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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Crafting Multifunctional Materials with Tailored Mechanical and Magnetic Properties by Solid-State Non-equilibrium Processing

Aluminum matrix composites hold promise for creating lightweight structural components with multifunctional properties. Nonetheless, achieving desired magnetic or electrical characteristics without compromising their fundamental mechanical properties presents a significant challenge. Here, in this study, we explore mechanical stir-based extrusion as a solid-state metalworking technique to develop fine-grained microstructures and highly refined metallic composites. Our study focuses on creating a SmCo 5 -reinforced aluminum matrix composite using solid stir extrusion (SSE) and assessing its microstructure, mechanical, and magnetic properties through a comprehensive suite of characterization tools, including x-ray diffraction, electron microscopy, and magnetometry. Our findings reveal that incorporating a small amount (3.76 wt.%) of SmCo 5 phase in a non-heat-treatable, non-magnetic aluminum alloy via SSE yields a composite that exhibits good hard magnetic characteristics with a large coercivity (H ci = 13.5 kOe) and improved mechanical properties. This study underscores non-equilibrium processing via solid-state high-speed stirring as a compelling method for crafting multifunctional materials with tailored mechanical and magnetic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Dynamic re-equilibration controlled multi-step transformations in (Mn, Fe) 2 (P, Si) alloys

In (Mn, Fe) 2 (P, Si) alloys crystallographic first-order phase transformations enable strong coupling of magnetic and entropic properties, potentially leading to high-efficiency energy generation and refrigeration applications. Although hysteresis losses that limit these applications can be reduced through careful control of alloy composition, compositional tuning can also unfavorably influence transformation temperatures and magnetocaloric coupling strength. Hence, exploration of additional processing variables enabling independent control of transformation properties is crucial. In this work, we investigate the role of thermal history as an additional processing variable, exploiting thermally-activated mechanisms to control properties of non-diffusive transformations in (Mn, Fe) 2 (P, Si) alloys. In so doing, we report an unusual transformation-splitting phenomenon following annealing at intermediate times, where a single well-defined magneto-structural transformation evolves towards a multi-step transformation with individual steps occurring at multiple distinct temperatures. Here, on longer annealing at the same temperatures, single-step transformation behavior is recovered. Through additional magnetic and crystallographic characterization, we show that the thermal history-controlled multi-step behavior results from sluggish thermally-activated diffusion. The two-step transformation corresponds to non-equilibrium bimodal composition distributions in the transforming phase, and these develop through a dynamic re-equilibration process as the alloy passes relatively slowly between different thermal equilibria. Together, these results suggest that thermal history primarily controls the transformation properties of (Mn, Fe) 2 (P, Si) alloys indirectly through the composition of one or more transforming phases. Additional investigations are needed to develop thermal history processing for decoupling hysteresis control from other transformation properties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Mirostructure Characterization of Friction Consolidated Copper-Nickel using a Machine Learning Approach: Developing Process to Microstructure Associations

Friction consolidation (FC) is a solid phase processing approach where discrete material forms such as powders, chips, nuggets, etc. are densified via shear deformation. The precursors are placed in a billet container and brought in contact with a rotating tool that applying the desirable amount of normal force. Under the combined action of the rotation and normal pressure, the discrete precursor is consolidated through porosity reduction and shear deformation. FC is increasingly being studied as an attractive approach to manufacturing fully dense parts from powder forms owing to its ability to mix, alloy and consolidate difficult-to-process precursors in minimal number of process steps. Material consolidation and deformation in shear consolidation processes have been studied extensively previously for different material combinations previously. However, despite the extensive research in this area, understanding of the mechanistic processes in pore consolidation, deformation-induced mixing and material solubility during FC is still evolving. Material development using solid phase processing approaches such as FC is often performed based on research experience/education, which can be biased. Conventional analysis and simulation tools in this area tend to be successful only when material thermodynamic pathways and microstructural evolution sequences resulting from processing are clearly defined or known. They are not as effective for emerging advanced manufacturing technologies where material evolution pathways are not well established. The ability to predict optimal process parameters based on material chemistry and bulk properties is essential to accelerate materials design and processing, as are an understanding of the relevant structure-processing-property relationships. These structure-processing-property-performance relationships are at the core of materials science research. Microstructure characterization provides the link to these four core areas, often through visualizing material microstructure using imaging techniques. However, linking microstructure image data (i.e., micrographs) to variables of interest (e.g., processing parameters, material chemistry) in a reproducible, generalizable, and quantitative manner is a significant challenge. Typically, quantitatively linking image data to processing history relies on significant domain knowledge and manual or subject matter expert (SME)-heuristic based image analysis. Such an approach to image analysis has the potential to be biased, inefficient, and difficult to replicate.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Embedded Aluminum Nitride Sensors for Advanced Reactors

