the optimized crystal structure, relaxed volume, and configurational entropy of the model structures for solid solution alloys.

36 MATERIALS SCIENCE↗

Tribological Behavior of Structural Materials in High Temperature Helium Gas-Cooled Reactor Environments

The High-Temperature Gas-cooled Reactor (HTGR) is a Generation IV concept designed to produce electricity and hydrogen at high efficiencies via high operating temperatures (700 °C or higher). Helium, the primary coolant for HTGRs, contains impurities (e.g., CO, H2O and CH4) that can induce corrosion reactions at high temperatures such as oxidation and (de)carburization, which in turn can affect the tribological behavior of components. Incoloy® 800HT (Ni-Fe-Cr austenitic solid-solution alloy) and Inconel® 617 (Ni-Cr-Co-Mo solid-solution alloy) are two high-temperature superalloys currently selected as candidate structural materials for the HTGR. The objective of this study is to evaluate the high-temperature tribological performance of these two candidate alloys after conditioning them in HTGR environments. Four regimes of corrosion were considered: a non-conditioned regime (Regime I), an oxidizing regime (Regime II), a carburizing and oxidizing regime (Regime III), and a carburizing regime (Regime IV). To simulate oxidation in HTGR, samples were conditioned for 22 days at elevated temperatures in a once-through helium loop with 4 ppmv H2O. Carburization of the samples was achieved by the commercial process, Kolsterising®. In addition, two surface treatments – shot peening and aluminization – were considered as potential routes of improving the alloys’ wear resistance. Surface-treated samples were tested both before and after conditioning in Regime II. Tribological testing of the samples was performed via a pin-on-disk tribometer at elevated temperatures in ambient environment – 650 and 750°C for 800HT; 850 and 900°C for 617 – with applied loads of 1N, 2N and 5N. The wear behavior of the alloys was assessed via wear volume and friction coefficient measurements, supported by morphological, structural and compositional analyses of the wear tracks. Conditioning the samples in Regime II led to the formation of a chromium oxide on both alloys. This protective scale increased the wear resistance compared to that of as-received samples (Regime I) due to the formation of a compacted ‘glaze’ oxide layer during sliding, rendering the wear track nearly undistinguishable from the unworn background and resulting in wear volumes below the detection limits of the measurement technique. The variability of the friction coefficients of the conditioned samples was also considerably reduced compared to that of the as-received samples due to the glaze layer. Additionally, the initial friction coefficients of the samples conditioned in Regime II were reduced by 45% and 54% compared to those of as-received samples for alloys 800HT and 617, respectively. Carburizing the samples (Regime IV) hardened the surfaces of both alloys and promoted the formation of an iron oxide on 800HT during tribological testing, thereby increasing the wear resistance and decreasing the initial friction coefficient by a factor of two compared to those of as-received 800HT. Alloy 617 exhibited an enhanced wear resistance but similar initial friction coefficient compared to those of as-received samples due to the increased surface hardness. The Mn-Cr oxide developed during Regime III conditioning of 800HT did not develop a glaze layer during tribotesting, even at lower loads. Thus, it was not as protective as the oxide produced during conditioning of Regime II samples, leading to lower wear resistance of 800HT in Regime III compared to that measured in the Regime II condition. 800HT benefited from the aluminization surface treatment, particularly before conditioning in Regime II, due to the promotion of a wear-resistant aluminum oxide layer during testing and the increase in surface hardness due to the presence of a FeAl intermetallic phase. The presence of this phase caused an order-of-magnitude reduction in wear volumes compared to those of as-received 800HT. Aluminization of 617 decreased its wear resistance, particularly after conditioning in Regime II, due to significant wear of the aluminum oxide via a ceramic wear mechanism. This aluminum oxide was removed during sliding, causing the wear volumes to increase by a factor of five compared to those of 617 conditioned in Regime II. Shot-peened 800HT exhibited a tribological behavior similar to that of as-received 800HT, despite an enhancement in the rate of chromium oxide formation. Shot-peened 800HT conditioned in Regime II showed lower wear resistance compared to that of 800HT conditioned in Regime II due to the poor adhesion between the oxide and the underlying metal, preventing the formation of the glaze layer during sliding. Shot peening of 617 increased its wear resistance at higher load, reducing worn volumes by 60% compared to that measured with as-received 617. Tribotesting of shot-peened 617 in Regime II revealed that the glaze-oxide layer was formed at every load, resulting in negligible wear, similar to what was observed from testing 617 after conditioning in Regime II. Overall, alloy 617 exhibited tribologically superior behavior compared to that of alloy 800HT, as demonstrated by its lower friction coefficients and its order-of-magnitude lower wear volumes when measurable.

