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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Extending a 10‐node composite tetrahedral finite element for solid mechanics

Abstract We propose to extend the composite tetrahedral finite element first introduced by Thoutireddy et al. (2002) and recently reformulated by Ostien et al. (2016). We generalize the gradient operator and mass matrix to curved domains through analytical expressions weighted by subtetrahedra Jacobians. Optimal integration weights are constructed to increase the accuracy of Gaussian quadrature. We preserve the variational structure of the formulation through a new five‐field functional with additional, independent fields for the Jacobian and the pressure. This approach not only obviates volumetric locking but also yields symmetry. A deleterious soft mode, common to both the quadratic and composite tetrahedral element with constant pressure formulations is effectively stabilized through a novel convex energy penalty function. Numerous numerical examples spanning a patch test to the impact of a Taylor bar demonstrate the accuracy, robustness, and convergence of the extended composite tetrahedral element for application to structural metals.

Foulk III, James W.↗
DOE OSTI2022

Effect of microstructure on fatigue crack propagation in additive manufactured nickel-based superalloy Haynes 282: an experiment and crystal plasticity study

Haynes 282 is a γ' precipitation-strengthened nickel-based superalloy known for its exceptional high-temperature creep resistance and excellent fabricability. Recent advancements in powder-bed fusion-based additive manufacturing (PBF-AM) have enabled the fabrication of Haynes 282 with accurate, site-specific control of the grain orientation and morphology at the microscale. This ability opens up new avenues for microstructure design, to improve the material’s fatigue crack resistance and service life. This paper investigates the fatigue crack growth behavior of hybrid microstructure Haynes 282 fabricated via PBF-AM. Previous experiments revealed a higher crack propagation rate in the coarse columnar-grained microstructural regions when compared against fine-grained areas. Here, a strain gradient crystal plasticity model was adapted to study the fracture-related mechanical fields at the crack tip in the two microstructures. The simulation results showed a consistent influence of grain structure and texture on crack propagation, as was seen in the experiment. The model analysis revealed higher crack propagation driving force along crack direction in the coarse-grained sharply textured microstructure and higher driving force for crack kinking in fine-grained more diffusely textured microstructure, which is ascribed to the combined effect of yield stress, hardening rate, texture and grain morphology. The presented modeling approach will facilitate the development of the AM-based accurate microstructure design by deepening the fundamental study in AM-specific microstructure-properties relations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Transition from retrograde to prograde drift instabilities in a magnetron microdischarge

Rotating plasma structures, or “spokes,” in magnetized discharges characterized by perpendicular electric and magnetic fields have been seen in a growing number of studies and are believed to be the result of gradient-driven drift instabilities. Under certain conditions, we have shown the spoke’s rotation to be opposite to the E B direction, i.e., retrograde in its expected direction. Recently, we have linked such counter-intuitive rotation to a local inversion of the electric field. Here, we give further experimental evidence for this inversion and attempt to provide an explanation for a relatively distinct transition seen between retrograde and positive (prograde) drift. In the experiments, a partially magnetized plasma forms inside a magnetron device of mm radius operated with argon. Discharge current–voltage measurements are acquired for a range of argon fill pressure and inter-electrode spacing. We find two branches of operation—a low current branch of negative resistance, coinciding with the retrograde spoke rotation, and a higher current branch of positive resistance, coincident with prograde spoke rotation. We postulate that at low discharge currents, high magnetic field confinement leads to a large density gradient, causing more electron transport to the anode than that demanded by the external circuit. At higher currents, anomalous axial electron transport (across the magnetic field lines) becomes dominant, eliminating the conditions for field inversion. Here, the current thresholds for the field inversion are found to be sensitive to the argon pressure and inter-electrode spacing.