This project aims to manipulate the of growth of aluminum nitride (AlN) inclusions in an iron-chromium-aluminum (FeCrAl) alloy, using the principle of powder metallurgy and heat treatment methods. to promote the formation of AlN phase within FeCrAl for embedded sensing. This effort seeks to fill in a gap with respect to robust sensor hardware for ubiquitous structural health monitoring of advanced nuclear reactors. A systematic evaluation of various solid-state methods will be performed to understand the influence of process conditions on AlN growth and to promote the growth of desirable AlN phase. Fabricated specimens will be analyzed to investigate the AlN structures that are formed using a suite of tools to characterize the concentration, morphology, and distribution of AlN within the FeCrAl substrate.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Emergence of liquid following laser melting of gold thin films

X-ray structural science is undergoing a revolution driven by the emergence of X-ray Free-electron Laser (XFEL) facilities. The structures of crystalline solids can now be studied on the picosecond time scale relevant to phonons, atomic vibrations which travel at acoustic velocities. In the work presented here, X-ray diffuse scattering is employed to characterize the time dependence of the liquid phase emerging from femtosecond laser-induced melting of polycrystalline gold thin films using an XFEL. In a previous analysis of Bragg peak profiles, we showed the supersonic disappearance of the solid phase and presented a model of pumped hot electrons carrying energy from the gold surface to scatter at internal grain boundaries. This generates melt fronts propagating relatively slowly into the crystal grains. By conversion of diffuse scattering to a partial X-ray pair distribution function, we demonstrate that it has the characteristic shape obtained by Fourier transformation of the measured F ( Q ). The diffuse signal fraction increases with a characteristic rise-time of 13 ps, roughly independent of the incident pump fluence and consequent final liquid fraction. This suggests the role of further melt-front nucleation processes beyond grain boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Strengthening Mechanisms and Deformation Behavior of Industrially-Cast and Lab-Cast Dual-Phase High Entropy Alloy

An iron-rich high entropy alloy Al 0.65 CoCrFe 2 Ni comprising of both FCC and BCC phases was designed and fabricated using induction melting at a large industrial scale and suction casting at a small lab scale. Spinodally decomposed interdendritic regions were uniformly distributed in the industrially melted alloy, and a finer dendritic structure with smaller sized spinodal structures was observed in the alloy suction cast at lab scale. The suction cast alloy fabricated at the lab scale exhibited significantly higher compressive yield strength compared to the industrially cast alloy. The relative strengthening contributions in the alloys due to solid solution, grain boundary, dislocation interactions and interphase boundary were analyzed. Dislocation hardening was the major contributor responsible for the higher strength of the SC alloy. The deformation behavior in the alloys was examined with the help of orientation image mapping. Finally, intense slip band formation at large strains in the industrially melted alloy indicates that cold working can be an effective technique to enhance the strength of the dual-phase high entropy alloy processed at a large scale.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Sulfate reduction accelerates groundwater arsenic contamination even in aquifers with abundant iron oxides

