Hydrogen segregation to dislocations and formation of nano-hydrides
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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.
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This poster was displayed at UPISC. It details NETL advancements in single crystal optical fiber.
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In the globular cluster NGC 3201, we study subpopulations (SPs) of red giants (RGs) distinguished by their characteristics. In its central part, we make use of multicolor Hubble Space Telescope (HST) photometry coupled with spectroscopy of RGs spread out over a larger cluster face. In the color index CI = (m{sub F275W}−m{sub F336W}) −(m{sub F336W}−m{sub F439W}), RGs commonly referred to as first generation, SPI, are separated from the counterparts of the second generation, SPII. The latter are more concentrated than the former at a confidence level of P = 93%, within the field covered by the HST photometry. Their minor portion (∼28%, SPIIm) located in the middle of the δCI range spanned across the split RG branch relative to the splitting edge is more centrally concentrated at a higher confidence level of 96%. We found, from the [Na/Fe]−δCI plot for RGs in common between the photometry and spectroscopy, that SPI and SPII are mostly overlapped within 0.0 < [Na/Fe] < 0.3. RGs with [Na/Fe] < 0.0 (mostly SPI) keep their lower concentration to the cluster center over larger radial distance as compared to SPII RGs with [Na/Fe] > 0.3 at a confidence level of P = 88%. It is increased up to 95% if a restriction on [O/Fe] is imposed. The obtained result, particularly in the central part, is a clue that SPIIm RGs are the descendants of more massive progenitors. Of these RGs approximately one-third probably originate from recent (within the past 1.5 Gyr) blue stragglers with M {sub BS} > 1.1M {sub ☉}, and the other two-thirds could be accounted for by older collision products of primordial MS stars.
Presented at the CNMS User Meeting 2020, August 10-12, 2020, Virtual Conference, 8/10
Abstract not provided.
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Segregation of alloying elements to a prismatic dislocation loop under irradiation is an important phenomenon in understanding the role of loops in radiation effects in alloys. In this work, various segregation sequences of Cr and Al atoms to a $\langle$100$\rangle$ and a 1/2 $\langle$111$\rangle$ prismatic dislocation loop in a Fe-Cr-Al alloy are explored using molecular dynamics method and ab initio energy calculation. Here, the results reveal that Cr can readily segregate to the loops while Al atoms cannot by themselves, but the segregated Cr atoms are able to promote Al segregation at the loops, defined as a coupled segregation of Cr and Al. After interacting with Cr and Al, a previously mobile 1/2 $\langle$111$\rangle$ loop becomes sessile. Al segregation through the coupled segregation process can further affect the pinning behavior of a dislocation loop to an edge dislocation motion. By varying the Al fraction in the segregated solutes, a nonlinear dependence of the pinning effect on dislocation motion is determined. At lower fractions, the pinning strength increases with the increasing Al fraction until Al fraction reaches a critical value of about 19%, above which the pinning strength decreases with further increase of Al fraction. All these results suggest that, in addition to the effect of Al on the surface resistance to oxidation, Al effect on the dislocation loop behavior is important to optimize the composition of Fe-Cr-Al alloys for their applications in accident tolerant fuel concepts.
Boron is commonly added to superalloys in small amounts to enhance creep resistance, but can lead to cracking at high concentrations, especially during the additive manufacturing process. Two variants of CoNi-based GammaPrint®-700 superalloy with different B contents (0.08 at% vs 0.16 at%) were printed via laser powder bed fusion (LPBF) with the same printing parameters, with only the high B alloy exhibiting solidification cracking. Atom probe tomography (APT) revealed stronger segregation behaviors in the high B alloy compared to the low B alloy at both the inter-dendritic regions and grain boundaries (GBs). The segregation behavior at inter-dendritic regions was well captured with Scheil simulation and can correlate with the existing cracking susceptibility index (CSI) on cracking tendencies, although high angle GBs are where cracking occurs according to electron backscatter diffraction (EBSD) measurements. Additionally, the extent of GB segregation was compared between the high B and low B alloy. Higher B additions led to significantly more GB B segregation in the high B alloy compared to the low B alloy. Further, for the high B alloy, the cracked region of one GB exhibited higher levels of B compared to the uncracked region of the same GB. However, much higher B contents were also found in two other uncracked GBs in the high B alloy, which demonstrates that higher GB B concentrations are not fully responsible for the cracking. A much larger variance in GB B segregation content was found in the high B alloy compared to the low B alloy. These phenomena were explained with a solidification model with the GB segregation content expressed explicitly by a modified Langmuir-McLean equation. This model linked the GB segregation content with solidification undercooling, which can be used as quantitative cracking criteria for future builds.
Grain boundaries in metallic materials can exist in a wide range of stable and metastable structures. In addition, the properties of a grain boundary may be altered through solute segregation. In this work, we present a formulation that combines the spectrum of embrittling potencies associated with solute segregation with site-occupancy statistics. As a prototype problem, we illustrate the relation between segregation and embrittlement in the case of S segregation to grain boundaries in Ni. To obtain a population of site segregation energies, we perform molecular statics calculations on 378 different symmetric-tilt grain boundaries and their free surface equivalents, using an embedded-atom method interatomic potential developed specifically for studying embrittlement. Our results show that it is important to consider both the energies associated with embrittlement and the probability of occupancy to describe the general embrittling nature of a grain boundary. When analyzed in isolation, certain grain boundaries show large embrittling potencies; however, that effect is diminished when the probability of S segregation to that grain boundary is considered within a polycrystal. We propose a new quantity, the embrittling estimator, which not only categorizes grain boundaries as embrittling or strengthening, but also considers site occupancy probabilities, so that the embrittlement behavior of grain boundaries within a network of grain boundaries can be compared. Finally, we examine the relationship between embrittlement behavior and innate grain boundary properties, such as the free volume, and find statistical evidence that the complex nature of embrittlement cannot be explained by linear correlations with excess volumes or energies. Ultimately, this combined approach provides a theoretical tool to assist grain boundary engineering of metastable alloys.
