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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Three-State Majority-vote Model on Scale-Free Networks and the Unitary Relation for Critical Exponents

Abstract We investigate the three-state majority-vote model for opinion dynamics on scale-free and regular networks. In this model, an individual selects an opinion equal to the opinion of the majority of its neighbors with probability 1 − q , and different to it with probability q . The parameter q is called the noise parameter of the model. We build a network of interactions where z neighbors are selected by each added site in the system, a preferential attachment network with degree distribution k − λ , where λ = 3 for a large number of nodes N . In this work, z is called the growth parameter. Using finite-size scaling analysis, we obtain that the critical exponents $$\beta /\bar{\nu }$$ β / ν ¯ and $$\gamma /\bar{\nu }$$ γ / ν ¯ associated with the magnetization and the susceptibility, respectively. Using Monte Carlo simulations, we calculate the critical noise parameter q c as a function of z for the scale-free networks and obtain the phase diagram of the model. We find that the critical exponents add up to unity when using a special volumetric scaling, regardless of the dimension of the network of interactions. We verify this result by obtaining the critical noise and the critical exponents for the two and three-state majority-vote model on cubic lattice networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Unraveling the Highly Plastic Behavior of ALD-Aluminum Oxide Encapsulations by Small-Scale Tensile Testing

We present a study directly measuring the electron-beam-induced plasticity of amorphous Al 2 O 3 coatings. Core–shell nanostructures are employed as small-scale model systems for two-dimensional coatings made by atomic layer deposition (ALD). Copper nanowires (NWs) are used as substrates for ALD deposition, representing a model system for interconnects commonly found in integrated circuits. Experiments are performed in situ in a transmission electron microscope (TEM) and further analyzed with electron energy loss spectroscopy (EELS). Our in situ TEM tensile experiments reveal the highly plastic behavior of the ALD shell, which withstands a maximum strain of 188%. Comparable samples under beam-off conditions show a brittle fracture, which underlines the effect of electron irradiation. The electron-beam-activated bond switching within the amorphous network enables compensation of the applied tensile strain, leading to viscous flow. By incorporating an intermediate nanocrystalline layer within the Al 2 O 3 shell, the plasticity is suppressed and brittle fracture occurs. This work directly demonstrates the tuning of mechanical properties in amorphous ALD structures through electron irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Enabling 6C Fast Charging of Li–Ion Batteries with Graphite/Hard Carbon Hybrid Anodes

Li-ion batteries that can simultaneously achieve high-energy density and fast charging are essential for electric vehicles. Graphite anodes enable a high-energy density, but suffer from an inhomogeneous reaction current and irreversible Li plating during fast charging. In contrast, hard carbon exhibits superior rate performance but lower energy density owing to its lower initial coulombic efficiency and higher average voltage. In this work, these tradeoffs are overcome by fabricating hybrid anodes with uniform mixtures of graphite and hard carbon, using industrially-relevant multi-layer pouch cells (>1 Ah) and electrode loadings (3 mAh cm –2 ). By controlling the graphite/hard carbon ratio, this study shows that battery performance can be systematically tuned to achieve both high-energy density and efficient fast charging. Pouch cells with optimized hybrid anodes retain 87% and 82% of their initial specific energy after 500 cycles of 4C and 6C fast-charge cycling, respectively. This is significantly higher than the 61% and 48% specific energy retention with graphite anodes under the same conditions. The enhanced performance is attributed to improved homogeneity of the reaction current throughout the hybrid anode, which is supported by continuum-scale modeling. Furthermore, this process is directly compatible with existing roll-to-roll battery manufacturing, representing a scalable pathway to fast charging.

