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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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At least 127 records · Page 7

Thin film combinatorial sputtering of TaTiHfZr refractory compositionally complex alloys for rapid materials discovery

Many applications from advanced nuclear reactors to aerospace and automotive industries require materials to operate in extreme environments. In search of new materials that can operate in these extremes, the present work explores this space whereby: (1) guided by atomistic and thermodynamic calculations we utilize thin film combinatorial synthesis to rapidly explore mechanical and thermal properties in a broad range of refractory compositionally complex alloys, and (2) observe transformation induced plasticity via oscillations in the thin film nanoindentation load depth curves that are attributed to, (3) a stress-induced HCP-to-BCC phase transformation in the resulting nanogranular microstructure, which to our knowledge has not been observed before in this alloy system; and finally (4) scale to bulk materials to compare the thin film results.

36 MATERIALS SCIENCE↗

Direct Prediction of Phonon Density of States With Euclidean Neural Networks

Abstract Machine learning has demonstrated great power in materials design, discovery, and property prediction. However, despite the success of machine learning in predicting discrete properties, challenges remain for continuous property prediction. The challenge is aggravated in crystalline solids due to crystallographic symmetry considerations and data scarcity. Here, the direct prediction of phonon density‐of‐states (DOS) is demonstrated using only atomic species and positions as input. Euclidean neural networks are applied, which by construction are equivariant to 3D rotations, translations, and inversion and thereby capture full crystal symmetry, and achieve high‐quality prediction using a small training set of examples with over 64 atom types. The predictive model reproduces key features of experimental data and even generalizes to materials with unseen elements, and is naturally suited to efficiently predict alloy systems without additional computational cost. The potential of the network is demonstrated by predicting a broad number of high phononic specific heat capacity materials. The work indicates an efficient approach to explore materials' phonon structure, and can further enable rapid screening for high‐performance thermal storage materials and phonon‐mediated superconductors.

97 MATHEMATICS AND COMPUTING↗

Exploring the Microstructure-Property Relationship of Mg-Al-Mn alloys enhanced via Friction Stir Processing

Friction Stir Processing (FSP) is a solid-state thermomechanical processing technique that enables local grain refinement, densification, and homogenization of microstructure in metallic components. Here, FSP is applied to thin sheets of high-pressure die cast AM60 to address the porosity and heterogeneities inherent to the casting process. In this work, microstructure characterization is correlated to improvements in the static mechanical properties of the Mg-Al-Mn alloy system at various FSP processing conditions. Notably, there is a significant increase in the ductility and ultimate tensile stress of system following FSP. The dominant deformation mechanisms for the as-cast material and the FSP material are investigated. Finally, the fatigue life improvement is correlated to microstructure modifications that may lead to distinct behavior in crack initiation and crack propagation for the as-cast and FSP material.

Garcia, David↗

Smaller and faster: a review of conventional and nanocalorimetry techniques for determining thermophysical properties of nuclear materials

Thermal analysis of nuclear materials is critical for the advancement of nuclear technology. The heat effects associated with heat capacity, phase transformation, and radiation damage can be measured with conventional calorimeters. However, conventional calorimetric techniques are often restricted in terms of heating rate and sample mass, especially when studying the limited amounts of materials subject to extreme conditions. In this review, we summarize conventional calorimetric studies of critical thermophysical and thermochemical properties of pure actinide metals (U, Np, Am, Pu), fast reactor metallic fuel alloy systems (U–Zr, U–Pu–Zr, Pu–U, Pu–Zr), and actinide oxides that are primary constituents or transmutation products in light water reactor fuel rods (U–O, Np–O, Am–O, Pu–O, Pu–U–O). Adiabatic and drop calorimetry have been the primary techniques used for these studies, however the development of fast scanning calorimetry using micro-electro-mechanical-based systems allows determination of thermodynamic properties from smaller sample masses. We report recent investigations that leverage the fast heating rates of nanocalorimetry by itself or combined with other characterization techniques. Furthermore, we then discuss opportunities for nanocalorimetry to provide solutions to some of the technical challenges inherent in thermal analysis of nuclear materials, namely a reduction in sample activity, emulating heating transients, investigation of phase evolution in irradiated samples, and characterization of radiation damage evolution. Nanocalorimetry has the potential to significantly advance the understanding of thermophysical properties in nuclear materials and thus accelerate the development of nuclear technology.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Nanoscale Perspectives of Metal Degradation via In Situ Atom Probe Tomography

