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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 OSTI2018

Auto-ignition study of FACE gasoline and its surrogates at advanced IC engine conditions

Robust surrogate formulation for gasoline fuels is challenging, especially in mimicking auto-ignition behavior observed under advanced combustion strategies including boosted spark-ignition and advanced compression ignition. This work experimentally quantifies the auto-ignition behavior of bi- and multi-component surrogates formulated to represent a mid-octane (Anti-Knock Index 91.5), full boiling-range, research grade gasoline (Fuels for Advanced Combustion Engines, FACE-F). A twin-piston rapid compression machine is used to achieve temperature and pressure conditions representative of in-cylinder engine operation. Changes in low- and intermediate-temperature behavior, including first-stage and main ignition times, are quantified for the surrogates and compared to the gasoline. This study identifies significant discrepancies in the first-stage ignition behavior, the influence of pressure for the bi- to ternary blends, and highlights that better agreement is achieved with multi-component surrogates, particularly at lower temperature regimes. A recently-updated detailed kinetic model for gasoline surrogates is also used to simulate the measurements. Finally, sensitivity analysis is employed to interpret the kinetic pathways responsible for reactivity trends in each gasoline surrogate.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Data analytics approach to predict high-temperature cyclic oxidation kinetics of NiCr-based Alloys

Abstract Although of practical importance, there is no established modeling framework to accurately predict high-temperature cyclic oxidation kinetics of multi-component alloys due to the inherent complexity. We present a data analytics approach to predict the oxidation rate constant of NiCr-based alloys as a function of composition and temperature with a highly consistent and well-curated experimental dataset. Two characteristic oxidation models, i.e., a simple parabolic law and a statistical cyclic oxidation model, have been chosen to numerically represent the high-temperature oxidation kinetics of commercial and model NiCr-based alloys. We have successfully trained machine learning (ML) models using highly ranked key input features identified by correlation analysis to accurately predict experimental parabolic rate constants ( k p ). This study demonstrates the potential of ML approaches to predict oxidation kinetics of alloys over wide composition and temperature ranges. This approach can also serve as a basis for introducing more physically meaningful ML input features to predict the comprehensive cyclic oxidation behavior of multi-component high-temperature alloys with proper constraints based on the known underlying mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Micron-sized spinel crystals in high level waste glass compositions: Determination of crystal size and crystal fraction

The compositions utilized for immobilization of nuclear waste are controlled using glass property models to avoid the deleterious effects of crystallization in the high-level waste (HLW) vitrification melters. The type and size of the crystals that precipitate during melter operations (typically at 1150 °C) and idling (~ 1000 °C) are significantly impacted by glass composition and thermal history. This study was conducted to measure the impact of melt composition and heat treatment temperature on crystal size and fraction. A matrix of 31 multi-component glasses canvasing the expected Hanford HLW compositional space was developed and the glasses fabricated and heat treated at 850 = T = 950°C. The crystal filling fraction values, as determined by X-ray diffraction, varied from 0.2 to 41.0 wt%. Spinel filling fraction values ranged from 0.0 to 13.8 wt%. One glass of the matrix did not precipitate spinel and contained 0.2 wt% RuO 2 , which was assumed to be undissolved from the melting process. All compositions contained crystals in the as-quenched glass. All of the spinel based crystals present in the glasses were less than 10 µm in diameter, as determined by scanning electron microscopy. Composition and temperature dependent models were generated using the resulting data and the best model fit was obtained by only considering spinel filling fractions (R 2 = 0.83). Two glasses were unable to be characterized due to an inability to process the glass under the conditions of this study. Those glasses were utilized to give insight into a potential multi-component constraint to aid in future statistical composition designs.

Lonergan, C. E.↗
DOE OSTI2025

Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model

Compound riverine and coastal flooding is usually driven by complex interactions among meteorological, hydrological, and ocean extremes. However, existing efforts to model this phenomenon often do not integrate hydrological processes across atmosphere–land–river–ocean systems, leading to substantial uncertainties that have not been fully examined. To bridge this gap, we leverage the new capabilities of the Energy Exascale Earth System Model (E3SM) that enable a multi-component framework that integrates coastally refined atmospheric, terrestrial, and oceanic components. We evaluate compound uncertainties arising from two-way land–river–ocean coupling in E3SM and track the cascading meteorological and hydrological uncertainties through ensemble simulations over the Delaware River basin and estuary during Hurricane Irene (2011). Our findings highlight the importance of two-way river–ocean coupling to compound flood modeling and demonstrate E3SM's capability in capturing compound flood extent near the coast, with a hit rate over 0.75. Our study shows the growing uncertainties that transition from atmospheric forcings to flood distribution and severity. Furthermore, an analysis based on artificial neural networks is used to assess the roles of hydrological drivers, such as infiltration and soil moisture, in the generation of compound flooding. The response of compound floods to tropical cyclones (TCs) is found to be susceptible to these often overlooked drivers. For instance, the flooded area could increase more than 2-fold (∼2.4) if Hurricane Irene were preceded by an extreme antecedent soil moisture condition (AMC). The results not only support the use of a multi-component framework for interactive flooding processes, but also underscore the necessity of broader definitions of compound flooding that encompass the simultaneous occurrence of intense precipitation, storm surge, and high AMC during TCs.