25 ENERGY STORAGE↗
DOE OSTI2021

Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis

The generalized singular value decomposition (GSVD) is a valuable tool that has many applications in computational science. However, computing the GSVD for large-scale problems is challenging. Motivated by applications in hyper-differential sensitivity analysis (HDSA), in this work we propose new randomized algorithms for computing the GSVD which use randomized subspace iteration and weighted QR factorization. Detailed error analysis is given which provides insight into the accuracy of the algorithms and the choice of the algorithmic parameters. We demonstrate the performance of our algorithms on test matrices and a large-scale model problem where HDSA is used to study subsurface flow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Interfacial Effects on the Dielectric Properties of Elastomer Composites and Nanocomposites

Elastomer-based composites and nanocomposites are discussed, with the emphasis on the filler and interfacial effects on their dynamics, and the resulting manifestation in their macroscopic dielectric or mechanical response. Specifically, selected polydimethylsiloxane (PDMS)/barium-titanate and styrene-butadiene rubber (SBR)/graphene oxide nanocomposites are discussed, as examples where controlled spatial distribution of filler (structured composites) gives rise to significantly different dielectric and thermomechanical behaviors. Also, ethylene–propylene–diene (EPDM)/carbon black (CB) composites are presented, as examples of systems that exhibit an abnormal temperature dependence of dielectric relaxation; and this response is discussed in the context of CB cluster polarization and quantified through a simple scaling model of the same. Finally, multi-filler EPDM/CB/ceramic elastomer nanocomposites are discussed, as examples of systems with antagonistic interfacial effects between conductive and dielectric fillers, as well as with strong interphase responses that can overwhelm the dielectric contributions from the fillers; in these systems, interphasial responses result in counter-intuitive dielectric behaviors and in strong deviations from standard design principles typically employed in the design of dielectric composite systems.

Li, Bo↗
DOE OSTI2022

Computational Design of a Simple Flyer Plate Launcher

The response of materials to shock loading is important to understand for a variety of applications. When shock physics emerged during and after WWII, direct explosive loading or explosively driven plate impact was the primary tool for these studies. Subsequent decades have seen the widespread use of large caliber guns for plate impact studies, laser-shock facilities and pulsed power facilities. INL currently lacks a gun suitable for plate impact or explosives casting and machining facilities; however, it does possess explosives use and handling capabilities. An option for performing plate impact experiments was needed, therefore continuum scale models were utilized to explore a few simple donor-acceptor explosive plane wave lens designs, one of which could be hand packed with plastic explosives to launch flyer plates. 2D simulations were performed to study different geometries in an effort to minimize the difference in shock arrival across the central portion of a small copper flyer plate. A shock wave arrival time difference under 50 ns across 50 percent of the center of the flyer was achieved with a few designs. This work summarizes the computational models and results.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Impact of Drought on Ecohydrology of Southern California Grassland and Shrubland

Abstract Through their rooting profiles and water demands, plants affect the distribution of water in the soil profile. Simultaneously, soil water content controls plant development and interactions within and between plant communities. These plant-soil water feedbacks might vary across plant communities with different rooting depths and species composition. In semiarid environments, understanding these differences will be essential to predict how ecosystems will respond to drought, which may become more frequent and severe with climate change. In this study, we tested how plant-soil water feedbacks responded to drought in two contrasting ecosystem types—grassland and shrubland—in the coastal foothills of southern California. During years 5–8 of an ongoing precipitation manipulation experiment, we measured changes in plant communities and soil moisture up to 2 m depth. We observed different water use patterns in grassland and shrubland communities with distinct plant functional types and water use strategies. Drought treatment did not affect perennial, deep-rooted shrubs because they could access deep soil water pools. However, mid-rooted shrubs were sensitive to drought and experienced decreased productivity and die-off. As a result, water content actually increased with drought at soil depths from 50–150 cm. In grassland, biomass production by annual species, including annual grasses and forbs, declined with drought, resulting in lower water uptake from the surface soil layer. An opportunistic “live fast, die young“ life strategy allowed these species to recover quickly once water availability increased. Our results show how drought interacts with plant community composition to affect the soil water balance of semiarid ecosystems, information that could be integrated into global scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High fidelity simulations of contaminant dispersion in an urban environment with comparison to magnetic resonance imaging measurements

