Nb-Mediated Grain Growth and Grain-Boundary Engineering in Mg[subscript 3]Sb[subscript 2]-Based Ther
Explore the source record for details and available documents.
SEARCH · Engineering Papers
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.
Explore the source record for details and available documents.
Grain-boundary engineering is pivotal to fully utilize the mechanical, electrical, and thermal-transport properties of various materials. However, current methods in metallurgy rely almost exclusively on top-down approaches, making precise grain-boundary engineering, especially at nanoscale, difficult to achieve. Herein, we report a method to produce tailored grain-boundary conditions with nanoscale precision from colloidal metal nanocrystals through surface treatment followed by a pressure-sintering process. The resulting bulk grain-boundary materials (which we call “nanocrystal coins”) possess a metal-like appearance and conductivity while inheriting the original domain features of the nanocrystal building blocks. In this work, nanoindentation measurements confirmed the superior mechanical hardness of the obtained materials. Further, we use this method to fabricate, for the first time, a single-component bulk metallic glass from amorphous palladium nanoparticles. Our discovery may spur the development of new materials whose functionality crucially depends on the domain configuration at nanoscale, such as superhard materials, thermoelectric generators, and functional electrodes.
Compositionally complex ceramics (CCCs), including high-entropy ceramics, offer a vast, unexplored compositional space for materials discovery. Herein, we propose and demonstrate strategies for tailoring CCCs via a combination of non-equimolar compositional designs and control of grain boundaries (GBs) and microstructures. Using oxide solid electrolytes for all-solid-state batteries as an example, we have discovered a class of compositionally complex perovskite oxides (CCPOs) with improved lithium ionic conductivities beyond the limit of conventional doping. For example, we demonstrate that the ionic conductivity can be improved by >60% in (Li 0.375 Sr 0.4375 )(Ta 0.375 Nb 0.375 Zr 0.125 Hf 0.125 )O 3-δ compared with the (Li 0.375 Sr 0.4375 )(Ta 0.75 Zr 0.25 )O 3-δ (LSTZ) baseline. Furthermore, the ionic conductivity can be improved by another >70% via quenching, achieving >270% of the LSTZ. Notably, we demonstrate GB-enabled conductivity improvements via both promoting grain growth and altering GB structures through compositional designs and processing. In a broader perspective, this work suggests new routes for discovering and tailoring CCCs for energy storage and many other applications.
Increased demand for high-performance permanent magnets in the electric vehicle and wind-turbine industries has prompted the search for cost-effective alternatives. Discovering magnetic materials with the desired intrinsic and extrinsic permanent magnet properties presents a significant challenge to researchers because of issues with the global supply of rare-earth elements, material stability, and a low maximum magnetic energy product BH max . While first-principles density functional theory (DFT) predicts materials’ magnetic moments, magnetocrystalline anisotropy constants, and exchange interactions, it cannot compute extrinsic properties such as coercivity (H c ). Although it is possible to calculate H c theoretically with micromagnetic simulations, the predicted value is larger than the experiment by almost an order of magnitude due to the Brown paradox. To circumvent these issues, we employ machine-learning (ML) methods on an extensive database obtained from experiments, DFT calculations, and micromagnetic modeling. The use of a large experimental dataset enables realistic H c predictions for materials such as Ce-doped Nd 2 Fe 14 B, comparing favorably against micromagnetically simulated coercivities. Remarkably, our ML model accurately identifies uniaxial magneto-crystalline anisotropy as the primary contributor to H c . With DFT calculations, we predict the Nd-site-dependent magnetic anisotropy behavior in Nd 2 Fe 14 B, confirming that Nd 4g sites mainly contribute to uniaxial magnetocrystalline anisotropy, and also calculate the Curie temperature (T c ). Finally, both calculated results are in good agreement with the experiments. The coupled experimental dataset and ML modeling with DFT input predict H c with far greater accuracy and speed than was previously possible using micromagnetic modeling. Further, we reverse engineer the grain-boundary and intergrain exchange coupling with micromagnetic simulations by employing the ML predictions.
