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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Grain boundary structure search by using an evolutionary algorithm with effective mutation methods

Grain boundaries (GBs) accommodate the misorientation between adjacent grains in a polycrystalline material. GBs are geometrically described by the macroscopic and microscopic degrees of freedom. Besides, at the atomistic level, GBs exhibit complicated behaviors under varying thermodynamic conditions. The complexity of atomistic GB structures demands stochastic searching for possible states. The effectiveness of stochastic search methods relies on techniques to recreate and select atomistic structures. In this work, we developed a new mutation operator that can induce direct and collective atomistic structure changes to boost the search efficiency of exploring GB structures with evolutionary algorithms (EA). We implemented the mutation methods along with innovative selection, crossover, boundary condition preprocessing methods to form an EA-based package to explore GB structures in grand canonical ensembles with atomistic simulations. We used this package to study the [001] symmetric tilt grain boundaries (STGBs) in FCC copper (Cu), the [110] STGBs in BCC tungsten (W), and the $[1\bar{2}10]$ STGBs in HCP magnesium (Mg). The results show that our design and implementation based on new mutation procedures, selection, and boundary conditions provide a high-quality search of atomistic GB structures in the grand canonical ensemble for different crystal lattices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dendrite-resolved, full-melt-pool phase-field simulations to reveal non-steady-state effects and to test an approximate model

In this report we study the epitaxial, columnar growth of (multiply oriented) dendrites/cells for a spot melt in a polycrystalline Al–Cu substrate using two-dimensional, phase-field, direct numerical simulations (DNS) at the full-melt-pool scale. Our main objective is to compare the expensive DNS model to a much cheaper but approximate “line” model in which a single-crystal phase-field simulation is confined to a narrow rectangular geometry. To perform this comparison, we develop algorithms that automatically extract quantities of interest (QoIs) from both DNS and line models. These QoIs allow us to quantitatively assess the assumptions in the line model and help us analyze its discrepancy with the DNS model. We consider four sets of heat source parameters, mimicking welding and additive manufacturing conditions, that create a combination shallow and deep melt pools. Our largest DNS simulation used 16K x 14K grid points in space. Our main findings can be summarized as follows. Under AM conditions, the QoIs of line models are in excellent agreement with the full DNS results for both shallow and deep melt pools. Under welding conditions, the primary spacing of the DNS model is smaller than the prediction of line model. We identify a geometric crowding effect that accounts for the discrepancies between the DNS and line models. We propose two potential mechanisms that determine the response of the microstructure to geometric crowding.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Comparison of three state-of-the-art crystal plasticity based deformation twinning models for magnesium alloys

In magnesium alloys, deformation twinning and its interactions with dislocation slip are responsible for a sigmoidal shape stress–strain behavior and an asymmetrical tension–compression yield strength in magnesium alloys. The sensitivity of twinning to the underlying microstructure renders the crystal plasticity method the most commonly adopted modeling approach for magnesium-twinning. This paper compares three state-of-the-art crystal plasticity-based twinning models from the literature, namely the elastic-viscoplastic self-consistent twinning-detwinning (EVPSC-TDT) model, crystal plasticity finite element model based on enhanced predominate twin reorientation approach (CPFE-ePTR), and the crystal plasticity finite element model based on “discrete twinning” approach (CPFE-DT). A polycrystalline microstructure is simulated with all three methods to compare the resulting stress–strain curves and lattice strains to those from the experimentally measured data. All three methods showed the capability of capturing the experimental results with different levels of accuracy. Additionally, the EVPSC-TDT method avoids solving the finite element matrices and showed the highest computational efficiency. The CPFE-ePTR model shows a higher accuracy in capturing the lattice strain. The CPFE-DT relies on high-resolution finite element mesh and is much slower than the other two methods, but it captured the local deformation concentration and stress reversal phenomena near the twin band, which was not possible with the other two methods. Based on the comparison, guidance for the selection of the appropriate model based on the specific modeling target is provided in this paper.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Recent progress on the mesoscale modeling of architected thin-films via phase-field formulations of physical vapor deposition