Abstract We report a unique in situ instrument development effort dedicated to studying gas/solid interactions relevant to heterogeneous catalysis and early stages of oxidation of materials via atom probe tomography and microscopy (APM). An in situ reactor cell, similar in concept to other reports, has been developed to expose nanoscale volumes of material to reactive gas environments, in which temperature, pressure, and gas chemistry are well controlled. We demonstrate that the combination of this reactor cell with APM techniques can aid in building a better mechanistic understanding of resultant composition and surface and subsurface structure changes accompanying gas/surface reactions in metal and metal alloy systems through a series of case studies: O 2 /Rh, O 2 /Co, and O 2 /Zircaloy-4. In addition, the basis of a novel operando mode of analysis within an atom probe instrument is also reported. The work presented here supports the implementation of APM techniques dedicated to atomic to near-atomically resolved gas/surface interaction studies of materials broadly relevant to heterogeneous catalysis and oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Research on Bulk-metallic Glasses and High-entropy Alloys in Peter K. Liaw’s Group and with His Colleagues

Bulk-metallic glasses (BMGs) and high-entropy alloys (HEAs) have attracted extensive attention in the field of metallic materials research for several decades due to their extraordinary properties. Many scientists and researchers have significantly contributed to developing new classes of metallic alloys, such as BMGs and HEAs, for various applications. Liaw’s group and his colleagues have focused on the fundamental understanding of unique features, structures, and properties in BMGs and HEAs as well as the development of new types of metallic materials. Here, we summarized the research work of Liaw’s group and his colleagues by reviewing relevant papers. The goal is to provide an understanding of the current research progression in BMGs and HEAs while further encouraging young and junior researchers to be involved in the field of structural materials research pertaining to these classes of exotic alloy systems.

36 MATERIALS SCIENCE↗

A Review: Microstructural and Phase Evolution in Alloys during Extended Plastic Deformation

Materials in service and during processing are often subjected to plastic deformation. For multi-phase metallic alloys, simple geometric models and atomistic simulations suggest that two distinctive regimes in these materials’ evolution during deformation exist. At low strains, evolutions are often dominated by the kinetic roughening of interfaces, which results from the superdiffusive transport of matter in sheared crystals. Furthermore, at high strains and temperatures where thermal diffusion is sluggish, on the other hand, shearing- induced forced atomic mixing dominates these evolutions, resulting in significantly enhanced solubility. Distinguishing these two regimes is shown to provide a convenient framework for rationalizing and analyzing recent experiments and simulations on wear of layered structures in the low strain-regime and nonequilibrium phase co-existence and self-organization in highly immiscible or reactive alloy systems in the high-strain regime.

36 MATERIALS SCIENCE↗

Kinetics and evolution of solid-state metal dealloying in thin films with multimodal analysis

Thin-film solid-state metal dealloying (thin-film SSMD) is an emerging technique that uses self-organization to design nanostructured thin films. The resulting 3D bicontinuous nanostructures are promising for a wide range of applications, such as catalysis and energy storage. In this work, we prepared thin films by SSMD using Ti-Cu as the parent alloy and Mg as the solvent. Using a multimodal approach, we combined synchrotron X-ray spectroscopy, diffraction, and high-resolution electron-based spectroscopy and imaging to study their morphological, structural, and chemical evolution. The processing-structure relationship was analyzed as a function of parent alloy composition and dealloying temperature and time. Morphological transitions from globular, to lamellar, to bicontinuous structures, in conjunction with a ligament size evolution, were identified as functions of the parent alloy composition. The dealloying rate increased with increasing concentration of interdiffusing elements (dissolving component) in the parent alloy. The parting limit, a dealloying compositional threshold, was systematically analyzed and determined to be 30%–40%. The order of crystalline phase formation is CuMg 2 , Cu 2 Mg, and Ti; the Ti phase first shows self-reorganization during dealloying, separate from the crystallization process. The coarsening in thin-film SSMD was identified and not entirely self-similar; in addition to the increase of ligament size over time, the formation of larger globular ligaments were also observed. This work furthers our fundamental understanding of thin-film SSMD and nanostructured thin-film design, where the thermodynamic and kinetic effects differ from the bulk counterparts. The fact that dealloying and diffusion outpaces the crystallization and new phase formation also offers opportunities to utilize thin-film SSMD in certain alloy systems in which deleterious intermetallic phases need to be suppressed, that may not be possible in the bulk geometry.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Analytical gradient-based optimization of CALPHAD model parameters