Groundwater contamination by geogenic arsenic is a global problem affecting nearly 200 million people. In South and Southeast Asia, a cost-effective mitigation strategy is to use oxidized low-arsenic aquifers rather than reduced high-arsenic aquifers. Aquifers with abundant oxidized iron minerals are presumably safeguarded against immediate arsenic contamination, due to strong sorption of arsenic onto iron minerals. However, preferential pumping of low-arsenic aquifers can destabilize the boundaries between these aquifers, pulling high-arsenic water into low-arsenic aquifers. We investigate this scenario in a hybrid field-column experiment in Bangladesh where naturally high-arsenic groundwater is pumped through sediment cores from a low-arsenic aquifer, and detailed aqueous and solid-phase measurements are used to constrain reactive transport modelling. Here we show that elevated groundwater arsenic concentrations are induced by sulfate reduction and the predicted formation of highly mobile, poorly sorbing thioarsenic species. Furthermore, this process suggests that contamination of currently pristine aquifers with arsenic can occur up to over 1.5 times faster than previously thought, leading to a deterioration of urgently needed water resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

High-Accuracy Semiempirical Quantum Models Based on a Minimal Training Set

A great need exists for computationally efficient quantum simulation approaches that can achieve an accuracy similar to high-level theories at a fraction of the computational cost. In this regard, we have leveraged a machine-learned interaction potential based on Chebyshev polynomials to improve density functional tight binding (DFTB) models for organic materials. The benefit of our approach is two-fold: (1) many-body interactions can be corrected for in a systematic and rapidly tunable process, and (2) high-level quantum accuracy for a broad range of compounds can be achieved with ~0.3% of data required for one advanced deep learning potential. Our model exhibits both transferability and extensibility through comparison to quantum chemical results for organic clusters, solid carbon phases, and molecular crystal phase stability rankings. Overall, our efforts thus allow for high-throughput physical and chemical predictions with up to coupled-cluster accuracy for systems that are computationally intractable with standard approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Temperature-Controlled Reversible Formation and Phase Transformation of 3D Nanocrystal Superlattices Through In Situ Small-Angle X-ray Scattering

For decades, the spontaneous organization of nanocrystals into superlattices has captivated the scientific community. However, achieving direct control over the formation of the superlattice and its phase transformations has proven to be a grand challenge, often resulting in the generation of multiple symmetries under the same experimental conditions. Here, we achieve direct control over the formation of the superlattice and its phase transformations by modulating the thermal energy of a nanocrystal dispersion without relying on solvent evaporation. In this study, we follow the temperature-dependent dynamics of the self-assembly process using synchrotron-based small-angle X-ray scattering. When cooled below –24.5 °C, lead sulfide nanocrystals form micrometer-sized three-dimensional phase-pure body-centered cubic superlattices. When cooled below –35.1 °C, these superlattices undergo a collective diffusionless phase transformation that yields denser body-centered tetragonal phases. These structural changes can be reversed by increasing the temperature of the dispersion and may lead to the direct modulation of the optical properties of these artificial solids.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Polymorphism of garnet solid electrolytes and its implications for grain-level chemo-mechanics

Understanding and mitigating filament formation, short-circuit and solid electrolyte fracture is necessary for advanced all-solid-state batteries. Here, we employ a coupled far-field high-energy diffraction microscopy and tomography approach for assessing the chemo-mechanical behaviour for dense, polycrystalline garnet (Li 7 La 3 Zr 2 O 12 ) solid electrolytes with grain-level resolution. In situ monitoring of grain-level stress responses reveals that the failure mechanism is stochastic and affected by local microstructural heterogeneity. In this work, coupling high-energy X-ray diffraction and far-field high-energy diffraction microscopy measurements reveals the presence of phase heterogeneity that can alter local chemo-mechanics within the bulk solid electrolyte. These local regions are proposed to be regions with the presence of a cubic polymorph of LLZO, potentially arising from local dopant concentration variation. The coupled tomography and FF-HEDM experiments are combined with transport and mechanics modelling to illustrate the degradation of polycrystalline garnet solid electrolytes. The results showcase the pathways for processing high-performing solid-state batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamic compression of Ce and Pr with millisecond time-resolved X-ray diffraction

