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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 1,351 records · Page 75

Chemistry Informed Machine Learning-Based Heat Capacity Prediction of Solid Mixed Oxides

Knowing heat capacity is crucial for modeling temperature changes with the absorption and release of heat and for calculating the thermal energy storage capacity of oxide mixtures with energy applications. The current prediction methods (ab initio simulations, computational thermodynamics, and the Neumann–Kopp rule) are computationally expensive, not fully generalizable, or inaccurate. Machine learning has the potential of being fast, accurate, and generalizable, but it has been scarcely used to predict mixture properties, particularly for mixed oxides. Here, we demonstrate a method for the generalizable prediction of heat capacity of solid oxide pseudobinary mixtures using heat capacity data obtained from computational thermodynamics and descriptors from ab initio databases. Further, models trained through this workflow achieved an error (mean absolute error of 0.43 J mol –1 K –1 ) lower than the uncertainty in differential scanning calorimetry measurements, and the workflow can be extended to predict other properties derived from the Gibbs free energy and for higher-order oxide mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of Size and Shape on the Tolerances for Misalignment and Probabilities for Successful Oriented Attachment of Nanoparticles

Oriented attachment (OA) of nanoparticles is an important pathway of crystal growth, but tools for quantitatively modeling OA are lacking. Here we present several simple models that relate the probability of achieving OA to basic geometric parameters such as particle size, shape, and lattice periodicity. A Moiré-domain model is applied to understand twist-misorientations between parallel surfaces, and it predicts that the range of twist angles yielding perfect OA is inversely related to the width of the contact area. This is confirmed and further developed using a surface functional model, which predicts how crystallographic registration forces drive the emergence of complex orientational energy landscapes. The energy landscapes are predicted to possess local minima that can trap particles in imperfect alignments, and these local minima become deeper and more numerous as the contact area increases, making OA more challenging for large particles. Further, a second set of models is presented to understand the sequence of events by which two crystallographic faces become co-planer after collision. We use a ‘central force approximation’ to quantitatively predict the odds of attaining coalignment between various faces when particles collide with random misalignments, and we show that in the absence of biasing forces, the probability of attaining alignment on a given face is roughly proportional to its solid angle as viewed from the center of the particle. The model predicts that OA is most favorable between well-faceted particles and becomes exceedingly unlikely for large spherical particles that express many microfacets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selective Hydration of Rutile TiO 2 as a Strategy for Site-Selective Atomic Layer Deposition

In this report the feasibility of a site-selective hydration strategy that enables site-selective atomic layer deposition (ALD) is investigated among four rutile TiO 2 facets [(110), (100), (101) and (001)] and their most prevalent step edges. First-principles simulations of asymmetric slab models were utilized to create accurate representations of pristine terrace and step edge sites. The adsorption free energies for molecular and dissociative adsorption of H 2 O were calculated to evaluate this strategy as a viable route to step edge selectivity. We predict that selective hydroxylation is possible on the 110 and 001 step edges and further computationally evaluate three metalorganic ALD precursors for their compatibility with the selective hydration strategy. Experimental evidence for delayed nucleation of ALD on rutile (001), (110), and (100) TiO2 single crystals corroborates predictions of the dehydration of the surface and suggests the possibility of site-selective ALD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Model for Humidity-Mediated Diffusion on Aluminum Surfaces and Its Role in Accelerating Atmospheric Aluminum Corrosion

Bare aluminum metal surfaces are highly reactive, which leads to the spontaneous formation of a protective oxide surface layer. Because many subsequent corrosive processes are mediated by water, the structure and dynamics of water at the oxide interface are anticipated to influence corrosion kinetics. Here, using molecular dynamics simulations with a reactive force field, we model the behavior of aqueous aluminum metal ions in water adsorbed onto aluminum oxide surfaces across a range of ion concentrations and water film thicknesses corresponding to increasing relative humidity. We find that the structure and diffusivity of both the water and the metal ions depend strongly on the humidity of the environment and the relative height within the adsorbed water film. Aqueous aluminum ion diffusion rates in water films corresponding to a typical indoor relative humidity of 30% are found to be more than 2 orders of magnitude slower than self-diffusion of water in the bulk limit. Connections between metal ion diffusivity and corrosion reaction kinetics are assessed parametrically with a reductionist model based on a 1D continuum reaction–diffusion equation. Our results highlight the importance of incorporating the properties specific to interfacial water in predictive models of aluminum corrosion.