Thin-film coatings can be found everywhere in modern technological applications due to desirable electrical, mechanical, chemical, and optical properties. These properties directly depend upon the thin-film’s microstructural features, which are themselves influenced by the materials and vapor-deposition processing conditions used for fabrication. As such, understanding processing-microstructure relationships is essential to designing thin-films with optimized properties, and discovering new processing conditions that allow for novel thin-films with multifunctional microstructures. Here, a short review is presented on recent developments that utilize the phase-field method to simultaneously model the vapor-deposition process and corresponding microstructure formation at the mesoscale. Also phase-field-based vapor-deposition models that simulate thin-film growth of immiscible alloy and polycrystalline systems are highlighted in addition to machine-learning-based surrogate models that can facilitate accelerated high-fidelity simulations along with materials design and exploration studies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Graph neural networks for efficient learning of mechanical properties of polycrystals

Herein we present graph neural networks (GNNs) as an efficient and accurate machine learning approach to predict mechanical properties of polycrystalline materials. Here, a GNN was developed based on graph representation of polycrystals incorporating only fundamental features of grains including their crystallographic orientation, size, and grain neighbor connectivity information. We tested our method on modeling stiffness and yield strength of α -Ti microstructures, varying in their crystallographic texture. We find the GNN predicts both properties with high accuracy with mean relative errors of ~1% for unseen microstructures from a given set of textures and < 2% for microstructures of unseen texture, even when presented with limited training data. This accuracy is comparable to methods that require high-resolution three-dimensional (3D) microstructure data, such as 3D convolutional neural networks (3D-CNNs) and models that depend on the computation of spatial statistics. The present results show that graph-based deep learning is a promising framework for property prediction, especially considering the high cost associated with obtaining high-resolution 3D microstructure data and the general scarcity of experimental materials datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Computational modeling of grain boundary segregation: A review

Nearly all metals, alloys, ceramics, and their associated composites are polycrystalline in nature, with grain boundaries that separate well-defined crystalline regions that influence materials properties. In all but the most pure elemental systems, intentional solutes or impurities are present and can segregate to, or less commonly away from, the grain boundaries, in turn influencing boundary behavior, their stability, and associated materials properties. In some cases, grain-boundary segregation can also trigger “phase-like” structural transitions that dramatically alter the essential nature of the boundary. With the development of advanced electron microscopy techniques, researchers can directly observe grain-boundary structures and segregation with atomic precision. Despite such spatial resolution, the underlying mechanisms governing grain-boundary segregation remain difficult to characterize. As a result, computational modeling techniques such as density functional theory, molecular dynamics, mesoscale phase-field, continuum defect theory, and others are important complementary tools to experimental observations for studying grain-boundary segregation behavior. In conclusion, these computational methods offer the ability to explore the underlying formation mechanisms of grain-boundary segregation, elucidate complex segregation behavior, and provide insights into solutions to effectively controlling microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Corrosion characteristics of monolithic SiC materials in beryllium-bearing molten fluoride salt

In this work, chemical vapor deposited SiC single crystal and polycrystals were exposed to a static beryllium-bearing molten fluoride salt, 2LiF–BeF 2 for 500 and 1000 h at 750 °C. Overall, the single crystal and polycrystalline SiC materials experienced slight weight loss and nominal surface etching regardless of the material type. Localized pitting and nonuniform Si removal from surface regions were associated with trace metal impurities and oxygen. Cross-sectional observation revealed minimal subsurface changes in the microstructure. The corrosion damage processes were similar to those reported for molten LiF–KF–NaF salt with trace impurities, indicating that the impurities significantly affect SiC corrosion.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High Temperature Oxidation Behavior of Ni-based High Entropy Superalloys

A new class of polycrystalline gamma-prime strengthened superalloys with alloy compositions of (wt%) Ni-20Co-13Cr-6Fe-4Al-3W-2Mo-(4-x)Nb-(x)Ti (x = 0,1,2) were subjected to cyclic oxidation exposures in dry air at 800 °C for 3600 h. The alloys were borderline chromia/alumina formers, showing good oxidation resistance relative to commercially available materials of similar composition. While all alloys formed alumina scales initially, only the alloy with the lowest Ti/Nb ratio retained an alumina scale for the duration of the exposure. Formation of a continuous layer of rutile TiO 2 at the alumina/alloy interface is proposed to cause eventual alumina failure for the alloys containing Ti.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Impact of soiling on Si and CdTe PV modules: Case study in different Brazil climate zones