Abstract Both cerium (Ce) and praseodymium (Pr) undergo a volume collapse transition under compression that originate from similar electronic mechanisms. Yet the outcome could not be more different. In the case of Ce with one affected 4f electron the volume collapse leaves the crystal symmetry intact, whereas for Pr with two 4f electrons the crystal symmetry changes from a distorted face centered cubic structure to a lower symmetry orthorhombic structure. In this paper, we present a study of the effect of strain/compression rate spanning nearly 4 orders of magnitude on the volume collapse phase transitions in Ce and Pr. These dynamic compression experiments in a diamond anvil cell also reveal kinetic differences between the phase transformations observed in these two materials. The transition cannot be overdriven in pressure in Ce, which indicates a fast kinetic process, whereas fast compression rates in Pr lead to a shift of the phase boundary to higher pressures, pointing to slower kinetics possibly due to the realization of a new crystal structure.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Wetland Soil Characterization and Methane Production Impacted by Nickel Addition, Argonne and Tims Branch Wetlands, September and October 2020

Abstract:Freshwater wetland soils are foci of biogeochemical cycling as they serve as key sources of methane to the atmosphere. An array of metalloenzymes is essential to anaerobic microbial carbon transformations. Nickel is notably recognized as playing key roles in the enzymatic pathways of methanogenesis. Low availability of trace metals limits microbial element cycling in laboratory studies, but the occurrence of such limitations in natural subsurface aquatic systems is poorly understood. Microcosm incubation studies were carried out using two distinct wetland soils, one from a marsh wetland and the second from a riparian wetland, to explore the effect of dissolved Ni concentrations on methane production. Data are provided for wetland soil characterization and soil incubation experiments using materials from marsh wetlands at Argonne National Laboratory and riparian wetlands in the Tims Branch watershed at Savannah River National Laboratory. The characterization data consists soil carbon, nitrogen, sulfur, and iron contents plus as well as the solid-phase concentrations of copper, nickel, cobalt, and zinc, bioessential trace metals that may limits microbial metabolic process if they have low availability. The data for the soil incubation experiments include fluid pH, fluid dissolved trace metal concentrations, and cumulative methane production. Three soil incubations are reported: marsh wetland soil with increasing nickel addition, marsh wetland soil in sulfate-free water with increasing nickel addition, and riparian wetland soil with increasing nickel addition. All data are provided in text-based CSV format with header sections indicating the data contained in each file and the corresponding units. Note that "u" is used in place of Greek lower case mu to indicate the micro prefix on units. A Table of Contents file (Yan_Soil_Incubations_2020_TOC.txt) provides an index for the data contained in the individual files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mapping causal patterns in crystalline solids

The evolution of the atomic structures of the combinatorial library of Sm-substituted thin film BiFeO 3 along the phase transition boundary from the ferroelectric rhombohedral phase to the non-ferroelectric orthorhombic phase is explored using scanning transmission electron microscopy. Localized properties, including polarization, lattice parameter, and chemical composition, are parameterized from atomic-scale imaging, and their causal relationships are reconstructed using a linear non-Gaussian acyclic model. This approach is further extended to explore the spatial variability of the causal coupling using the sliding window transform method, which revealed that new causal relationships emerged at both the expected locations, such as domain walls and interfaces, and at additional regions forming clusters in the vicinity of the walls or spatially distributed features. While the exact physical origins of these relationships are unclear, they likely represent nanophase-separated regions in the morphotropic phase boundaries. Overall, we posit that an in-depth understanding of complex disordered materials away from thermodynamic equilibrium necessitates understanding not only the generative processes that can lead to observed microscopic states but also the causal links between multiple interacting subsystems.