42 ENGINEERING↗
DOE OSTI2022

Quantum Machine Learning with SQUID

In this work we present the Scaled QUantum IDentifier (SQUID), an open-source framework for exploring hybrid Quantum-Classical algorithms for classification problems. The classical infrastructure is based on PyTorch and we provide a standardized design to implement a variety of quantum models with the capability of back-propagation for efficient training. We present the structure of our framework and provide examples of using SQUID in a standard binary classification problem from the popular MNIST dataset. In particular, we highlight the implications for scalability for gradient-based optimization of quantum models on the choice of output for variational quantum models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

High-Nickel Cathodes with Mechanical and Interfacial Robustness via Tailored Concentration Gradients for Stable Li-Ion Batteries

Here, we have developed a versatile mathematical framework integrated with an automated reactor system to design and reify highly customizable full concentration gradient (FCG) in high-nickel cathodes for advanced Li-ion batteries. This method provides precise and independent control of the average composition, slope, and curvature of FCGs, enabling the optimization of structural and mechanical properties of the cathode materials. We have showcased this method with Ni 0.8 Co 0.1 Mn 0.1 (OH) 2 precursors of controlled FCGs, which unlocked an optimized cathode with excellent cycling stability without crack formation after repeated cycles. This work opens up new possibilities for the design and manufacturing of advanced cathode materials, enabling safer, high-performance batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

The effects of turbulence on the flame structure and NO formation of ammonia turbulent premixed combustion at various equivalence ratios

Ammonia is carbon-free and is regarded as a potential fuel to address global warming issues. Here, in this work, three-dimensional direct numerical simulations (DNS) of ammonia/air turbulent premixed flames were performed to explore the influence of turbulence and equivalence ratio on the flame structure and NO formation characteristics. Two equivalence ratios were considered, i.e. Φ=0.9 and Φ=1.1. The general flame structures were presented and species distributions were examined. The NO mass fraction was found to be the highest in the product for the lean case and in the reaction zone for the rich case. The conditional mean values of species mass fractions and reaction rates were compared with those of the unstrained and strained laminar premixed flames to explore how well the laminar flame structures can approach those of the turbulent flame. The budget analysis of the species transport equations showed that turbulent diffusion plays an important role in species transport. The turbulent diffusivity D T was estimated using the gradient hypothesis based on the DNS data. Various laminar flame simulations with different diffusivities were carried out. It was shown that the conditional means of the DNS agree well with those of the laminar flames including D T in the transport property calculation. The global and local NO formation characteristics were investigated. It was found that the mean NO production conditioned on the progress variable is lower compared with the corresponding laminar flame in the rich case. However, the relative contributions from various NO pathways are rarely affected by turbulence. The NO mass fraction is higher in negative curvature regions compared with positive curvature regions of the flame surface for the rich case, which is due to the preferential diffusion of H 2 and other radicals and the enhanced NO pathways in negatively curved regions.

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

Salinization and sedimentation drive contrasting assembly mechanisms of planktonic and sediment‐bound bacterial communities in agricultural streams

Abstract Agriculture is the most dominant land use globally and is projected to increase in the future to support a growing human population but also threatens ecosystem structure and services. Bacteria mediate numerous biogeochemical pathways within ecosystems. Therefore, identifying linkages between stressors associated with agricultural land use and responses of bacterial diversity is an important step in understanding and improving resource management. Here, we use the Mississippi Alluvial Plain (MAP) ecoregion, a highly modified agroecosystem, as a case study to better understand agriculturally associated drivers of stream bacterial diversity and assembly mechanisms. In the MAP, we found that planktonic bacterial communities were strongly influenced by salinity. Tolerant taxa increased with increasing ion concentrations, likely driving homogenous selection which accounted for ~90% of assembly processes. Sediment bacterial phylogenetic diversity increased with increasing agricultural land use and was influenced by sediment particle size, with assembly mechanisms shifting from homogenous to variable selection as differences in median particle size increased. Within individual streams, sediment heterogeneity was correlated with bacterial diversity and a subsidy‐stress relationship along the particle size gradient was observed. Planktonic and sediment communities within the same stream also diverged as sediment particle size decreased. Nutrients including carbon, nitrogen, and phosphorus, which tend to be elevated in agroecosystems, were also associated with detectable shifts in bacterial community structure. Collectively, our results establish that two understudied variables, salinity and sediment texture, are the primary drivers of bacterial diversity within the studied agroecosystem, whereas nutrients are secondary drivers. Although numerous macrobiological communities respond negatively, we observed increasing bacterial diversity in response to agricultural stressors including salinization and sedimentation. Elevated taxonomic and phylogenetic bacterial diversity likely increases the probability of detecting community responses to stressors. Thus, bacteria community responses may be more reliable for establishing water quality goals within highly modified agroecosystems that have experienced shifting baselines.