36 MATERIALS SCIENCE↗

Atomic Ordering-Induced Ensemble Variation in Alloys Governs Electrocatalyst On/Off States

The catalytic behavior of a material is influenced by ensembles—the geometric configuration of atoms. Traditional approaches, mainly utilizing solid-solution alloys in electrocatalysis, have often overlooked the challenges posed by concurrent changes in the electronic structure (i.e. d-band center) when the composition is altered. Here, this study introduces a methodology that distinctly separates the geometric effects (i.e. ensembles) from the electronic structure. We compare the reactivity of compositionally identical, but structurally different Pd 3 Bi ordered intermetallic and solid-solution alloys. Remarkably, we find that Pd 3 Bi intermetallics display nearly no reactivity for the methanol oxidation (MOR), while their solid-solution counterparts have significant reactivity. This highlights a unique case where materials with identical chemical compositions demonstrate drastically different catalytic behavior underscoring the critical importance of ensembles in electrocatalysis. Specifically, Pd 3 Bi intermetallics form smaller ensembles (average coordination number: 4.5 ± 1.6) with almost no measurable MOR activity at room temperature, in contrast to the solid-solution Pd 3 Bi that exhibit larger ensembles (average coordination number: 6.8 ± 0.9) and considerable MOR reactivity (0.5 mA cm −2 Pd ). An ordered Pd 3 Bi alloy, with an intermediate ensemble size (average coordination number: 5.3 ± 1.2), displays moderate MOR activity (0.1 mA cm −2 Pd ), further confirming the direct correlation between ensemble size and catalytic activity. Notably, all Pd 3 Bi alloys maintain similar electronic structures, because the chemical composition of the alloys is fixed, indicating that the differences in reactivity are predominantly from changes to the ensemble size. Our findings offer an approach for precisely controlling catalytic activity through manipulating the geometric configuration of the atoms within an alloy, paving the way for more efficient catalyst design.

alloys↗

Nanotwin stability in alloyed copper under ambient and cryo-temperature dependent deformation states

Nanometer size grains, solid solution strengthening, low temperatures, and a high density of nanotwins can provide significant strengthening to a material. Nevertheless, under loading the microstructure may evolve altering the effect of grain size, twin density, etc. on this strengthening. In some cases, these effects can be coupled as in detwinning, which is a mechanism for cryogenic grain growth. Here, in this work, a series of copper nanotwinned columnar grains are solid solution alloyed with aluminum and subject to ambient and cryogenic (–196 °C) environments during mechanical indentation, with the influence of alloying on the detwinning evolution studied. Under indentation, at a lower aluminum solute content (2 at.%), the columnar grains bent corresponding to a loss of twins. At a higher aluminum solute content (8 at.%), the grains shear and retain the nanotwins. Atomistic-scale simulations reveal an increase in the incoherent twin boundary velocity with decreasing temperature, but this boundary velocity is reduced with increasing alloy solute content. The coupling of solid solution strengthening and nanotwin stabilization is then used to explain the microstructural stability as a function of indentation at different temperature conditions.

36 MATERIALS SCIENCE↗

Potential Dependent Mn Oxidation and Its Role in Passivation of Ni 38 Fe 20 Cr 22 Mn 10 Co 10 Multi-Principal Element Alloy Using Multi-Element Resolved Atomic Emission Spectroelectrochemistry

The identity of passivating oxides on multi-principal element alloys is of great interest as their optimization offers the potential for exceptional corrosion resistance in aqueous solutions over a broad range of potential and pH. This study focuses on a non-equiatomic Ni 38 Fe 20 Cr 22 Mn 10 Co 10 solid solution alloy and tracks the fate of each alloying element during linear sweep voltammetry, low and intermediate potential holds in the passive potential domain as well as during open circuit relaxation after anodic polarization in slightly acidified Cl − solution. Ni dissolves at all potentials investigated in this work, Fe and Co are incorporated into oxides or hydroxides in low concentrations whilst Cr and Mn are enriched at passive potentials. At low passivating potentials, Mn(II) dissolves and is incorporated in minor amounts in oxides containing large concentrations of Cr(III). Considerable enrichment in Mn(II)-species occurs relative to Cr(III) in the oxide at 0.1 V vs SCE. Electrochemical impedance spectroscopy suggests the presence of layered oxides with marginal passivation at high Mn(II) levels. The formation of these oxides depends on a combination of thermodynamic and kinetic factors as well as the sequence of passivation.