The dispersion of a contaminant in an urban environment has the potential to impact a large population of people. In this work, a complex urban canopy flow based on the Oklahoma City downtown business district circa 2003 is studied using Magnetic Resonance Imaging (MRI) and high-fidelity Large Eddy Simulations (LES). MRI is a novel experimental technique that can provide high-resolution measurements in four dimensions (three spatial and temporal) for lab scale models. The experiments and simulations use the same geometry and boundary conditions providing a one-to-one comparison of the two methods. Results are presented on the time-averaged velocity and concentration fields, the temporal dynamics of the concentration plumes for a transient release, and a novel Cloud Identification Algorithm that can separate plumes produced by periodic contaminant releases used for ensemble averaging over many releases. The MRI and LES datasets both include millions of measurement voxels and the comparisons highlight the complex 3D nature of the flow including strong vertical velocities in spanwise street canyons and flow acceleration in streamwise street canyons. The concentration fields are qualitatively similar albeit the LES shows larger dispersion. A quantitative analysis with performance measures compares the datasets pointwise and demonstrates that the two 3D datasets are similar with respect to many measures including a fractional bias of 0.02 (ideal=0.0), correlation coefficient of 0.87 (ideal = 1.0), and the fraction points within a factor of 2 is 0.98 (ideal = 1.0). Plume analysis compares the arrival and residence time of contaminant and is found to vary significantly with location within the urban environment with arrival times between 0 and 1.25 and differences within the contaminant cloud less than 10% at most locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A multiscale approach to analyze the effect of radial void fraction distributions on BWR neutronic lattice parameters

The goal of this study is to analyze the effect of radial void fraction distribution, considered at three degrees of fidelity, on lattice and 2-group homogenized cross sections. The novelty of this work lies in its use of experimentally-determined radial void fraction distributions which allows for fine-scale coolant density data with no predictive uncertainty and which could be prohibitively expensive to simulate over the range of operational parameters used in the experiments. The experimentally-determined radial void fraction distributions are also characterized using a statistical tool called a semi-variogram in order to determine the scale of continuity. Void fraction distributions are averaged at the lattice and subchannel level for comparison with the fine-scale model. Models averaged at the subchannel and lattice level show a difference in about 68% of the time. Also, by comparing 2-group homogenized cross-sections, the differences between the subchannel and homogeneous cases are measurable.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Multiscale simulations reveal TDP-43 molecular-level interactions driving condensation

The RNA-binding protein TDP-43 is associated with mRNA processing and transport from the nucleus to the cytoplasm. TDP-43 localizes in the nucleus as well as accumulating in cytoplasmic condensates such as stress granules. Aggregation and formation of amyloid-like fibrils of cytoplasmic TDP-43 are hallmarks of numerous neurodegenerative diseases, most strikingly present in >90% of amyotrophic lateral sclerosis (ALS) patients. If excessive accumulation of cytoplasmic TDP-43 causes, or is caused by, neurodegeneration is presently not known. In this work, we use molecular dynamics simulations at multiple resolutions to explore TDP-43 self- and cross-interaction dynamics. A full-length molecular model of TDP-43, all 414 amino acids, was constructed from select structures of the protein functional domains (N-terminal domain, and two RNA recognition motifs, RRM1 and RRM2) and modeling of disordered connecting loops and the low complexity glycine-rich C-terminus domain. All-atom CHARMM36m simulations of single TDP-43 proteins served as guides to construct a coarse-grained Martini 3 model of TDP-43. The Martini model and a coarser implicit solvent Cα model, optimized for disordered proteins, were subsequently used to probe TDP-43 interactions; self-interactions from single-chain full-length TDP-43 simulations, cross-interactions from simulations with two proteins and simulations with assemblies of dozens to hundreds of proteins. Our findings illustrate the utility of different modeling scales for accessing TDP-43 molecular-level interactions and suggest that TDP-43 has numerous interaction preferences or patterns, exhibiting an overall strong, but dynamic, association and driving the formation of biomolecular condensates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems

In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A fast computational framework for the design of solvent-based plastic recycling processes