DeVilbiss, Stephen E.↗
DOE OSTI2022

Sensitivity of the electronic and magnetic structures of cuprate superconductors to density functional approximations

Abstract We discuss the crystal, electronic, and magnetic structures of La 2− x Sr x CuO 4 (LSCO) for x = 0.0 and x = 0.25 employing 13 density functional approximations, representing the local, semi-local, and hybrid exchange-correlation approximations within the Perdew–Schmidt hierarchy. The meta-generalized gradient approximation (meta-GGA) class of functionals is found to perform well in capturing the key properties of LSCO, a prototypical high-temperature cuprate superconductor. In contrast, the localspin-density approximation, GGA, and the hybrid density functional fail to capture the metal-insulator transition under doping.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Range-separated thermal hybrid exchange-correlation density functional for accurate band-gap calculations of warm dense matter

Here, in this study, we present a range-separated thermal hybrid exchange-correlation (XC) functional, termed RS-KDT0, which provides highly accurate band-gap predictions at elevated temperature while reducing the computational cost relative to thermal global hybrid functionals. At zero temperature, RS-KDT0 recovers the widely used ground-state range-separated hybrid functional HSE06. To assess its performance across temperature regimes, we conducted static calculations of electronic pressure, band gaps, and band structures. RS-KDT0 exhibits the same level of accuracy as HSE06 in the low-temperature regime and demonstrates improved agreement with finite-temperature GW calculations at elevated temperatures when compared to other thermal XC functionals such as the generalized gradient approximation (GGA)-level KDT16 and the global hybrid KDT0.

density functional theory↗
DOE OSTI2024

A Modeling framework for flocculated cohesive sediment transport in the current bottom boundary layer

Cohesive sediment transport, where its settling velocity is controlled by the flocculation process, is a crucial component in determining biochemical cycles, fate of pollutants, and morphodynamics in many aquatic ecosystems. In this study, a modeling framework is presented to investigate how flocculation influences cohesive sediment transport in the current bottom boundary layer in dilute conditions, consistent with the calibration range of the flocculation model. From a local analysis of floc dynamics in homogenous turbulence, we identify that the floc size distribution is mainly controlled by floc cohesion and yield strength. The uncertainty in fractal dimension plays a minor role for the floc size but it influences the resulting floc density and settling velocity. The transport analysis in the current boundary layer shows that the flocculation process alters the vertical distribution of the settling velocity and hence the sediment concentration with a strong dependence on cohesion, floc yield strength, and floc structure. When the flocs are more susceptible to breaking, a well-mixed concentration profile is obtained. In contrast, for flocs with higher cohesion or yield strength, higher concentration with a sharp gradient is observed close to the bed. Overall, the settling velocity exhibits a low vertical variability within 20 % of the depth-averaged value except near the bed. Further, this suggests that using a depth-averaged settling velocity yields acceptable predictions of the sediment concentration profiles, especially for flocs with lower cohesion.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Interpretation of high-harmonic fast-wave propagation in the scrape-off layer of NSTX-U as a geometrically bounded-waveguide mode

This paper revisits the onset of high-harmonic fast-wave (HHFW) propagation in the scrape-off layer (SOL) plasma of the NSTX/NSTX-U spherical tokamak, motivated by past HHFW heating and current drive experiments and modelling. Previously, the fast-wave propagation in the SOL was correlated with the opening (suppression) of the fast-wave right-hand cutoff layer in front of the antenna. In this work, the SOL propagation is interpreted as a geometric waveguide mode guided by the SOL geometry, whose radial width can be comparable to the wave’s perpendicular wavelength in the HHFW regime. A two-dimensional circular model is first employed using full-wave solvers to characterise the poloidal eigenmode structures and to clarify their relationship to annulus resonance. By progressively adding a tokamak-like magnetic-field configuration, starting from a uniform axial field, the effects of magnetic-field gradients and pitch on the SOL waveguide mode are characterised. The poloidal mode numbers supported by the SOL plasma agree well with analytic estimates, indicating that an anisotropic plasma in a bounded geometry selectively supports and amplifies the resonant poloidal mode number. Additionally, two-dimensional axisymmetric NSTX-U simulations demonstrate that the SOL eigenmode features identified in the circular model persist in the experimentally relevant configurations. A control approach based on lengthening the wave perpendicular wavelength relative to the SOL width, including a higher magnetic (B)-field operation, is discussed. The analysis here shows the key role of a bounded geometry in interpreting HHFW eigenmode coupling and propagation in the NSTX-U SOL plasma.

