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At least 37 records · Page 2

A critical dislocation velocity for serration mechanism transition in a nickel-chromium solid solution alloy

Here, the influence of strain rate across three orders of magnitude (1.70 × 10 –5 /s to 1.43 × 10 –2 /s) along with the effect of the plastic strain accumulation (up to 10%) on the serrated plastic flow were investigated in the nickel-chromium (Ni-Cr) solid solution alloy Nimonic 75 by performing constant-strain-rate tension testing at 600 °C. As the strain rate decreased, the critical strain for the onset of serrations transitioned from normal behavior to inverse behavior. The serrated flow was characterized as Type A+B serration at high strain rate (1.43 × 10 –2 /s). In the intermediate strain-rate regime (1.43 × 10 –3 /s and 1.45 × 10 –4 /s), Type B serrations were observed and followed by a transformation to Type C+B serrations. At the low strain rate (1.70 × 10 –5 /s), the plastic flow immediately displayed Type C serrations, which later evolved into Type C+B serrations. Regardless of the strain rate, plastic strain, or dislocation density, a critical dislocation velocity falling in the range of 1.2 × 10 –6 – 2.2 × 10 –6 m/s was identified to signify the onset of Type C serration, whereby the mobile dislocations break free from the solute cloud for short bursts of deformation. Finally, a novel model by solute rearrangement across dislocation cores was used to understand how the critical dislocation velocity is quantitatively determined by the rate at which solute atoms are able to hop across the glide plane as a partial dislocation core moves through the lattice.

36 MATERIALS SCIENCE↗

The Evolution of the Deformation Substructure in a Ni-Co-Cr Equiatomic Solid Solution Alloy

The equiatomic NiCoCr alloy exhibits an excellent combination of strength and ductility, even greater than the FeNiCrCoMn high entropy alloy, and also displays a simultaneous increase in strength and ductility with decreasing the testing temperature. To systemically investigate the origin of the exceptional properties of NiCoCr alloy, which are related to the evolution of the deformation substructure with strain, interrupted tensile testing was conducted on the equiatomic NiCoCr single-phase solid solution alloy at both cryogenic and room temperatures at five different plastic strain levels of 1.5%, 6.5%, 29%, 50% and 70%. The evolution of deformation substructure was examined using electron backscatter diffraction (EBSD), transmission Kikuchi diffraction (TKD), conventional transmission electron microscopy (CTEM), diffraction contrast imaging using STEM (DCI-STEM) and atomic resolution scanning transmission electron microscopy. While the deformation substructure mainly consisted of planar dislocation slip and the dissociation of dislocations into stacking faults at small strain levels (≤6.5%), at larger strain levels, additional substructures including nanotwins and a new phase with hexagonal close packed (HCP) lamellae also appeared. The volume fraction of the HCP lamellae increases with increasing deformation, especially at cryogenic temperature. First principles calculations at 0 K indicate that the HCP phase is indeed energetically favorable relative to FCC for this composition. The effects of the nanotwin and HCP lamellar structures on hardening rate and ductility at both cryogenic and room temperature are qualitatively discussed.

Twinning↗

Deformation mechanisms in single crystal Ni-based concentrated solid solution alloys by nanoindentation

Nanoindentation is a critical technique to probe mechanical properties at the micrometer and sub-micrometer scales, accompanied by challenges from indentation size effect, pile-up/sink-in effect, and strain rate sensitivity. In this work, different nanoindentation techniques have been employed to explore Ni-based concentrated solid solution alloys (CSAs) with the addition of 3d transition metal elements including Co, Cr, Mn, and Fe, including unique single-crystal Ni, NiCo, NiFe, Ni 80 Cr 20 , and NiCoFeCr samples with (100) surfaces. A procedure of nanoindentation tests and data analysis/correction have been developed, and a data set of hardness, elastic modulus, strain rate sensitivity, and activation volume for Ni-based CSAs are provided, including the less explored binary alloys such as Ni 80 Cr 20 and Ni 80 Mn 20 . The results show that the type of alloying elements is more critical than the number of elements in strengthening: Co does not provide strengthening in NiCo, while Cr, Mn, and Fe are effective strengthening elements. Cr is the most effective among all the 3d transition metal elements. Furthermore, atomic-level lattice distortion is responsible for the strengthening and the role of stacking fault energy is insignificant in Ni-based CSAs at room temperature. In summary, nanoindentation shows increasing promise as a reliable and fast tool to provide comprehensive mechanical information for new alloy design and development.

36 MATERIALS SCIENCE↗

Molecular dynamics simulation of vacancy and void effects on strain-induced martensitic transformations in Fe-50 at.% Ni model concentrated solid solution alloy

Strain-induced martensitic transformations can improve the strength and ductility of some face centered cubic (FCC) metals and alloys. Irradiation-induced defects such as vacancies, dislocation loops, and voids activate martensitic transformations over a wider range of mechanical loading conditions than in pristine material. Furthermore, the mechanisms underlying irradiation-enabled martensite transformations remain unclear. In this work, we use molecular dynamics simulations to study the effect of vacancies and voids on strain-induced martensitic transformations in a model concentrated solid solution alloy Fe-50 at.% Ni. It has been found that single vacancies have no resolvable effect on the transformation because they reduce the stacking fault energy by a relatively insignificant margin and do so only if the vacancy is located on the stacking fault plane. Voids, however, activate the martensite transformation through shear strain accumulation around the void due to dislocation pileup. The larger the void, the more pronounced this effect.