Han, Junsoo (ORCID:0000000192952954)↗

Recent progress on understanding the temperature-dependent irradiation resistance ranking among NiFe, NiCoCr, and NiCoFeCr alloys: A review

Systematic temperature-effects investigations on damage evolution in ion-irradiated Ni-based concentrated solid-solution alloys (CSAs) are pivotal to provide reliance on their use in nuclear applications. Here, in search of the origin behind the temperature-dependent irradiation resistance ranking among equiatomic NiFe, NiCoCr and NiCoFeCr alloys, we have compared, previously experimental and theoretical published data involving ion irradiation experiments performed on these alloys with new ion channeling results from ion-irradiated NiCoFeCr at 500 K. Moreover, the current results are compared with independent theoretical calculations and relevant TEM results from literature, which allow us to suggest that the lower migration energy of vacancies in NiCoCr, as compared with those in NiFe and NiCoFeCr, is the reason behind why NiCoCr is no longer outperforming NiFe under ion irradiation above 300 K.

99 GENERAL AND MISCELLANEOUS↗

Temperature-Dependent Configurational Entropy Calculations for Refractory High-Entropy Alloys

The cluster expansion formalism for alloys is used to construct surrogate models for three refractory high-entropy alloys (NbTiVZr, HfNbTaTiZr, and AlHfNbTaTiZr). These cluster expansion models are then used along with Monte Carlo methods and thermodynamic integration to calculate the configurational entropy of these refractory high-entropy alloys as a function of temperature. Many solid solution alloy design guidelines are based on the ideal entropy of mixing, which increases monotonically with N , the number of elements in the alloy. However, our results show that at low temperatures, the configurational entropy of these materials is largely independent of N , and the assumption described above only holds in the high-temperature limit. This suggests that alloy design guidelines based on the ideal entropy of mixing require further examination.

36 MATERIALS SCIENCE↗

Role of chemical disorder on radiation-induced defect production and damage evolution in NiFeCoCr

Understanding chemical disorder in many concentrated solid solution alloys (CSAs) at the levels of electrons and atoms has attracted increasing attention as a path forward to reveal and identify underlying mechanisms for extraordinary mechanical properties and improved radiation tolerance. Single-phase NiFeCoCr CSA is a common base for many high-entropy alloys (HEAs) that have shown improved mechanical strength and radiation tolerance. In this study, defect production and damage evolution in NiFeCoCr under ion irradiation at room temperature to dose over 20 dpa are determined using ion channeling technique along both <100> and <110> directions utilizing multiple probing beam energies. The results obtained from the multi-axial and multi-energy channeling analysis are compared with those previously obtained for Ni crystals irradiated under similar conditions. The influence of chemical complexity on defect production and clustering at early-stage under room temperature irradiation up to dose of 1 dpa is discussed based on positron annihilation spectroscopy results. Defect structure evaluation in Ni and NiFeCoCr is also discussed based on transmission electron microscopy results over a prolonged irradiation at both room and elevated temperatures. Compared with chemically complex NiFeCoCr, larger dislocation loops thus less lattice strain are expected to form in pure Ni. Moreover, the role of chemical disorder in this CSA is also investigated based on ab initio calculations using large supercells. Finally, to understand the impact of chemical complexity effect on defect structure evolution, this integrated research effort attempts to link the relatively large charge redistribution due to difference in valence electron counts resulting from alloying different 3d transition metal elements, moderate lattice distortion arising from similar adaptable atomic size, and notable suppressed or delayed damage evolution in NiFeCoCr.

36 MATERIALS SCIENCE↗

Transferring predictions of formation energy across lattices of increasing size*

In this study, we show the transferability of graph convolutional neural network (GCNN) predictions of the formation energy of the nickel-platinum solid solution alloy across atomic structures of increasing sizes. The original dataset was generated with the large-scale atomic/molecular massively parallel simulator using the second nearest-neighbor modified embedded-atom method empirical interatomic potential. Geometry optimization was performed on the initially randomly generated face centered cubic crystal structures and the formation energy has been calculated at each step of the geometry optimization, with configurations spanning the whole compositional range. Using data from various steps of the geometry optimization, we first trained our open-source, scalable implementation of GCNN called HydraGNN on a lattice of 256 atoms, which accounts well for the short-range interactions. Using this data, we predicted the formation energy for lattices of 864 atoms and 2048 atoms, which resulted in lower-than-expected accuracy due to the long-range interactions present in these larger lattices. We accounted for the long-range interactions by including a small amount of training data representative for those two larger sizes, whereupon the predictions of HydraGNN scaled linearly with the size of the lattice. Therefore, our strategy ensured scalability while reducing significantly the computational cost of training on larger lattice sizes.

36 MATERIALS SCIENCE↗