Feng, Dongyu [Pacific Northwest National Laborator↗
DOE OSTI2023

Plastic homogeneity in nanoscale heterostructured binary and multicomponent metallic eutectics: An overview

Heterostructured materials comprised of relatively soft/hard disparate phases typically exhibit composite strengthening but lack plastic deformability at ambient temperatures. However, heterostructured systems comprised of nanoscale phases can simultaneously enhance yield strength and strain hardening, thereby promoting uniform distribution of plastic flow. In this review, the atomic-scale deformation mechanisms in model systems of eutectic alloys, Al-Al 2 Cu and Al-Si, refined to nanoscales via laser rapid solidification are discussed, and compared with literature on multi-component (high entropy) eutectics such as Ni-Al-Fe-based with Cr and/or Co additions. The nano-lamellar Al-Al 2 Cu structures exhibit unit defect mechanisms not reported in monolithic Al 2 Cu intermetallic: localized shear on {0 1 1} and shear-induced faults on {1 2 1} planes, constrained by closely-spaced dislocation arrays in Al confined by Al/Al 2 Cu interfaces. The unexpected plasticity mechanisms are enabled by slip continuity in nanoscale Al-Al 2 Cu eutectics associated with the orientation relationship and interface habit planes. In nano-fibrous Al-Si eutectic, tensile ductility at strength approaching 600 MPa is observed resulting from dislocation plasticity in the nano-Al channels and cracking in Si nanofibers. Molecular dynamics simulations show that Al dislocations easily cross-slip (screw) or climb (edge) along Al-Si interfaces, making slip transmission difficult. The propagation of nano-cracks is suppressed by surrounding strain hardening Al, retaining good ductility of the sample, in spite of lack of direct slip transmission. Finally, the critical unit mechanisms of slip transmission and interface-enabled plasticity observed in nanoscale eutectic binary systems can also explain the strength-ductility relationship in multi-component eutectics and homogeneously distributed plastic flow with increasing microstructural heterogeneity.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Evaluation of Tellurium as a Fuel Additive in Neodymium-Containing U-Zr Metallic Fuel

Phase-stability in a U-Zr-Te-Nd multi-component metallic fuel for advanced nuclear reactors is systematically investigated by taking into account binary, ternary and quaternary interactions between elements involved. Historically, the onset of fuel-cladding chemical interactions (FCCI) greatly limits the burnup potential of U-Zr fuels primarily due to interactions between lanthanide fission products and cladding constituents. Tellurium (Te) is evaluated as a potential additive for U-Zr fuels to bind with lanthanide fission products, e.g. neodymium (Nd), negating or mitigating the FCCI effect. Potential fresh fuel alloy compositions with the Te additive, U-Zr-Te, are characterized. Te is found to completely bind with Zr within the U-Zr matrix. Alloys simulating the formation of the lanthanide element Nd within U-Zr-Te are also evaluated, where the Te-Nd binary interaction dominates and NdTe is found to form as a high temperature stable compound. The experimental observations agree well with the trends obtained from density functional theory calculations. According to the calculated enthalpy of mixing, Zr-Te compound formation is favored in the U-Zr-Te alloy whereas NdTe compound formation is favored in the U-Zr-Te-Nd alloy. Further, the calculated charge density distribution and density of states provide sound understanding of the mutual chemical interactions between elements and phase-stability within the multi-component fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Solvent-Free Self-Assembly for Scalable Preparation of Highly Crystalline Mesoporous Metal Oxides