Soiling, particulate accumulation on photovoltaic (PV) module surfaces, reduces the available solar resource and the resulting generated device power. This case-study summarizes initial results of 5-year research on the contrasting soiling conditions in the tropical, subtropical, and semi-arid climates in Brazil. A major objective is to present a case study of the effects of soiling on PV module performance in different Brazil climate zones that represent the primary areas for the current and expanding Brazil solar installations. For this, the paper presents methodologies to quantify the soiling ratio (SRatio) and soiling rate (SRate) for two representative commercial technologies, polycrystalline or multicrystalline silicon (mc-Si) and thin-film cadmium telluride (CdTe) modules, through soiling monitoring stations deployed in the selected climate regions. An aim is to add to the growing soiling-research knowledge base through addressing these key factors and their relationships to critical electrical, solar resource, thermal, and local meteorological and environmental parameters. This paper presents, evaluates, and compares soiling rates and losses in Belo Horizonte, Minas Gerais (Equatorial Tropical: 19.92° S, 43.99° W), Porto Alegre, Rio Grande do Sul (Humid-Subtropical: 30.05° S, 51.17° W), and Brotas de Macaúbas, Bahia (Semi-Arid: 12.00° S, 42.63° W). The results show that soiling is moderate in all 3-regions, for example with 0.1%/day < SRate < 0.2%/day for Belo Horizonte. Precipitation dominates the cleaning of the modules in the summertime in this climate zone, while it is the major factor year-round in Rio Grande do Sul. Wind is the major issue mitigating the soiling accumulation for the Bahia installation. The methodology incorporates several key refinements, including the normalization and adjustment for the meteorological parameters (temperature, irradiance, wind, precipitation). The evaluations include the region-specific differing effects of non-uniform soiling, natural cleaning, and ambient temperatures.

14 SOLAR ENERGY↗
DOE OSTI2026

Analysis of the electrical double layer using electrochemical X-ray photoelectron spectroscopy

The element-sensitivity of X-ray spectroscopies offers the potential to disentangle the individual chemistries of water, ions, and adsorbates at the electrode-electrolyte interface in an element-by-element manner. However, targeted experimental design is needed to establish interface-sensitive in situ X-ray spectroscopy in a realistic electrochemical environment. Here, we demonstrate how electrochemical X-ray photoelectron spectroscopy (EC-XPS) in the dip-and-pull geometry can be used to specifically probe the behavior of ions in the electrical double layer. Taking the case study of a polycrystalline Au foil in 50 mM KClO 4 electrolyte, we tracked the electrochemical response of interfacial K + cations across a broad potential range. We show how, in combination with modeling, key parameters such as the potential of zero charge (PZC), ion packing behavior, dielectric saturation, and the electrostatic potential decay in the double layer can be extracted from the data. Importantly, we also analyze how the experimental conditions and non-idealities can influence the results and put forward criteria for reliable experimentation and data analysis.

Dip-and-pull↗
DOE OSTI2021

Controlling the Reconstruction of Ni/CeO 2 Catalyst during Reduction for Enhanced CO Methanation

Reductive pretreatment is an important step for activating supported metal catalysts but has received little attention. In this study, reconstruction of the supported nickel catalyst was found to be sensitive to pretreatment conditions. In contrast to the traditional activation procedure in hydrogen, activating the catalyst in syngas created supported Ni nanoparticles with a polycrystalline structure containing an abundance of grain boundaries. The unique post-activation catalyst structure offered enhanced CO adsorption and an improved CO methanation rate. The current strategy to tune the catalyst structure via manipulating the activation conditions can potentially guide the rational design of other supported metal catalysts.