36 MATERIALS SCIENCE↗

Deconvoluting XPS Spectra of La-Containing Perovskites from First-Principles

Perovskite-based oxides are used in electrochemical CO 2 and H 2 O reduction in electrochemical cells due to their compositional versatility, redox properties and stability. However limited knowledge exists on the mechanisms driving these processes. Toward this understanding, herein we probe the core level binding energy shifts of water-derived adspecies (H, O, OH, H 2 O) as well as the adsorption of CO 2 on LaCoO 3 and LaNiO 3 and we correlate the simulated peaks with experimental Temperature Programmed X-ray Photoelectron Spectroscopy (TPXPS) results. We find the strong adsorption of such chemical species can affect the antiferromagnetic ordering of LaNiO 3 . The adsorption of such adspecies is further quantified through Bader and differential charge analyses. We find the higher O 1s core level binding energy peak for both LaCoO 3 and LaNiO 3 corresponds to adsorption of water-related species and CO 2 , while the lower energy peak is due to lattice oxygen. We further correlate these DFT-based core level O 1s binding energies with the TPXPS measurements to quantify the decrease of the O 1s contribution due to desorption of adsorbates and the apparent increase of the lattice oxygen (both bulk and surface) with temperature. Finally, we quantify the influence of adsorbates on the La 4d, Co 2p and the Ni 3p core level binding energy shifts. This work demonstrates how theoretically generated XPS data can be utilized to predict species-specific binding energy shifts to assist in the deconvolution of the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting solid state material platforms for quantum technologies

Semiconductor materials provide a compelling platform for quantum technologies (QT). However, identifying promising material hosts among the plethora of candidates is a major challenge. Therefore, we have developed a framework for the automated discovery of semiconductor platforms for QT using material informatics and machine learning methods. Different approaches were implemented to label data for training the supervised machine learning (ML) algorithms logistic regression, decision trees, random forests and gradient boosting. We find that an empirical approach relying exclusively on findings from the literature yields a clear separation between predicted suitable and unsuitable candidates. In contrast to expectations from the literature focusing on band gap and ionic character as important properties for QT compatibility, the ML methods highlight features related to symmetry and crystal structure, including bond length, orientation and radial distribution, as influential when predicting a material as suitable for QT.

36 MATERIALS SCIENCE↗

Strong stretching theory for pH-responsive polyelectrolyte brushes in large salt concentrations

Here, we develop a theory for describing the thermodynamics, configuration, and electrostatics of strongly-stretched, pH-responsive polyelectrolyte (PE) brushes in the presence of large salt concentrations. The aim of the paper, therefore, is to study the properties of a PE brush in a salt concentration regime (namely, large concentrations of several molars) that has been hitherto unexplored theoretically in the context of PE brushes but can be routinely encountered in molecular scale simulations of the problem. The brushes are modelled using our recently developed augmented Strong Stretching Theory (SST), while the effect of the presence of the large salt concentration is accounted for by including the contributions of three different types of non-Poisson–Boltzmann (non-PB) effects to the free energy description of the PE brush induced electric double layer (EDL). These non-PB effects are ionic non-mean-field ion–ion correlations, solvent polarization, and the finite size effect of the ions and water dipoles. We study the individual influences of these different effects and show that the ion–ion correlations and solvent polarization effect reduce the brush height which consequently enhances the monomer density and leads to an electrostatic potential distribution of the brush induced EDL that has a larger magnitude at near-wall locations and becomes zero at shorter distances from the wall. The finite size effect, on the other hand, increases the brush height and therefore, weakens the monomer density and leads to a smaller near-wall magnitude of the EDL potential that becomes zero at larger distances from the wall. In time, we consider the impact of all the three non-PB effects simultaneously and show that the ion–ion correlations and solvent polarization effect dominate the size effects and dictate the overall brush configuration and the EDL electrostatics. We also point out that the influence of all the three non-PB effects becomes the largest for a larger salt concentration and a smaller bulk pH. Finally, we compare our theoretical predictions with those obtained from our recently developed all-atom MD simulation model and obtain an excellent match.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High pressure chemical reactivity and structural study of the Na–P and Li–P systems