plasma heating↗
DOE OSTI2024

Force-Free Identification of Minimum-Energy Pathways and Transition States for Stochastic Electronic Structure Theories

Here, the accurate mapping of potential energy surfaces (PESs) is crucial to our understanding of the numerous physical and chemical processes mediated by atomic rearrangements, such as conformational changes and chemical reactions, and the thermodynamic and kinetic feasibility of these processes. Stochastic electronic structure theories, e.g., Quantum Monte Carlo (QMC) methods, enable highly accurate total energy calculations that in principle can be used to construct the PES. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms for minimum-energy pathway (MEP) and transition state (TS) identification, such as the nudged elastic band (NEB) algorithm and its climbing image formulation. Here, we present strategies that utilize the surrogate Hessian line-search method, previously developed for QMC structural optimization, to efficiently identify MEP and TS structures without requiring force calculations at the level of the stochastic electronic structure theory. By modifying the surrogate Hessian algorithm to operate in path-orthogonal subspaces and at saddle points, we show that it is possible to identify MEPs and TSs by using a force-free QMC approach. We demonstrate these strategies via two examples, the inversion of the ammonia (NH 3 ) molecule and the nucleophilic substitution (S N 2) reaction F – + CH 3 F → FCH 3 + F – . We validate our results using Density Functional Theory (DFT)- and Coupled Cluster (CCSD, CCSD(T))-based NEB calculations. We then introduce a hybrid DFT-QMC approach to compute thermodynamic and kinetic quantities, free energy differences, rate constants, and equilibrium constants that incorporates stochastically optimized structures and their energies, and show that this scheme improves upon DFT accuracy. Our methods generalize straightforwardly to other systems and other high-accuracy theories that similarly face challenges computing energy gradients, paving the way for highly accurate PES mapping, transition state determination, and thermodynamic and kinetic calculations at significantly reduced computational expense.

Iyer, Gopal R.↗
DOE OSTI2020

Temperature dependence of nuclear quantum effects on liquid water via artificial neural network model based on SCAN meta-GGA functional

We investigate the temperature dependence of nuclear quantum effects (NQEs) on structural and dynamic properties of liquid water by training a neural network force field using first-principles molecular dynamics (FPMD) based on the strongly constrained and appropriately normed meta-generalized gradient approximation exchange-correlation approximation. The FPMD simulation based on density functional theory has become a powerful computational approach for studying a wide range of condensed phase systems. However, its large computational cost makes it difficult to incorporate NQEs in the simulation and investigate temperature dependence of various properties. To circumvent this difficulty, we use an artificial neural network model and employ the thermostatted ring polymer MD approach for studying the temperature dependence of NQEs on various properties. The NQEs generally bring the radial distribution functions closer to the experimental measurements. Translational diffusivity and rotational dynamics of water molecules are both slowed down by the NQEs. The competing inter-molecular and intra-molecular quantum effects on hydrogen bonds, as discussed by Habershon, Markland, and Manolopoulos [J. Chem. Phys. 131(2), 024501 (2019)], can explain the observed temperature dependence of the NQEs on the dynamical properties in our simulation.

Yao, Yi (ORCID:0000000299576979)↗
DOE OSTI2022

Cation reordering instead of phase transitions: Origins and implications of contrasting lithiation mechanisms in 1D ζ- and 2D α-V 2 O 5