The calibration of CALPHAD (CALculation of PHAse Diagrams) models involves the solution of a very challenging high-dimensional multiobjective optimization problem. Traditional approaches to parameter fitting predominantly rely on gradient-free methods, which while robust, are computationally inefficient and often scale poorly with model complexity. In this work, we introduce and demonstrate a generalizable framework for analytic gradient-based optimization of the parameters of the CALPHAD model enabled by the recently formalized Jansson derivative technique. This method allows for efficient evaluation of gradients of thermodynamic properties at equilibrium with respect to model parameters, even in the presence of arbitrarily complex internal degrees of freedom. Leveraging these semi-analytic gradients, we employ the conjugate gradient (CG) method to optimize thermodynamic model parameters for four binary alloy systems: Cu-Mg, Fe-Ni, Cr-Ni, and Cr-Fe. Across all systems, CG achieves comparable or superior optimality relative to Bayesian ensemble Markov Chain Monte Carlo (MCMC) with improvements in computational efficiency ranging from one to three orders of magnitude. Furthermore, our results establish a new paradigm for CALPHAD assessments in which high fidelity data-rich model calibration becomes tractable using deterministic gradient-informed algorithms.

CALPHAD↗

Machine learning elastic constants of multi-component alloys

The present manuscript explores application of machine learning methods for determining elastic constants and other derived mechanical properties of multi-component alloys. Here, a number of machine learning models, including linear regression, neural network and random forest based models, are trained and tested on a dataset of binary alloys generated using density functional theory (DFT) calculations and spanning over a large number of elemental species in the periodic table. Starting with a wide range of simple and easily accessible compositionally-averaged elemental features, a correlation-based feature selection strategy was used to systematically down-select a set of most relevant features towards the prediction of the elasticity tensor components. The true predictive performance and the associated uncertainties of the models were established by testing on unseen data and bootstrapping, respectively. A single and pair-wise feature partial dependence analysis was performed to visualize the average property trends in the multi-dimensional feature space in order to further understand the achieved predictive performance. The utility of the trained model is further demonstrated by obtaining sufficiently accurate yet highly efficient approximations for bulk modulus, Young’s modulus, shear modulus and Poisson’s ratio for alloys beyond the binary space (i.e., two-component alloys) on which the model was originally trained. More importantly, we test and validate the predictive performance of the developed model directly against the experimentally measured elastic constants of technologically relevant multi-component alloys (such as, Ni- and Ti-based alloys). Finally, utility of such a data-enabled route is demonstrated by predicting the possible range of various elastic properties for vast composition space available within the five component Ni-Cr-Fe-Mo-W alloy system in a high-throughput manner.

36 MATERIALS SCIENCE↗

The role of Si in determining the stability of the θ; precipitate in Al-Cu-Mn-Zr alloys

Precipitate-strengthened Al-Cu-Mn-Zr (ACMZ) alloys demonstrate improved microstructural stability compared to conventional Al-Cu alloys. Si is typically considered an impurity in these alloys, but a systematic analysis of ACMZ alloys with a range of Si levels revealed that there is a Si content range (~0.05 wt. % < Si < ~0.10 wt. %) for achieving optimal high temperature microstructural stability. A combination of hardness testing, scanning electron microscopy, and atom probe tomography has been used to understand the relationship between Si content, aging response, and thermal stability in ACMZ alloys. It is shown that the optimum Si content range corresponds to a reduced as-aged hardness, but a greater hardness value retained by the alloy after thermal exposure to 350 °C for 200 hours. A mechanism is proposed in which optimum Si levels reduce the number density of nucleation sites for θ' precipitates, resulting in larger precipitates that, on average, provide a reduced as-aged strength but are more coarsening resistant. This inherent θ' coarsening resistance allows more time for slow-diffusing Mn and Zr to reach the θ' interface and further stabilize the precipitates. Designing the optimal as-aged microstructure for improved thermal stability of the alloy by controlling impurity levels is a concept that has implications beyond the investigated Al-Cu alloy system.