Multicomponent plastics cannot be processed using mechanical recycling technologies, hindering efforts to deal with plastic waste. Multicomponent plastics include multilayer plastic films, which are widely used for food and healthcare packaging. Multilayer films combine several layers (potentially dozens) of different polymers to protect products from external factors (e.g., oxygen, water, temperature, shock, and light). Solvent-based separation processes have emerged as a promising alternative to recycle these complex materials. For instance, the Solvent-Targeted Recovery and Precipitation (STRAP TM ) process uses sequential solvent washes to selectively dissolve and separate constituent polymers from multicomponent plastic waste, including films. STRAP TM process design (separation sequence, type of solvents, and operating conditions) changes significantly depending on the design of the multilayer plastic film (e.g., number, types, and proportions of polymers). The ability to quickly quantify the economic and environmental benefits of diverse STRAP TM process designs is essential to accelerate the development of sustainable recycling processes and more recyclable multilayer film products. In this work, we present a fast computational framework that integrates molecular-scale models, process modeling, and techno-economic and life cycle analysis to quickly evaluate STRAP TM designs. The computational framework is general and can be used to study the processing of complex multilayer plastic waste streams that contain many layers. Furthermore, we highlight the different uses of the framework via targeted case studies.

Computational framework↗
DOE OSTI2023

A study of adhesive bonding in metal–metal, metal–CFRP, and CFRP–CFRP material combinations under shear deformation: Fracture morphologies and damage mechanisms

Safe design of adhesive joining in multi-materials in engineered structures requires the accumulation of numerous experimental data on the failure behavior of various adhesively-bonded material combinations under different loading conditions. The deep understanding of mechanical performance, fracturing morphologies, and main damage mechanisms is also quintessential for accelerating the development of proper physics-based and multi-scale models for assisting the design. Towards this goal, this work presents a comprehensive characterization of the failure behavior of adhesively-bonded metal–metal, metal–CFRP, and CFRP–CFRP material combinations under global shear deformation via single lap shear testing. Thanks to a synergistic combination of measurement methods by using Digital Imaging Correlation (DIC) and 3D optical profilometry, adhesive features on the adherend after failure were quantified and the main progressive damage mechanisms were identified. The characterization performed in this work provides quantitative data that contributes to a better understanding of shear failure in adhesive bonding across different bi-material combinations. Finally, the obtained results have practical implications, including the potential to enhance adhesive bonding design, identify failure causes in adhesive joints, and develop or validate computational models capable of capturing the observed behavior in various adhesively-bonded materials under global shear deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The role of moisture in MgCl 2 salt: A multiscale approach to TES performance

This study presents a comprehensive multiscale analysis to evaluate the influence of moisture on the thermal performance of thermal energy storage systems using magnesium chloride (MgCl 2 ) as the phase-changing material. The system uses graphite foam with 90% relative density to enhance thermal conductivity. The analysis includes thermal conductivity calculations and specific heat capacity for different hydrate phases of MgCl 2 : Anhydrous, Mono, Di, Tetra, and Hexa. These properties were evaluated for the first time using the phonon density of states from Density Functional Theory simulations. Results showed that thermal conductivity decreased, while specific heat capacity increased by a factor of two as the phase changed from anhydrous to hexahydrate. Meso-scale models were created to account for the anisotropy of graphite foam and property variations of the MgCl 2 hydrate phases. Asymptotic Expansion homogenization simulations determined the anisotropic thermal conductivity for all phases. This unique methodology improved simulation accuracy, which matched experimental data for anhydrous MgCl 2 . A parametric study examined various operating conditions and their effect on TES performance. It revealed that higher charging temperatures did not enhance exergy efficiency, but increased discharge mass flow rates improved it due to better heat transfer. Thermal performance evaluated by the exergy efficiency remained consistent across hydrate systems under the tested conditions. Furthermore, the study suggests that this uniformity is linked to missing key data, particularly latent heat and melting point for different hydrates. Overall, it highlights the importance of multiscale effects and accurate material properties in designing and optimizing TES systems.