42 ENGINEERING↗
DOE OSTI2020

Single crystal cathodes enabling high-performance all-solid-state lithium-ion batteries

All-solid-state lithium-ion batteries (ASSLIBs) are receiving significant attention owing to their improved safety and energy density over liquid counterparts. However, single-crystal cathodes have never been investigated in ASSLIBs. In this work, single-crystal Li(Ni 0.5 Mn 0.3 Co 0.2 )O 2 (SC-NMC532) is used as the cathode material for ASSLIBs, which exhibits 6~14 times higher Li + diffusion coefficient than polycrystalline Li(Ni 0.5 Mn 0.3 Co 0.2 )O 2 (PC-NMC532). As a result, SC-NMC532 exhibits an initial specific capacity of 156.4 mAh.g -1 while PC-NMC532 shows an initial capacity of only 127.5 mAh.g -1 . After 150 cycles, SC-NMC532 retains the capacity of 94.5 mAh.g -1 . More impressively, under a high current density of 1.3 mA.cm -2 , SC-NMC532 exhibits a capacity of 82 mAh.g -1 , much higher than that of PC-NMC532 (2.1 mAh.g -1 ). This work demonstrates that single-crystal NMC cathodes could enable both high power density and high energy density of ASSLIBs.

25 ENERGY STORAGE↗
DOE OSTI2021

A perspective on single-crystal layered oxide cathodes for lithium-ion batteries

As the demand for lithium-ion batteries grows exponentially to feed the nascent electric-vehicle and grid-storage markets, the need for higher energy density and longer cycle life becomes more apparent. Increasing the nickel content in the layered-oxide cathodes has been a dominant strategy to increase energy density, but this has exacerbated the surface reactivity concerns. Furthermore, the high states of charge associated with increased capacity lead to cracking of the polycrystalline cathode particles, which exposes fresh surfaces and accelerates capacity fade. Single-crystal cathode particles with low susceptibility to cracking have recently taken on intense interest due to their remarkable cyclability. Many different approaches to single-crystal synthesis have been explored, but there has been no systematic analysis of the different techniques to date. Additionally, many reports have taken on a trial-and-error approach, ignoring well established literature on grain growth outside the battery field. This perspective reviews the literature on single-crystal cathode synthesis through the lens of classic grain growth theories, providing insight and hopefully accelerating the adoption of the promising single-crystal cathode morphology.

25 ENERGY STORAGE↗
DOE OSTI2024

Machine-learning-assisted deciphering of microstructural effects on ionic transport in composite materials: A case study of Li 7 La 3 Zr 2 O 12 -LiCoO 2

The effective diffusivity of ionic species in multiphase materials is critical for the design and function of composite materials for electrochemical energy storage. In practice, effective diffusivity depends sensitively not only on the intrinsic diffusivities of constituting materials but also on their topological arrangement; nevertheless, these coupled contributions are oversimplified in most analytical models. Here, we combine atomistically informed mesoscale modeling and machine learning (ML) analysis to unravel how such features affect effective diffusivity in two-phase composites. Using the Li 7 La 3 Zr 2 O 12 -LiCoO 2 composite solid-state battery cathode as a model system, we compute effective diffusivity for 600 distinct dense polycrystalline microstructures with different topological configurations of grains, grain boundaries, and heterointerfaces. We verify that in addition to atomic-scale variabilities, microstructural feature diversity can significantly impact effective transport properties. Across the ensemble of test microstructures, this often results in bimodal distributions of effective diffusivity that encompass two qualitatively distinct operating mechanisms, which we identify via flux analysis. An ML approach reveals that the most critical determining factors for effective diffusivity are the connectivity of bulk phases and their heterointerfaces. The role of ionic mobility at the heterointerfaces is also discussed. These insights highlight the combined importance of microstructure and interface engineering in tuning the transport properties of ionic species in composite materials. In conclusion, our framework can also be extended for understanding generic microstructure-property relationships in other complex multiphase materials.

25 ENERGY STORAGE↗
DOE OSTI2024

Probing degradation at solid-state battery interfaces using machine-learning interatomic potential