Causal inference↗
DOE OSTI2023

Data and scripts associated with a manuscript investigating impacts of solid phase extraction on freshwater organic matter optical signatures and mass spectrometry pairing

This data package is associated with the publication “Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high-resolution mass spectrometry data in a freshwater system” submitted to “Limnology and Oceanography: Methods.” This data is an extension of the River Corridor and Watershed Biogeochemistry SFA’s Spatial Study 2021 (https://doi.org/10.15485/1898914). Other associated data and field metadata can be found at the link provided. The goal of this manuscript is to assess the impact of solid phase extraction (SPE) on the ability to pair ultra-high resolution mass spectrometry data collected from SPE extracts with optical properties collected on ambient stream samples. Forty-seven samples collected from within the Yakima River Basin, Washington were analyzed dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), absorbance, and fluorescence. Samples were subsequently concentrated with SPE and reanalyzed for each measurement. The extraction efficiency for the DOC and common optical indices were calculated. In addition, SPE samples were subject to ultra-high resolution mass spectrometry and compared with the ambient and SPE generated optical data. Finally, in addition to this cross-platform inter-comparison, we further performed and intra-comparison among the high-resolution mass spectrometry data to determine the impact of sample preparation on the interpretability of results. Here, the SPE samples were prepared at 40 milligrams per liter (mg/L) based on the known DOC extraction efficiency of the samples (ranging from ~30 to ~75%) compared to the common practice of assuming the DOC extraction efficiency of freshwater samples at 60%. This data package folder consists of one main data folder with one subfolder (Data_Input). The main data folder contains (1) readme; (2) data dictionary (dd); (3) file-level metadata (flmd); (4) final data summary output from processing script; and (5) the processing script. The R-markdown processing script (SPE_Manuscript_Rmarkdown_Data_Package.rmd) contains all code needed to reproduce manuscript statistics and figures (with the exception of that stated below). The Data_Input folder has two subfolders: (1) FTICR and (2) Optics. Additionally, the Data_Input folder contains dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data (SPS_NPOC_Summary.csv) and relevant supporting Solid Phase Extraction Volume information (SPS_SPE_Volumes.csv). Methods information for the optical and FTICR data is embedded in the header rows of SPS_EEMs_Methods.csv and SPS_FTICR_Methods.csv, respectively. In addition, the data dictionary (SPS_SPE_dd.csv), file level metadata (SPS_SPE_flmd.csv), and methods codes (SPS_SPE_Methods_codes.csv) are provided. The FTICR subfolder contains all raw FTICR data as well as instructions for processing. In addition, post processed FTICR molecular information (Processed_FTICRMS_Mol.csv) and sample data (Processed_FTICRMS_Data.csv) is provided that can be directly read into R with the associated R-markdown file. The Optics subfolder contains all Absorbance and Fluorescence Spectra. Fluorescence spectra have been blank corrected, inner filter corrected, and undergone scatter removal. In addition, this folder contains Matlab code used to make a portion of Figure 1 within the manuscript, derive various spectral parameters used within the manuscript, and used for parallel factor analysis (PARAFAC) modeling. Spectral indices (SPS_SpectralIndices.csv) and PARAFAC outputs (SPS_PARAFAC_Model_Loadings.csv and SPS_PARAFAC_Sample_Scores.csv) are directly read into the associated R-markdown file. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Predictive Chemical Kinetic Modeling: Where We Succeed, Where We Struggle, and What Comes Next

Chemical kinetic modeling plays a foundational role in fields ranging from energy to environmental science, pharmaceuticals, and advanced materials. The past two decades have seen remarkable progress, particularly in modeling gas-phase reactions for thermochemical processes, leading to impactful industrial applications such as steam cracking and air quality management. However, new challenges are emerging. The successful development of systematic methodologies for the description of gas-phase kinetics opens the possibility to apply the same approach to the study of more challenging systems. Here, we review recent advances, including ab initio transition state theory-based master equation estimation of elementary rates, automated mechanism generation, machine-learning-assisted kinetics, and uncertainty quantification, and discuss the advances needed to apply the same methodological approach in areas such as heterogeneous catalysis, electrochemistry, liquid-phase and solid-state reactivity, and multiscale model integration. We advocate for the development of targeted tools, especially methods that go beyond empirical tuning toward first-principles-based predictions. We highlight the need for accessible software and AIaugmented workflows to democratize modeling for industry and academia alike. In this perspective, we call attention to not only what has worked but also what remains unsolved, advocating to avoid overemphasizing successes in scientific works at the expense of realism. The next decade should focus on predictive capability, physical accuracy, and community infrastructure (e.g., databases and services) to enable innovation across diverse fields. We argue that kinetic modeling, properly equipped, can accelerate discovery far beyond its traditional domains.