Substantial improvements in cycle life, rate performance, accessible voltage, and reversible capacity are required to realize the promise of Li-ion batteries in full measure. Here, we have examined insertion electrodes of the same composition (V 2 O 5 ) prepared according to the same electrode specifications and comprising particles with similar dimensions and geometries that differ only in terms of their atomic connectivity and crystal structure, specifically two-dimensional (2D) layered α-V 2 O 5 that crystallizes in an orthorhombic space group and one-dimensional (1D) tunnel-structured ζ-V 2 O 5 crystallized in a monoclinic space group. By using particles of similar dimensions, we have disentangled the role of specific structural motifs and atomistic diffusion pathways in affecting electrochemical performance by mapping the dynamical evolution of lithiation-induced structural modifications using ex situ scanning transmission X-ray microscopy, operando synchrotron X-ray diffraction measurements, and phase-field modeling. We find the operation of sharply divergent mechanisms to accommodate increasing concentrations of Li-ions: a series of distortive phase transformations that result in puckering and expansion of interlayer spacing in layered α-V 2 O 5 , as compared with cation reordering along interstitial sites in tunnel-structured ζ-V 2 O 5 . By alleviating distortive phase transformations, the ζ-V 2 O 5 cathode shows reduced voltage hysteresis, increased Li-ion diffusivity, alleviation of stress gradients, and improved capacity retention. The findings demonstrate that alternative lithiation mechanisms can be accessed in metastable compounds by dint of their reconfigured atomic connectivity and can unlock substantially improved electrochemical performance not accessible in the thermodynamically stable phase.

25 ENERGY STORAGE↗
DOE OSTI2023

How fluctuation intensity flux drives SOL expansion

Abstract Predictions of heat load widths λ q based on particle orbits alone are very pessimistic. This paper shows that pedestal peeling-ballooning (P-B) magnetohydrodynamic (MHD) turbulence broadens the stable scrape-off layer (SOL) by the transport, or spreading, of fluctuation energy from the pedestal. λ q is seen to increase with Γ ε , the fluctuation energy density flux. We elucidate the fundamental physics of the spreading process. Γ ε increases with pressure fluctuation correlation length. P-B turbulence is seen to be especially effective at spreading, on account of its large effective mixing length. Spreading is shown to be a multiscale process, which is enhanced by the synergy of large and small-scale modes. Pressure fluctuation skewness correlates well with the spreading flux–with the zero crossing of skewness and Γ ε spatially coincident–suggesting the role of coherent fluctuation structures and the presence of intermittency in λ q broadening. λ q ∼ B p − 1 scaling persists for the broadened SOL. We show that the spreading flux increases for increasing pedestal pressure gradient ∇ P 0 and for decreasing pedestal collisionality υ ped ∗ . This trend is due to the dominance of peeling modes for large ∇ P 0 and low υ ped ∗ . Ultimately, we see that a state of weak MHD turbulence, as for small ELMs, is very attractive for heat load management. Our findings have transformative implications for future fusion reactor designs and call for experimental investigations to validate the observed trends.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Shock-induced metallization of polystyrene along the principal Hugoniot investigated by advanced thermal density functionals

To date, none of the ab-initio molecular dynamics simulations of polystyrene, often used as an ablator material in inertial confinement fusion targets, with the standard ground-state exchange-correlation (XC) functional in density-functional theory can satisfactorily agree with experiments in terms of reflectivity measurements. Here, we use recently developed thermal strongly constrained and appropriately normed Laplacian dependent meta-generalized gradient approximation XC density functional (T-SCAN-L) and thermal hybrid XC density functional (KDT0) to show that the inclusion of thermal and inhomogeneity effects is crucial for accurate prediction of structural evolution and corresponding insulator-metal transition (IMT) during shock compression. Optical reflectivity calculated as an indicator of IMT is in perfect accord with experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Can Simple Machine Learning Tools Extend and Improve Temperature-Based Methods to Infer Streambed Flux?

Temperature-based methods have been developed to infer 1D vertical exchange flux between a stream and the subsurface. Current analyses rely on fitting physically based analytical and numerical models to temperature time series measured at multiple depths to infer daily average flux. These methods have seen wide use in hydrologic science despite strong simplifying assumptions including a lack of consideration of model structural error or the impacts of multidimensional flow or the impacts of transient streambed hydraulic properties. We performed a “perfect-model experiment” investigation to examine whether regression trees, with and without gradient boosting, can extract sufficient information from model-generated subsurface temperature time series, with and without added measurement error, to infer the corresponding exchange flux time series at the streambed surface. Using model-generated, synthetic data allowed us to assess the basic limitations to the use of machine learning; further examination of real data is only warranted if the method can be shown to perform well under these ideal conditions. We also examined whether the inherent feature importance analyses of tree-based machine learning methods can be used to optimize monitoring networks for exchange flux inference.

54 ENVIRONMENTAL SCIENCES↗