36 MATERIALS SCIENCE↗

Fast and stable deep-learning predictions of material properties for solid solution alloys

We present a novel deep learning (DL) approach to produce highly accurate predictions of macroscopic physical properties of solid solution binary alloys and magnetic systems. The major idea is to make use of the correlations between different physical properties in alloy systems to improve the prediction accuracy of neural network (NN) models. We use multitasking NN models to simultaneously predict the total energy, charge density and magnetic moment. These physical properties mutually serve as constraints during the training of the multitasking NN, resulting in more reliable DL models because multiple physics properties are correctly learned by a single model. Two binary alloys, copper–gold (CuAu) and iron–platinum (FePt), were studied. Our results show that once the multitasking NN's are trained, they can estimate the material properties for a specific configuration hundreds of times faster than first-principles density functional theory calculations while retaining comparable accuracy. We used a simple measure based on the root-mean-squared errors to quantify the quality of the NN models, and found that the inclusion of charge density and magnetic moment as physical constraints leads to more stable models that exhibit improved accuracy and reduced uncertainty for the energy predictions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

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↗

Development and Characterization of Improved NiTiPd High-Temperature Shape-Memory Alloys by Solid-Solution Strengthening and Thermomechanical Processing

The need for compact, solid-state actuation systems for use in the aerospace, automotive, and other transportation industries is currently motivating research in high-temperature shape-memory alloys (HTSMA) with transformation temperatures greater than 100 C. One of the basic high-temperature alloys investigated to fill this need is Ni(19.5)Ti(50.5)Pd30. Initial testing has indicated that this alloy, while having acceptable work characteristics, suffers from significant permanent deformation (or ratcheting) during thermal cycling under load. In an effort to overcome this deficiency, various solid-solution alloying and thermomechanical processing schemes were investigated. Solid-solution strengthening was achieved by substituting 5at% gold or platinum for palladium in Ni(19.5)Ti(50.5)Pd30, the so-called baseline alloy, to strengthen the martensite and austenite phases against slip processes and improve thermomechanical behavior. Tensile properties, work behavior, and dimensional stability during repeated thermal cycling under load for the ternary and quaternary alloys were compared. The relative difference in yield strength between the martensite and austenite phases and the dimensional stability of the alloy were improved by the quaternary additions, while work output was only minimally impacted. The three alloys were also thermomechanically processed by cycling repeatedly through the transformation range under a constant stress. This so-called training process dramatically improved the dimensional stability in these samples and also recovered the slight decrease in work output caused by quaternary alloying. An added benefit of the solid-solution strengthening was maintenance of enhanced dimensional stability of the trained material to higher temperatures compared to the baseline alloy, providing a greater measure of over-temperature capability.

Bigelow, Glen↗

Investigation of compositional segregation during unidirectional solidification of solid solution semiconducting alloys

Compositional segregation of solid solution semiconducting alloys in the radial direction during unidirectional solidification was investigated by calculating the effect of a curved solid liquid interface on solute concentration at the interface on the solid. The formulation is similar to that given by Coriell, Boisvert, Rehm, and Sekerka except that a more realistic cylindrical coordinate system which is moving with the interface is used. Analytical results were obtained for very small and very large values of beta with beta = VR/D, where V is the velocity of solidification, R the radius of the specimen, and D the diffusivity of solute in the liquid. For both very small and very large beta, the solute concentration at the interface in the solid C(si) approaches C(o) (original solute concentration) i.e., the deviation is minimal. The maximum deviation of C(si) from C(o) occurs for some intermediate value of beta.

Wang, J. C.↗

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↗

Solidification and crystal growth of solid solution semiconducting alloys

Problems associated with the solidification and crytal growth of solid-solution semiconducting alloy crystals in a terrestrial environment are described. A detailed description is given of the results for the growth of mercury cadmium telluride (HgCdTe) alloy crystals by directional solidification, because of their considerable technological importance. A series of HgCdTe alloy crystals are grown from pseudobinary melts by a vertical Bridgman method using a wide range of growth rates and thermal conditions. Precision measurements are performed to establish compositional profiles for the crystals. The compositional variations are related to compositional variations in the melts that can result from two-dimensional diffusion or density gradient driven flow effects ahead of the growth interface. These effects are discussed in terms of the alloy phase equilibrium properties, the recent high temperature thermophysical data for the alloys and the highly unusual heat transfer characteristics of the alloy/ampule/furnace system that may readily lead to double diffusive convective flows in a gravitational environment.

Lehoczky, S. L.↗