Mesoporous metal oxides (MMOs) have been demonstrated great potential in various applications. Up to now, the direct synthesis of MMOs is still limited to the solvent induced inorganic-organic self-assembly process. In this work, we develop a facile, general, and high throughput solvent-free self-assembly strategy to synthesize a series of MMOs including single-component MMOs and multi-component MMOs (e.g., doped MMOs, composite MMOs, and polymetallic oxide) with high crystallinity and remarkable porous properties by grinding and heating raw materials. Compared with the traditional solution self-assembly process, the avoidance of solvents in this method not only greatly increases the yield of target products and synthesis efficiency, but also reduces the environmental pollution and the consumption of cost and energy. We believe the presented approach will pave a new avenue for scalable production of advanced mesoporous materials for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning

Proton exchange membrane fuel cells, consuming hydrogen and oxygen to generate clean electricity and water, suffer acute liquid water challenges. Accurate liquid water modelling is inherently challenging due to the multi-phase, multi-component, reactive dynamics within multi-scale, multi-layered porous media. In addition, currently inadequate imaging and modelling capabilities are limiting simulations to small areas (<1 mm 2 ) or simplified architectures. Herein, an advancement in water modelling is achieved using X-ray micro-computed tomography, deep learned super-resolution, multi-label segmentation, and direct multi-phase simulation. The resulting image is the most resolved domain (16 mm 2 with 700 nm voxel resolution) and the largest direct multi-phase flow simulation of a fuel cell. This generalisable approach unveils multi-scale water clustering and transport mechanisms over large dry and flooded areas in the gas diffusion layer and flow fields, paving the way for next generation proton exchange membrane fuel cells with optimised structures and wettabilities.

25 ENERGY STORAGE↗
DOE OSTI2023

A General Framework for Progressive Data Compression and Retrieval

In scientific simulations, observations, and experiments, the transfer of data to and from disk and across networks has become a major bottleneck for data analysis and visualization. Compression techniques have been employed to tackle this challenge, but traditional lossy methods often demand conservative error tolerances to meet the numerical accuracy requirements of both anticipated and unknown data analysis tasks. Progressive data compression and retrieval has emerged as a promising solution, where each analysis task dictates its own accuracy needs. However, few analysis algorithms inherently support progressive data processing, and adapting compression techniques, file formats, client/server frameworks, and APIs to support progressivity can be challenging. Here, this paper presents a framework that enables progressive-precision data queries for any data compressor or numerical representation. Our strategy hinges on a multi-component representation that successively reduces the error between the original and compressed field, allowing each field in the progressive sequence to be expressed as a partial sum of components. We have implemented this approach with four established scientific data compressors and assessed its effectiveness using real-world data sets from the SDRBench collection. The results show that our framework competes in accuracy with the standalone compressors it is based upon. Additionally, (de)compression time is proportional to the number of components requested by the user. Finally, our framework allows for fully lossless compression using lossy compressors when a sufficient number of components are employed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Model development for flash boiling spray and validations with isooctane, hexane, ethanol and their binary mixtures

The objective of this study is to develop a comprehensive model for spray atomization under the consideration of flash boiling, which includes nucleation, bubble growth, and droplet breakup. Although flash boiling has been previously studied, there is still no well-established analytical and numerical model of their mechanisms, or general guidelines on the implementation of this atomization strategy. In this study, detailed formulations are elaborated for the unified spray atomization model under both non-flash and flash boiling conditions. Next, the model was implemented into CFD software and 3-D simulations were performed for model validations. Two fuel blends are tested: ethanol-isooctane blends and hexane-isooctane blends. Simulation results were compared with the experimental measurements conducted using two methodologies, DBI (Diffuse Backlight Imaging) system for spray images captured by a high-speed camera, and a PDA (Phase Doppler Anemometry) system for droplet size measurement during the spray injection process. It was found that the current flash boiling model can accurately capture the spray characteristics under different environment conditions, such as the spray plume interactions and liquid penetration. The averaged Sauter mean diameter (SMD) calculations match the measurement sufficiently well. The spray structures for both single- and multi-component fuels during the injection process are well represented by current model.

42 ENGINEERING↗
DOE OSTI2025

Alloying multiple halide perovskites on the same sublattice in search of stability and target band gaps