Lithium (Li) metal anode is a promising candidate for high energy density solid-state batteries. However, the interface issues, including large interfacial resistance and Li dendrite generation, have always frustrated the attempt to commercialize solid-state Li metal batteries (SSLBs). Here, we report that infusing the garnet-type solid electrolytes (GSEs) with air-stable electrolyte Li 3 PO 4 (LPO) dramatically reduces the interfacial resistance to ~1 Ω cm 2 and achieves a high critical current density of 2.2 mA cm -2 under ambient condition due to enhanced interfacial stability to Li metal anode. The coated and infused LPO electrolytes not only improve the mechanical strength and Li-ion conductivity of grain boundaries, but also form a stable Li-ion conductive but electron-insulating LPO-derived solid-electrolyte interphase between Li metal and GSEs, and consequently eliminates the Li dendrites growth and prevents the direct reduction of GSEs by Li metal over a long cycle life. This interface engineering approach together with grain-boundary modification on GSEs represents a promising strategy to revolutionize the anode-electrolyte interface chemistry for SSLBs and provides new design strategy for other-types of solid-state batteries.
The concept of grain-boundary-engineering through elimination of the grain-boundary silicate phase in silicon nitride was developed. The process involved removal of the silica from the nitride powder via a thermal treatment coupled with the use of nitride additives to compensate the remaining oxygen. Magnesium and aluminum nitrides are found to be the most effective additive for use as oxygen compensators. Strength decreases at elevated temperatures are not observed in the alumina containing material. The creep rate of a dual additive sialon composition was two orders of magnitude lower at 1400 C than commercial silicon nitride. A cursory analysis of the creep mechanism indicate that grain-boundary sliding is avoided through elimination of the grain-boundary silicate phase.
Combined computational and experimental approaches were used to evaluate defective 2H-MoS 2 nanosheets for their activity and selectivity for hydrogen evolution reaction (HER) and nitrogen reduction reaction (NRR). Density functional theory calculations were used to understand the relationship between HER and NRR activity on the ideal basal MoS 2 plane, seven grain-boundaries, ten single-/few-atom vacancies and anti-sites, and zigzag and armchair edge sites. The results confirm that 2H-MoS 2 should contain several defects with high activity for HER: armchair and zigzag edges, VS vacancy, MoS 2 anti-site, and S-S and Mo-Mo grain boundaries. Considering Gibbs free energy change for all the steps in the NRR mechanism and kinetic barriers for a key NRR step, we have found that activation of perspective NRR selective sites in 2H-MoS 2 , namely V MoS6 and clusters of S-vacancies, would require large overpotential, conditions at which HER dominates. The DFT conclusions are supported by the electrochemical studies of NRR activity and selectivity under aqueous conditions, which show an increase in NRR activity but a decrease in Faradaic efficiency as applied cell potential becomes more negative. The results of this work therefore highlight the challenges in activating natural 2H-MoS 2 for NRR, which would require additional material engineering or reaction condition optimization as a way to suppress HER, decrease the NRR overpotential or preferentially both.
Superplasticity, the capacity of materials to sustain extraordinary tensile elongations at elevated temperatures, underpins a range of advanced metal-forming technologies. Conventionally, it is achieved in fine-grained alloys where deformation is dominated by grain-boundary sliding, accommodated by diffusion and dislocation activity. The advent of medium- and high-entropy alloys (M/HEAs), with their high chemical complexity and unconventional phase stability, offers new pathways to superplastic behavior beyond traditional alloy systems. Although investigated only recently, several M/HEAs already exhibit elongations that rival or exceed those of classical superplastic materials, particularly when ultrafine or metastable microstructures are engineered. Here, we review progress in understanding superplastic deformation in M/HEAs, emphasizing the interplay among composition, initial microstructure, thermomechanical processing, and microstructural evolution during high-temperature deformation. We discuss approaches to generating the fine-grained structures necessary for grain-boundary sliding, including severe plastic deformation and tailored heat treatments. We further highlight dynamic phenomena such as phase transformations, evolving grain-boundary chemistry, and deformation-induced grain refinement that can enhance plasticity in these systems. These mechanisms often shift the balance of deformation processes, enabling large elongations even outside classical criteria. Finally, we outline key challenges for application, including cost, scalability, recyclability, and microstructural stability.