36 MATERIALS SCIENCE↗

Heterogeneous phase transformation pathways in additively manufactured Al-Ce-Mn alloys

Heat treatment of additively manufactured Al-Ce based multicomponent alloys leads to complex microstructure evolution. In this research, the ability to extend the phase transformation theories involving nucleation of a product phase from a heterogeneous multi-phase microstructure typical to that of additively manufactured samples is explored. The Al-10Ce-8Mn (wt%) was used as a model alloy system. Under additive manufacturing conditions different solidification microstructures were obtained due to spatial and temporal variations of thermal gradients (G) and liquid-solid interface velocities (R) within a given melt pool. Near the melt pool boundary (high G and low R, referred as MPB region), initially, Al 20 Mn 2 Ce forms from the liquid followed by a eutectic of FCC Al and Al 11 Ce 3 . In the melt pool interiors (low G and high R referred as ES region) a eutectic structure between FCC Al and Al 20 Mn 2 Ce is observed. During subsequent heat treatments, the MPB and ES regions transform into different sets of microstructures. In the MPB region, a fine globular microstructure containing FCC Al, Al 11 Ce 3 , Al 6 Mn, and Al 12 Mn results from the decomposition of Al 20 Mn 2 Ce. In the ES region a faceted Al 51 Mn 7 Ce 4 plate phase results from the decomposition of Al 20 Mn 2 Ce. The formation of the Al 51 Mn 7 Ce 4 phase within the eutectic microstructure at the boundaries of FCC Al and Al 20 Mn 2 Ce has not been reported in the literature. Further, these two distinct phase transformation pathways are rationalized based on the role of driving force on the nucleation of (Al 6 Mn) and/or metastable intermetallic (Al 51 Mn 7 Ce 4 ) phases at the interface of aluminum (FCC) and the non-equilibrium intermetallic (Al 20 Mn 2 Ce) phases.

36 MATERIALS SCIENCE↗

A process optimization framework for laser direct energy deposition: Densification, microstructure, and mechanical properties of an Fe-Cr alloy

Laser Direct Energy Deposition (DED) is a metal additive manufacturing technique with the ability to fabricate large and complex parts through deposition of metal powders. However, achieving high-density parts and targeted build heights using DED can be challenging due to the large number of highly sensitive process variables. This work proposes a robust fabrication parameter optimization framework to generate process maps for primary parameters in DED, including laser power, scan speed, mass flow rate, hatch spacing, and layer height. Simple single-track experiments were utilized to map out the parameter space, and a combination of geometric criteria for hatch spacing and layer height were proposed to determine parameter sets that achieve both targeted build heights and mitigate porosity formation. Using this framework, specimens with >99 % density and consistent mechanical properties were successfully fabricated over a wide range of process parameters for an Fe-9wt.%Cr (Fe9Cr) alloy, a surrogate for radiation damage-resistant reduced activation ferritic/martensitic (RAFM) steels. Processing these materials using DED is of particular interest in the development of plasma facing components for nuclear fusion applications. The microstructure and mechanical properties of as-printed Fe9Cr were characterized using optical and electron microscopy, X-ray diffraction, and uniaxial tensile tests. As-printed Fe9Cr displayed ~25 % elongation and ultimate tensile strengths of up to 475 MPa which is comparable to similar wrought alloys. Finally, the proposed framework will allow for accelerated DED parameter optimization for novel alloy systems, as well as open the possibility for local microstructure control while simultaneously mitigating defect formation.

42 ENGINEERING↗

Serrated flow in $\mathrm{NaI:Tl}$ scintillator crystals

We report the serrated-flow behavior is an important phenomenon that unveils material-deformation mechanisms, as reported for various kinds of materials. NaI doped with Tl (NaI:Tl) is unique among scintillation materials in that the structure contains glide planes that are linked to serration behavior. In the present work, single crystals of NaI:Tl were subjected to room-temperature compression experiments at different strain rates. The serrated flow was observed, and complexity and multifractal analyses were performed to analyze the serration behavior. The findings revealed that the strain rate had a pronounced effect on the complexity and multifractality of the serrated flow, similar to what has been found in other alloy systems. The results also indicate that there may be a strong link between the complexity of the serrated flow behavior and the heterogeneity of the underlying dynamics. It is expected that the present work could be a step toward a better understanding of the deformation behavior and forgeability of NaI:Tl single crystals.