In this work, the Na–P and Li–P chemical systems were studied under pressure using synchrotron X-ray diffraction in a diamond anvil cell up to 20 GPa, combined with the AIRSS ab initio random structure searching technique. The results reveal an enhanced reactivity of both alkali metals with phosphorous at slightly elevated pressures. This enables the synthesis of Li 3 P and Na 3 P at room temperature (RT) starting from element precursors, bypassing the established chemical synthesis methods. Both compounds undergo a pressure-induced phase transition from the hexagonal Na 3 As-type structure (stable at ambient conditions) towards a Fm m (FCC) structure that remains stable up to 20 GPa. Attempts to synthesize compounds with higher alkali metal content (such as Li 5 P) using high-temperature and -pressure conditions (up to 2000+ K and 30 GPa), inspired by recent theoretical predictions, were not successful.

25 ENERGY STORAGE↗

Informing air–carbon ablation modeling with theoretical calculations of atomic oxygen and nitrogen interacting with carbon surfaces

To understand the gas–surface chemistry above the thermal protection system of a hypersonic vehicle, it is necessary to map out the kinetics of key elementary reaction steps. In this work, extensive periodic density functional theory (DFT) calculations are performed to elucidate the interaction of atomic oxygen and nitrogen with both the basal plane and edge sites of highly oriented pyrolytic graphite (HOPG). Reaction energies and barriers are determined for adsorption, desorption, diffusion, recombination, and several reactions. These DFT results are compared with the most recent finite-rate model for air–carbon ablation. Our DFT results corroborated some of the parameters used in the model but suggest that further refinement may be necessary for others. The calculations reported here will help to establish a predictive kinetic model for the complex reaction network present under hypersonic flight conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

RASER MRI: Magnetic resonance images formed spontaneously exploiting cooperative nonlinear interaction

The spatial resolution of magnetic resonance imaging (MRI) is limited by the width of Lorentzian point spread functions associated with the transverse relaxation rate 1/T 2 * . Here, we show a different contrast mechanism in MRI by establishing RASER (radio-frequency amplification by stimulated emission of radiation) in imaged media. RASER imaging bursts emerge out of noise and without applying radio-frequency pulses when placing spins with sufficient population inversion in a weak magnetic field gradient. Small local differences in initial population inversion density can create stronger image contrast than conventional MRI. This different contrast mechanism is based on the cooperative nonlinear interaction between all slices. On the other hand, the cooperative nonlinear interaction gives rise to imaging artifacts, such as amplitude distortions and side lobes outside of the imaging domain. Contrast mechanism and artifacts are explored experimentally and predicted by simulations on the basis of a proposed RASER MRI theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of an accelerator-based neutron source to prototype Mo-99 production, part I: A liquid LBE windowless target

In this article, Molybdenum-99 (Mo-99)’s decay product, technetium-99 (Tc-99 m), is one of the most critical isotopes for medical diagnostics. To provide U.S. domestic supply of Mo-99 without using high-enriched uranium (HEU), a subcritical uranium target assembly (UTA) is irradiated by an accelerator-based neutron source to create Mo-99 through fission. This study discusses the development of the accelerator-based neutron source. The high-energy electrons from the accelerator irradiate a liquid lead-bismuth eutectic (LBE) target to produce neutrons. Part I of this work focuses on numerical and experimental analysis towards the development of a liquid LBE windowless target. Unlike the existing windowless targets in literature, the current design creates a vertical free surface for a beam to irradiate. First, a hydrodynamic analysis of the LBE windowless target is performed. Simplified analytical calculations are assisted by 2D computational fluid dynamics (CFD) simulations to design the target, with the focus on eliminating recirculation zones and avoiding cavitation. With the optimized geometry, the experimental study is performed to investigate the flow hydrodynamics using liquid LBE. The experiments (1) compare pressure drop in the system to correlation predictions; (2) visualize the free surface liquid LBE flow from the beam view; (3) validate the LBE flow profile using temperature sensitive paint from the side view; and (4) validate the liquid LBE film thickness using gamma densitometer measurements. Second, the power handling capability of the designed windowless target is investigated. The divider plate in the current design is susceptible to overheating due to the thin LBE film in front. As LBE erosion and corrosion is likely to occur at an LBE velocity of 2.0 m/s and temperature above 500 °C, a power limit of 10 kW of beam power was established to prevent this corrosion from occurring, which is calculated by a Nusselt number correlation. The divider plate surface temperature at 10 kW agrees well with the 3D CFD simulation results. Part I demonstrates the fundamental physics in liquid LBE windowless target design and associated testing. A companion paper, Part II will demonstrate how to couple this windowless target into the Mo-99 production system, including an accelerator system operating under an ultra-high vacuum and the UTA cooled by water at room temperature.