Single-component halide perovskites (HPs) rarely satisfy all the necessary criteria for optoelectronic applications, such as achieving an optimal band gap while maintaining high chemical and structural stability. Alloying halide perovskites has emerged as a promising strategy, not only to enhance stability but also to fine-tune their electronic and optical properties. In this work, we explore multiple degrees of freedom in alloy design, considering different substitution sublattices sites (A, B, or X in ABX3 perovskites), various chemical species (isovalent and hetero-valent elements), and multi-component compositions on a given sublattice. Using first-principles calculations based on density functional theory (DFT), we investigate how compositional variations influence the electronic (band gap) and structural properties (mixing enthalpy) of HP alloys. Our approach employs the polymorphous cell model, allowing full local relaxation which breaks local symmetry while preserving global cubic symmetry—an essential framework for accurately modeling HPs. Our results reveal that X-site mixing (halogen substitution) primarily affects the valence band maximum, allowing target band gap engineering. Additionally, variations in halogen radii introduce internal strain through octahedral distortions, influencing the mixing enthalpy. A-site substitution, while not directly contributing to the band edge states, modifies structural stability via volume effects, indirectly impacting the band gap. B-site alloying plays a dominant role in band gap modulation, leading to either positive or negative band gap bowing. Specifically, isovalent B-site mixing (Sn–Pb) induces strong positive bowing, where the alloy band gap is smaller than the average gap of parent compounds, whereas hetero-valent mixing (Cd–Pb) results in pronounced negative bowing. As an aside, we investigate the competition between the excess energy of disordered alloys vs. that of long-range ordered double perovskites of the same compositions, seeking examples of ordered phases emerging from disordered alloys. Furthermore, our findings provide fundamental insights into the electronic and structural behavior of HP alloys, offering valuable design principles for the development of stable and efficient materials for next-generation photovoltaic and optoelectronic devices.

14 SOLAR ENERGY↗
DOE OSTI2024

Integration and validation of some modules for modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures

Three modules are integrated into the built-in OpenFOAM rhoCentralFoam solver towards accurate and efficient modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures within the OpenFOAM 10.0 framework. The first module is the mixture-averaged diffusion model. The second module is the built-in OpenFOAM Lagrangian solver coupled with optimised droplet drag coefficient and convective heat transfer coefficient sub-models. The last module is a sparse stiff chemistry solver based on dynamic adaptive hybrid integration (AHI-S). The optimised droplet sub-models are first verified in correct implementation for subsequent simulations in this work. Further, they show good accuracy against experimental and analytical data in the modelling of ammonia droplet acceleration and cooling in the flowing and/or low-temperature air. The accuracy and efficiency gains related to the mixture-averaged diffusion model and the AHI-S chemistry solver are examined by simulating 1-D detonation propagation in ammonia droplet-free/laden ammoniaoxygen mixtures. Numerical results of detonation propagation speed, gaseous temperature, density, and species distributions around the induction zone show good agreement with experimental data and analytical solutions. Compared to the built-in OpenFOAM diffusion model, the mixture-averaged diffusion model provides different numerical predictions of pulsating instabilities in detonation propagation. It shows better accuracy in depicting the detonation structure within the droplet-free section attributed to improved multi-component diffusion modelling. Compared to the built-in OpenFOAM solver EulerImplicit (backward Euler), the AHI-S chemistry solver reduces the computational cost by around 50%. It achieves satisfactory accuracy in calculating detonation propagation speed within the droplet-free section with the optimal efficiency when the safety factor, β, equals 0.5.

42 ENGINEERING↗
DOE OSTI2023

Controls on Barite (BaSO 4 ) Precipitation in Unconventional Reservoirs

Barite (BaSO 4 ) precipitation is one of the most ubiquitous examples of secondary sulfate mineral scaling in shale oil and gas reservoirs. Often, a suite of chemical additives is used during fracturing operations to inhibit the accumulation of mineral scales, though their efficacy is widely varied and poorly understood. This study combines experimental data and multi-component numerical reactive transport modeling to offer a more comprehensive understanding of the geochemical behavior of barite accumulation in shale matrices under conditions typical of fracturing operations. A variety of additives and conditions are individually tested in batch reactor experiments to identify the factors controlling barite precipitation. Our experimental results demonstrate a pH dependence in the rate of barite precipitation, which we use to develop a predictive model including a pH-dependent term that satisfactorily reproduces our observations. Further, this model is then extended to consider the behavior of three major shale samples of highly variable mineralogy (Eagle Ford, Marcellus, and Barnett). This data-validated model offers a reliable tool to predict and ultimately mitigate against secondary mineral accumulation in unconventional shale reservoirs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Multi-element effects on arsenate accumulation in a geochemical matrix determined using µ-XRF, µ-XANES and spatial statistics