36 MATERIALS SCIENCE↗

An Electron Backscatter Diffraction Analysis of Grain Boundary Initiated Discontinuous Precipitation in U-10Mo

The effect of varied thermomechanical processing on discontinuous precipitation (DP) in U-10Mo was investigated, with specific emphasis on understanding the role of grain boundary misorientation in DP. Varied prior homogenization heat treatment and thermomechanical processing resulted in differences in both the fraction of DP and the colony width, and was attributed to variations in the grain boundary misorientation distribution. Regardless of the degree of DP-based transformation, extensive growth of DP colonies was dominant on 30°–45° misorientation boundaries. Interestingly, misorientation histograms of the deformed and annealed specimens suggest the processing steps involved may have inhibited DP colony growth along a small fraction of these high angle boundaries. Large-area electron backscatter diffraction montages coupled with high resolution mapping suggest symmetric {110}-type interfaces may be important considerations for mitigating extensive DP growth in this alloy system.

Discontinuous Precipitation, Uranium, Electron Bac↗

Machine learning bridges local static structure with multiple properties in metallic glasses

A long-standing challenge in the metallic glass (MG) community has been how to quantitatively gauge the influence of the intricate local packing environment on the response (such as the propensity for atomic rearrangement) of the atomic configuration to external stimuli. Here we establish this structure–property relation by representing the complex amorphous structure using a single, flexibility-orientated structural quantity. This structural flexibility (SF) couples to a bona fide structural representation, the pair distribution function (PDF) of individual atoms, through a weighting function that reflects what matters in the static atomic configuration to dynamic responses. Machine learning is used, employing microscopic flexibility volume as the supervisory signal, to establish via direct regression an optimized weighting vector, which is proven robust for all quenching rates, deformation conditions, and different compositions in a given (e.g., Cu x Zr 100-x ) alloy system. Additionally, the SF is evaluated solely from the particle positions (PDF), for any structure variation, from the atomic scale up to sample average. Strong correlations are demonstrated between SF and a broad range of properties, including vibrational, diffusional, as well as elastic and plastic relaxation responses.

36 MATERIALS SCIENCE↗

Simultaneously improved electrical and mechanical performance of hot-extruded bulk scale aluminum-graphene wires

Aluminum-based alloys are highly sought after as lightweight alternatives in electric grid applications. Improving the electrical conductivity of aluminum alloys has the potential to increase the energy efficiency of power transport. Here we used a hot extrusion process to synthesize AA1100 alloy with low-cost reduced graphene oxide nanoparticles to manufacture ultra-conductive aluminum composites in this study. The effects of graphene content on the electrical and mechanical performance of the composites were evaluated. The macroscale AA1100/graphene wires demonstrated a 2.1% enhancement in electrical conductivity at 20 °C, while the ultimate tensile strength increased by 6.1%. A Zener-Hollomon model was used to confirm the in-process exfoliation of the agglomerated graphene nanoparticle feedstock into high electrical conductivity graphene-like flakes during extrusion. They may have provided high-velocity carrier pathways leading to the enhanced electrical performance of the alloy. Transmission electron microscopy at aluminum-graphene interfaces ensures the preclusion of detrimental carbide formation during composite synthesis while confirming the structure graphene-like flakes. The in-process exfoliation provides an economically viable technique to produce bulk scale graphinated aluminum composites for advanced application and can be applied more generally to other alloy systems.

36 MATERIALS SCIENCE↗

Analysis of correlations between intrinsic ductility and electronic density of states in refractory alloys

High entropy alloys (HEAs) correspond to a new and emerging class of materials that allows us to explore a large composition space to tune mechanical strength and thermal stability. Therefore, to design better alloys, it is important to scan the high-dimensional space of chemistry, composition and temperature. Here, to facilitate this search, we present a method to screen intrinsically ductile body centered cubic (BCC) refractory alloys from electronic structure calculations by using the density of states (DOS) at the Fermi level, g(μ F ). This correlation between intrinsic ductility and g(μ F ) is tested by analyzing group V (V, Nb, Ta) and VI (Mo, W) refractory metals, binary alloys, such as W-Nb, W-V, Mo-Nb and Mo-V, and refractory alloys for which experimental stress-strain measurements are available. In addition, we perform a high-throughput exploration of the entire composition space of a recently proposed alloy system, CrMoNbV, and identify compositions that exhibit high intrinsic ductility.

36 MATERIALS SCIENCE↗