The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.
Here, we report on atomic-scale analyses of grain boundary (GB) structures and segregation in Nb 3 Sn coatings on Nb, prepared by the vapor-diffusion process, for superconducting radiofrequency (SRF) cavity applications, utilizing atom-probe tomography, high-resolution scanning transmission electron-microscopy and first-principles calculations. We demonstrate that the chemical composition of Nb 3 Sn GBs is correlated strongly with the diffusion of Sn and Nb at GBs during the coating process. In a sample coated with a relatively large Sn flux, we observe an interfacial width of Sn segregation at a GB of ~3 nm, with a maximum concentration of ~35 at.%. After post-annealing at 1100 °C for 3 h, the Sn segregated at GBs disappears and Nb segregation is observed subsequently at GBs, indicating that Nb diffused into the Nb3Sn GBs from the Nb substrate. It is also demonstrated that the amount of Sn segregation in a Nb 3 Sn coating can be controlled by: (i) Sn flux; and (ii) the temperatures of the Nb substrates and Sn source, which may affect the overall kinetics including GB diffusion of Sn and Nb. An investigation of the correlation between the chemical compositions of GBs and Nb 3 Sn SRF cavity performance reveals that the Nb 3 Sn SRF cavities with the best performance (high-quality factors at high accelerating electric-field gradients) do not exhibit Sn segregation at GBs. Our results suggest that the chemical compositions of GBs in Nb 3 Sn coatings for SRF cavities can be controlled by GB engineering and can be utilized to optimize fabrication of high-quality Nb 3 Sn coatings for SRF cavities.
Solute segregation to individual grain boundaries is used by design to produce strong and stable nanocrystalline metallic alloys. Grain-boundary segregation, however, is known to cause adverse embrittlement effects from a strain-localization failure mechanism that imposes significant material limitations for structural applications. Here, using atomistic simulations, it is discovered that heterogeneous Ni segregation in nanocrystalline Ni-mixed Ag alloys dramatically shuts down localized shear bands during plastic deformation, while simultaneously increasing the tensile strength. Nanocrystalline Cu-mixed Ag metals are predicted to exhibit standard homogeneous Cu segregation and a tensile strength that saturates above a solute concentration of 8 at.% due to glass-like shear localization induced by grain boundaries. By contrast, it is found that heterogeneous Ni segregation in nanocrystalline Ag-Ni alloys forms solute-rich clusters along interfaces leading to strain delocalization at high strain and continuous strengthening at high solute concentrations up to 15 at.%. As a result, this study reveals the importance of heterogeneous versus homogeneous segregation behaviors on strain localization and points to a fundamentally new strategy to design failure-resistant nanostructured materials through grain boundary segregation engineering.
The breakdown from grain-size strengthening to softening mechanisms is generally well understood for high-purity nanocrystalline materials when the mean grain size decreases to the nanometer range. In nanocrystalline alloys, however, the stabilization of nanosized grains by grain-boundary solute segregation complicates the above mechanisms. Moreover, current segregation models have little predictive power for determining the optimal solute content that maximizes Hall-Petch strengthening effects. In this article, using large-scale hybrid Monte-Carlo/molecular dynamic simulations, we present a systematic study of the Hall–Petch breakdown in Cu-segregated Ag alloys with grain sizes ranging from 8 nm to 59 nm, where three concentration-dependent regimes of plasticity are described: (1) Classical segregation strengthening behavior at low solute contents, (2) shear band-induced softening at high solute contents, and (3) a previously unknown, but extended plateau of maximum strengths for intermediate solute contents from 4 to 15 at.%, which we term as nanocrystalline Sterling silver. We find that flow strengths in nanocrystalline Sterling alloys naturally exhibit a zero-slope limit at the smallest grain sizes that is well below the ideal Hall–Petch strengthening trend. This phenomenon results from partially active grain-boundary segregation that acts to influence interfacial plasticity in some, but not all, grain boundary regions. Our findings amplify the atomic nature of solute segregation and interaction at grain boundaries and its complex roles on grain boundary-mediated plasticity mechanisms in nanocrystalline alloys.