Molten salt degradation↗
DOE OSTI2022

Computational design and engineering of an Escherichia coli strain producing the nonstandard amino acid para -aminophenylalanine

Introducing heterologous pathways into host cells constitutes a promising strategy for synthesizing nonstandard amino acids (nsAAs) to enable the production of proteins with expanded chemistries. However, this strategy has proven challenging, as the expression of heterologous pathways can disrupt cellular homeostasis of the host cell. Here, we sought to optimize the heterologous production of the nsAA para -aminophenylalanine (pAF) in Escherichia coli . First, we incorporated a heterologous pAF biosynthesis pathway into a genome-scale model of E. coli metabolism and computationally identified metabolic interventions in the host’s native metabolism to improve pAF production. Next, we explored different approaches of imposing these flux interventions experimentally and found that the upregulation of flux in the chorismate biosynthesis pathway through the elimination of feedback inhibition mechanisms could significantly raise pAF titers (~20-fold) while maintaining a reasonable pAF production-growth rate trade-off. Overall, this study provides a promising strategy for the biosynthesis of nsAAs in engineered cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Influence of Ag metal dispersion on the thermal conversion of ethanol to butadiene over Ag-ZrO 2 /SiO 2 catalysts

Atomistic scale models were developed and coupled with experimental investigation to deliver a functional understanding of catalytic activity and selectivity in the conversion of ethanol to 1,3-butadiene over Ag/ZrO 2 /SiO 2 . A detailed evaluation of the structural and electronic properties of the resultant catalyst models led to the identification of critical active sites of the catalyst. More importantly, the extent of Ag dispersion on the SiO 2 support and relative proximity to ZrO 2 were found to vary with the oxidation state of Ag and local coordination environment (Ag-O SiO2 ) allowing for critical control of ethanol conversion towards butadiene or ethylene. Simulations revealed that less dispersed or clustered Ag contain predominantly Ag 0 charge state and promote conversion of ethanol to ethylene. The well-dispersed Ag/ZrO 2 /SiO 2 catalyst instead contain a larger fraction of cationic Ag δ+ , and predominantly promote ethanol dehydrogenation and subsequent production of butadiene. The theoretical insights drawn were validated and confirmed experimentally using TEM, XRD and reactivity measurements demonstrating the effect of Ag dispersion on the selectivity of ethanol conversion.

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

Building energy efficiency and load flexibility optimization using phase change materials under futuristic grid scenario

This work investigates the energy savings and load flexibility capacity of phase change material (PCM) integrated into building envelope under a future energy generation scenario, where 80% of the energy load comes from renewable sources. Using community-scale modeling, we first determine the net thermal storage required to fully manage the demand variability at a utility grid, and then using whole-building simulations we optimize operating parameters - such as PCM thickness, latent heat, interior setpoint profile, PCM distribution, and heat transfer coefficient - to determine the optimal conditions required for maximum energy reduction and load flexibility without compromising occupants' thermal comfort. The optimal PCM-integrated envelope proposed in this study can provide annual load flexibility up to 33.6% and annual energy savings up to 10.8% in a lightweight residential building located in Baltimore, MD. This study is relevant given the increasing contributions of renewable energy in the total energy generation mix, leading to a significant time-imbalance between peak energy demand and peak energy production. While thermal energy storage using PCM is a recognized technique, there is no known prior study dedicated to examining the thermal performance of PCM-integrated envelope under future energy generation scenarios. This study bridges the research gap by investigating a practical way to implement PCMs in the buildings and maximize the energy efficiency as well as load flexibility related benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Numerical investigation and experimental validation of water condensation in the gas diffusion layer with different properties

Liquid water in porous media hinders the transport of reactant to catalyst layer, where the electrochemical reactions occur, which in turn, reduces performance and lifetime of a proton exchange membrane fuel cell (PEMFC). In this study, two types of gas diffusion layer (GDL) materials are used to study the two-phase saturation distribution in a PEMFC. The correlations between the effective and anisotropic transport properties and porosity of the two GDLs are solved by the pore scale model. In addition, the anisotropic liquid water permeability and the relationship between saturation pressure and capillary pressure is determined by using the Lattice-Boltzmann method. Fuel cell performance as well as liquid water distribution in the GDL using neutron radiography are obtained for validation. Under wet conditions, the cell with Freudenberg GDL performs better than that using Toray GDL, especially at high current densities. The results of the two-phase model simulation show that the peak water saturation for Toray GDL occurs in the catalyst layer and can reach 40%, while the peak water saturation for Freudenberg GDL occurs inside the GDL directly under the ribs and only reaches 25% saturation. The combined results provide key insights to enable high power density operation of a PEMFC through GDL material optimization.

42 ENGINEERING↗