Enhancement of thermal stability in Al-Ni alloys through microalloying with slow-diffusing elements, specifically Zr, has been previously reported which is attributed to Zr segregation at the Al/Al 3 Ni interface. In this study, we explore the influence of microalloying Al-Ni alloys with Zr, Ti, V, and Fe on microstructural evolution, hardness, and electrical and thermal conductivity across a range of heat-treatment temperatures from 300 to 450 °C. The distribution of microalloying elements and precipitates after heat treatment is characterized using atom probe tomography (APT). Our investigation confirms Zr segregation to the Al/Al 3 Ni interface, while similar interfacial segregation is absent with the addition of Ti, V, and Fe. Additionally, our analysis of the Al 3 Ni microfiber morphology reveals that their coarsening and spheroidization rates are similar with and without interfacial segregation; thus, retaining the fiber reinforcement through interfacial segregation of slow diffusing elements may not be an effective strategy. Precipitation of L1 2 nanoparticles was found to be the dominant mechanism affecting enhanced hardness and electrical conductivity in Al-Ni-Zr alloys, attributed to precipitation strengthening and solute depletion, respectively. Similar precipitation was not observed for additions of Ti, V, and Fe following heat treatment. We provide a thermodynamic explanation for this limitation. Furthermore, the findings of this study suggest that an effective approach for designing Al-Ni alloys should involve prioritizing microalloying elements to maximize L1 2 precipitation and minimize solute content in the FCC-Al matrix post heat treatment, rather than focusing on Al/Al3Ni interfacial segregation.
First-Passage Kinetic Monte Carlo (FPKMC) simulations of species migration in duplex stainless steels were performed in order to establish relationships between alloy content, segregation behavior, and the formation of Ni-Si-Mn rich particles in cast duplex stainless steels during thermal aging. The Ni-Si-Mn-rich second phase forms after extended aging at reactor operating temperatures and degrades alloy properties. Simulations of Ni-Si-Mn cluster formation were validated through comparison with experimental results obtained through Atom Probe Tomography (APT) on similar alloy compositions, identifying several trends. First, Cu promotes the formation of Ni-Si-Mn clusters, but only when Ni or Mn prefer segregation to the surface of Cu particles; without the segregation of these species, the critical composition for the clusters to form was not achieved. Second, the width of precipitate-denuded zones near ?/d interfaces increases with decreasing Cu content. This finding was in strong agreement with APT results, further validating our model. Finally, our model predicts that Ni-Si-Mn cluster formation will be the most extensive when the Si:Mn ratio is approximately 1:1 and the least extensive when one of these key elements is less concentrated (Mn = 0.5 at.% or Si = 0.5 at.%). The implications of these results on how to improve alloy properties are discussed.
This study explores the use of machine learning (ML) as a computational tool to accelerate the design of multi-principal element alloys (MPEAs) with improved tensile elongation. An ML model was trained using available experimental data from the literature along with theoretically derived features to predict yield strength (YS) and ductility. A subset of ML-predicted compositions—CoNiVFe, CoNiVTi, CoNiVTiFe, and CoCrNiVTi—was synthesized and evaluated through tensile testing. The ML model underpredicted YS by approximately 20–30 % and overpredicted ductility by 60–70 % for Ti-containing alloys. Microstructural analysis revealed that Ti segregation at interdendritic regions contributed to early fracture, leading to discrepancies in ductility predictions. Ti segregation at these regions likely drives the increased YS due to segregation strengthening. In contrast, the CoNiVFe alloy showed good agreement with both experimental YS and elongation, with prediction errors of ∼10.2 % and ∼20.7 %, respectively. Microstructural characterization revealed minimal segregation in this alloy, suggesting that the ML model can reliably predict the properties of alloys with little to no segregation. These findings highlight the capability of ML in predicting YS with good accuracy but underscore its limitations in capturing defect-driven failure mechanisms such as segregation-induced embrittlement.
We develop an efficient molecular-statics algorithm for predicting local solute-solute interaction effects on grain-boundary segregation. This algorithm is applied to the segregation and interaction of Ni and Cu solutes in a Σ9 (221) symmetric tilt grain boundary in Ag. It is found that the strength of interaction between two solutes directly correlates with the change of average segregation energy in the local atomic environment of a fixed grain-boundary solute. It is shown that local interaction effects at grain boundaries can be either attractive or repulsive wherein long-range attractive effects increase the propensity for solute cluster nucleation. This study underscores the atomic nature of grain-boundary solute segregation and provides a tool that could yield meaningful insight into heterogeneous solute segregation phenomena in polycrystalline alloys beyond their dilute limit.
Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 8046 CRISPRi perturbations targeting 1721 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual’s response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.
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