The thermal evolution of nanoscale oxide inclusions in 316L stainless steel (SS) manufactured by laser powder bed fusion additive manufacturing (AM) was explored. The size, chemical composition, morphology, and distribution of the oxides were characterized as the function of heat treatment conditions. The study revealed the mechanistic driving force of the rapid oxide coarsening during recrystallization. Ostwald ripening governs oxide coarsening. The active grain boundary-oxide interaction at the early stage of recrystallization accelerated oxide coarsening via enhanced solute diffusion along grain boundaries. Pipe diffusion along dislocation cellular boundaries has a negligible contribution to oxide coarsening. At high temperatures (T> 1065 °C), although lattice diffusion primarily controlled the oxide growth, the contribution from the grain-boundary diffusion was necessary. The transformation from MnSiO 3 to CrMn 2 O 4 took place in the un-recrystallized grains but was not observed when recrystallization started. The interaction of grain boundary and oxides during recrystallization resulted in a high fraction of oxides accumulated at grain boundaries. While oxide coarsening does not significantly alter the toughness value, grain-boundary oxides promote microvoid formation and intergranular fracture under Charpy impact in the recrystallized AM 316L SS.
Developing ultrahigh-strength steels that are ductile, fracture resistant, and cost effective would be attractive for a variety of structural applications. We show that improved fracture resistance in a steel with an ultrahigh yield strength of nearly 2 gigapascals can be achieved by activating delamination toughening coupled with transformation-induced plasticity. Delamination toughening associated with intensive but controlled cracking at manganese-enriched prior-austenite grain boundaries normal to the primary fracture surface dramatically improves the overall fracture resistance. As a result, fracture under plane-strain conditions is automatically transformed into a series of fracture processes in “parallel” plane-stress conditions through the thickness. The present “high-strength induced multidelamination” strategy offers a different pathway to develop engineering materials with ultrahigh strength and superior toughness at economical materials cost.
Today, a major thrust for achieving engine components with improved thermal capability is the development of fiber-reinforced silicon-carbide (SiC) matrix composites. These materials are not only lighter and capable of higher use temperatures than state-of-the-art metallic alloys and oxide matrix composites (approx. 1100 C), but they can provide significantly better static and dynamic toughness than unreinforced silicon-based monolithic ceramics. However, for successful application in advanced engine systems, the SiC matrix composites should be able to withstand component service stresses and temperatures for the desired component lifetime. Since the high-temperature structural life of ceramic materials is typically controlled by creep-induced flaw growth, a key composite property requirement is the ability to display high creep resistance under these conditions. Also, because of the possibility of severe thermal gradients in the components, the composites should provide maximum thermal conductivity to minimize the development of thermal stresses. State-of-the-art SiC matrix composites are typically fabricated via a three-step process: (1) fabrication of a component-shaped architectural preform reinforced by high-performance fibers, (2) chemical vapor infiltration of a fiber coating material such as boron nitride (BN) into the preform, and (3) infiltration of a SiC matrix into the remaining porous areas in the preform. Generally, the highest performing composites have matrices fabricated by the CVI process, which produces a SiC matrix typically more thermally stable and denser than matrices formed by other approaches. As such, the CVI SiC matrix is able to provide better environmental protection to the coated fibers, plus provide the composite with better resistance to crack propagation. Also, the denser CVI SiC matrix should provide optimal creep resistance and thermal conductivity to the composite. However, for adequate preform infiltration, the CVI SiC matrix process typically has to be conducted at temperatures below 1100 C, which results in a SiC matrix that is fairly dense, but contains metastable atomic defects and is nonstoichiometric because of a small amount of excess silicon. Because these defects typically exist at the matrix grain boundaries, they can scatter thermal phonons and degrade matrix creep resistance by enhancing grain-boundary sliding. To eliminate these defects and improve the thermomechanical properties of ceramic composites with CVI SiC matrices, researchers at the NASA Glenn Research Center developed a high-temperature treatment process that can be used after the CVI SiC matrix is deposited into the fiber preform.