Soils regulate the environmental impacts of trace elements, but direct measurements of reaction mechanisms in these complex, multi-component systems can be challenging. The objective of this work was to develop approaches for assessing effects of co-localized geochemical matrix elements on the accumulation and chemical speciation of arsenate applied to a soil matrix. Synchrotron X-ray fluorescence microprobe (µ-XRF) images collected across 100 µm × 100 µm and 10 µm × 10 µm regions of a naturally weathered soil sand-grain coating before and after treatment with As(V) solution showed strong positive partial correlations ( r ' = 0.77 and 0.64, respectively) between accumulated As and soil Fe, with weaker partial correlations ( r ' > 0.1) between As and Ca, and As and Zn in the larger image. Spatial and non-spatial regression models revealed a dominant contribution of Fe and minor contributions of Ca and Ti in predicting accumulated As, depending on the size of the sample area analyzed. Time-of-flight secondary ion mass spectrometry analysis of an area of the sand grain showed a significant correlation ( r = 0.51) between Fe and Al, so effects of Fe versus Al (hydr)oxides on accumulated As could not be separated. Fitting results from 25 As K -edge microscale X-ray absorption near-edge structure (µ-XANES) spectra collected across a separate 10 µm × 10 µm region showed ~60% variation in proportions of Fe(III) and Al(III)-bound As(V) standards, and fits to µ-XANES spectra collected across the 100 µm × 100 µm region were more variable. We find that, consistent with insights from studies on model systems, the results obtained here indicate a dominance of Fe and possibly Al (hydr)oxides in controlling As(V) accumulation within microsites of the soil matrix analyzed, but the analyses inferred minor augmentation from co-localized Ti, Ca and possibly Zn.

58 GEOSCIENCES↗
DOE OSTI2022

Emissions Merit Function for Evaluating Multifunctional Catalyst Beds

With emission control regulations getting stricter, multi-functional catalyst systems are increasingly important for low-temperature operation. We investigate a wide range of multi-component catalyst systems, as physical mixtures and in multi-bed configurations, while varying the ratios of hydrocarbon traps (HCT), passive NOx adsorbers (PNAs), and diesel oxidation catalysts (DOC). Using industrially guided protocols, we measured the ability of these complex catalyst systems to reduce emissions during a 40 °C/min temperature ramp to simulate cold-start conditions. Using a temperature boundary condition of 250 °C, the average conversion was calculated for each regulated pollutant: CO, NOx, and total hydrocarbons (THC). An emissions merit function was developed to evaluate the effectiveness of each system relative to the relevant emission standards and expected engine exhaust concentrations. This merit function identified that a 1:1:4 ratio of PNA:HCT:DOC was the most effective emissions reduction configuration and had similar reactivity as a physical mixture or as a PNA→HCT→DOC multi-bed reactor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Hydrodynamically Controlled Self‐Organization in Mixtures of Active and Passive Colloids

Abstract Active particles are known to exhibit collective behavior and induce structure in a variety of soft‐matter systems. However, many naturally occurring complex fluids are mixtures of active and passive components. The authors examine how activity induces organization in such multi‐component systems. Mixtures of passive colloids and colloidal micromotors are investigated and it is observed that even a small fraction of active particles induces reorganization of the passive components in an intriguing series of phenomena. Experimental observations are combined with large‐scale simulations that explicitly resolve the near‐ and far‐field effects of the hydrodynamic flow and simultaneously accurately treat the fluid–colloid interfaces. It is demonstrated that neither conventional molecular dynamics simulations nor the reduction of hydrodynamic effects to phoretic attractions can explain the observed phenomena, which originate from the flow field that is generated by the active colloids and subsequently modified by the aggregating passive units. These findings not only offer insight into the organization of biological or synthetic active–passive mixtures, but also open avenues to controlling the behavior of passive building blocks by means of small amounts of active particles.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High Density Two-Component Glasses of Organic Semiconductors Prepared by Physical Vapor Deposition

Physical Vapor Deposition (PVD) is widely utilized for the production of organic semiconductor devices due to its ability to form thin layers with exceptional properties. Although the layers in the device usually consist of two or more components, there is limited understanding about the fundamental characteristics of such multi-component vapor-deposited glasses. Here, spectroscopic ellipsometry was employed to characterize the densities, thermal stabilities and optical properties of co-vapor deposited NPD and TPD glasses across the entire range of composition. We find that co-deposited NPD and TPD form high density glasses with enhanced thermal stability. The dependences of density and stability upon substrate temperature are correlated, and the birefringence of the co-deposited glasses is determined by the reduced substrate temperature of mixtures. Additionally, we observe that the transformation of a highly stable and dense two-component glass into its supercooled liquid initiates from the free surface and propagates into the bulk at constant velocity, like single component PVD glasses. As a result, all these features are consistent with the surface equilibration mechanism.

77 NANOSCIENCE AND NANOTECHNOLOGY↗