ab initio calculations↗
DOE OSTI2021

Predicting phase transformation kinetics during metal additive manufacturing using non-isothermal Johnson-Mehl-Avrami models: Application to Inconel 718 and Ti-6Al-4V

Here, a computational model was developed to predict solid-state phase transformation kinetics within mechanical parts during metal additive manufacturing processes. This model is a modified version of the Johnson-Mehl-Avrami model for non-isothermal phase transformations that can be applied to various material systems undergoing solid-state phase transformations. Using the thermal history of an additive manufacturing fabricated mechanical part, along with the necessary thermodynamic data and kinetic information as inputs, the model outputs the history of phase fraction evolution during the build process. The model was applied to an Inconel 718 part built by powder bed fusion and a Ti-6Al-4V part built by directed energy deposition. Microstructure characterization and mechanical testing were performed for the validation of the model.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Thermo-mechanical behavior of hypoeutectic Ni-Y-Zr alloys

Microstructure refinement and optimized alloying can improve metallic alloy performance: stable nanocrystalline (NC) alloys with immiscible second phases, e.g., Cu-Ta, are stronger than unstable NC alloys and their coarse-grained (CG) counterparts, but higher melting point matrices are needed. Hypoeutectic, CG Ni-Y-Zr alloys were produced via arc-melting to explore their potential as high-performance materials. Microstructures were studied to determine phases present, local composition and length scales, while heat treatments allowed investigating microstructural stability. Alloys had a stable, hierarchical microstructure with ~250 nm ultrafine eutectic, ~10 µm dendritic arm spacing and ~1 mm grain size. Hardness and uniaxial compression tests revealed that mechanical properties of Ni-0.5Y-1.8Zr (in wt%) were comparable to Inconel 617 despite the small alloying additions, due to its hierarchical microstructure. Here, uniaxial compression at 600 °C showed that ternary alloys outperformed Ni-Zr and Ni-Y binary alloys in flow stress and hardening rates, which indicates that the Ni 17 Y 2 phase was an effective reinforcement for the eutectic, which supplemented the matrix hardening due to increased solubility of Zr. Results suggest that ternary Ni-Y-Zr alloys hold significant promise for high temperature applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Direct-Write Printing Copper–Nickel (Cu/Ni) Alloy with Controlled Composition from a Single Electrolyte Using Co-Electrodeposition

Although various processes for metal printing at the micro- and mesoscale have been demonstrated, printing functional devices such as thermocouples, thermopiles, and heat flux sensors that function based on interfaces between an alloy and another alloy/metal demands processes for printing alloys. Furthermore, a high-quality and crystalline alloy is required for acceptable function of these devices. This article reports for the first time co-electrodeposition-based printing of single-phase solid solution nanocrystalline copper/nickel (Cu/Ni) alloy with various controllable compositions (Cu100Ni0 to Cu19Ni81) from a single electrolyte. Additionally, the printed alloy is nanocrystalline (<35 nm), continuous, and dense with no apparent porosity, with remarkable mechanical and magnetic properties, without any postprocessing annealing such as heat treatment. In addition, a functional thermocouple fabricated using this process is demonstrated. Such a process can not only be used for fabrication of functional devices, it may also facilitate fundamental studies on alloys by printing a continuous library of alloy composition for material characterization.

36 MATERIALS SCIENCE↗