Solid-state batteries featuring fast ion-conducting solid electrolytes are promising next-generation energy storage technologies, yet challenges remain for practical deployment due to electro-chemo-mechanical instabilities at solid-solid interfaces. These interfaces, which include homogeneous/internal interfaces such as grain boundaries (GBs) and heterogeneous/external interfaces between solid-electrolyte and electrode materials, can impede Li-ion transport, deteriorate performance, and eventually lead to cell failure. Here, in this study, we leverage large-scale molecular simulations, enabled by validated machine-learning interatomic potentials, to directly probe the onset of interfacial degradation at the garnet Li 7 La 3 Zr 2 O 12 (LLZO) solid-electrolyte/LiCoO 2 (LCO) cathode interface. By surveying different interfacial geometries and compositions, it is found that Li-deficient interfaces can lead to severe interfacial disordering with cation mixing and Co interdiffusion from LCO into LLZO. By contrast, Li-sufficient interfaces are less disordered, although elemental segregation with local ordering is observed. As a consequence of Co interdiffusion, Co-rich regions are formed at the GBs of LLZO due to cation segregation and trapping effects. This behavior is independent of the GB tilting axis, degree of disorder at the GBs, and Co concentration, which implies Co clustering at GBs is a general phenomenon in polycrystalline LLZO and can dictate its overall transport and mechanical properties. Our findings elucidate the underlying fundamental mechanisms that give rise to experimentally observed physicochemical properties and provide guidelines for interface design that can mitigate interfacial degradation and improve cycling performance.

25 ENERGY STORAGE↗
DOE OSTI2024

Mesoscale interplay among composition heterogeneity, lattice deformation, and redox stratification in single-crystalline layered oxide cathode

Single-crystalline layered oxide materials for lithium-ion batteries are featured by their excellent capacity retention over their polycrystalline counterparts, making them sought-after cathode candidates. Their capacity degradation, however, becomes more severe under high-voltage cycling, hindering many high-energy applications. It has long been speculated that the interplay among composition heterogeneity, lattice deformation, and redox stratification could be a driving force for the performance decay. The underlying mechanism, however, is not well-understood. In this study, we use X-ray microscopy to systematically examine single-crystalline NMC particles at the mesoscale. This technique allows us to capture detailed signals of diffraction, spectroscopy, and fluorescence, offering spatially resolved multimodal insights. Focusing on early high-voltage charging cycles, we uncover heterogeneities in valence states and lattice structures that are inherent rather than caused by electrochemical abuse. These heterogeneities are closely associated with compositional variations within individual particles. Our findings provide useful insights for refining material synthesis and processing for enhanced battery longevity and efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multi-scale boron penetration toward stabilizing nickel-rich cathode

Nickel-rich layered oxides LiNi x Co y Mn 1-x-y O 2 (x≥0.8) have been recognized as the preferred cathode materials to develop lithium-ion batteries with high energy density (>300Wh kg -1 ). However, the poor cycling stability and rate capability stemming from intergranular cracks and sluggish kinetics hinder their commercialization. To address such issues, a multi-scale boron penetration strategy is designed and applied on the polycrystalline LiNi 0.83 Co 0.11 Mn 0.06 O 2 particles that are pre-treated with pore construction. The lithium-ion conductive lithium borate in grain gaps functions as the grain binder that can bear the strain/stress from anisotropic contraction/expansion, and provides more pathways for lithium-ion diffusion. As a result, the intergranular cracks are ameliorated and the lithium-ion diffusion kinetics is improved. Moreover, the coating layer separates the sensitive cathode surface and electrolyte, helping to suppress the parasitic reactions and related gas evolution. In addition, the enhanced structural stability is acquired by strong B-O bonds with trace boron doping. As a result, the boron-modified sample with an optimized boron content of 0.5% (B5-NCM) exhibits a higher initial discharge capacity of 205.5mAh g -1 at 0.1C (1C=200mA g -1 ) and improved capacity retention of 81.7% after 100 cycles at 1C. Furthermore, the rate performance is distinctly enhanced by high lithium-ion conductive LBO (175.6mAh g -1 for B5-NCM and 154.6mAh g -1 for B0-NCM at 5C).

25 ENERGY STORAGE↗
DOE OSTI2022

Experimental Investigation of Drillstring Torsional Vibration Effect on Rate of Penetration with PDC Bits in Hard Rock

Polycrystalline diamond compact (PDC) bits have shown tremendous performance compared to roller cone bits and have gained attraction in deep geothermal drilling applications. While PDC bits can reach a higher rate of penetration compared to other bits, they are more prone to drilling vibrations. The scope of this paper is to quantify the effects of drillstring torsional vibrations on PDC bit performance using a laboratory testing facility. Here, the tests were performed with three drillstring configurations to evaluate the effect of drillstring vibrations. The results showed that rigid testing overestimates the bit rate of penetration by 35% due to torsional vibrations.

15 GEOTHERMAL ENERGY↗