43 PARTICLE ACCELERATORS↗

Spontaneous magnetization of collisionless plasma

Here we study within a fully kinetic framework the generation of “seed” magnetic fields through the Weibel instability, driven in an initially unmagnetized plasma by a large-scale shear force. We develop an analytical model that describes the development of thermal pressure anisotropy via phase mixing, the ensuing exponential growth of magnetic fields in the linear Weibel stage, and the saturation of the Weibel instability when the seed magnetic fields become strong enough to instigate gyromotion of particles and thereby inhibit their free-streaming. The predicted scaling dependencies of the saturated fields on key parameters (e.g., ratio of system scale to electron skin depth and forcing amplitude) are confirmed by two-dimensional and three-dimensional particle-in-cell simulations of an electron–positron plasma. This work demonstrates the spontaneous magnetization of a collisionless plasma through large-scale motions as simple as a shear flow and therefore has important implications for magnetogenesis in dilute astrophysical systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Overview of ASDEX upgrade results in view of ITER and DEMO

Experiments on ASDEX Upgrade (AUG) in 2021 and 2022 have addressed a number of critical issues for ITER and EU DEMO. A major objective of the AUG programme is to shed light on the underlying physics of confinement, stability, and plasma exhaust in order to allow reliable extrapolation of results obtained on present day machines to these reactor-grade devices. Concerning pedestal physics, the mitigation of edge localised modes (ELMs) using resonant magnetic perturbations (RMPs) was found to be consistent with a reduction of the linear peeling-ballooning stability threshold due to the helical deformation of the plasma. Conversely, ELM suppression by RMPs is ascribed to an increased pedestal transport that keeps the plasma away from this boundary. Candidates for this increased transport are locally enhanced turbulence and a locked magnetic island in the pedestal. The enhanced D-alpha (EDA) and quasi-continuous exhaust (QCE) regimes have been established as promising ELM-free scenarios. Here, the pressure gradient at the foot of the H-mode pedestal is reduced by a quasi-coherent mode, consistent with violation of the high-n ballooning mode stability limit there. This is suggestive that the EDA and QCE regimes have a common underlying physics origin. In the area of transport physics, full radius models for both L- and H-modes have been developed. These models predict energy confinement in AUG better than the commonly used global scaling laws, representing a large step towards the goal of predictive capability. A new momentum transport analysis framework has been developed that provides access to the intrinsic torque in the plasma core. In the field of exhaust, the X-Point Radiator (XPR), a cold and dense plasma region on closed flux surfaces close to the X-point, was described by an analytical model that provides an understanding of its formation as well as its stability, i.e., the conditions under which it transitions into a deleterious MARFE with the potential to result in a disruptive termination. With the XPR close to the divertor target, a new detached divertor concept, the compact radiative divertor, was developed. Here, the exhaust power is radiated before reaching the target, allowing close proximity of the X-point to the target. No limitations by the shallow field line angle due to the large flux expansion were observed, and sufficient compression of neutral density was demonstrated. With respect to the pumping of non-recycling impurities, the divertor enrichment was found to mainly depend on the ionisation energy of the impurity under consideration. In the area of MHD physics, analysis of the hot plasma core motion in sawtooth crashes showed good agreement with nonlinear 2-fluid simulations. This indicates that the fast reconnection observed in these events is adequately described including the pressure gradient and the electron inertia in the parallel Ohm’s law. Concerning disruption physics, a shattered pellet injection system was installed in collaboration with the ITER International Organisation. Thanks to the ability to vary the shard size distribution independently of the injection velocity, as well as its impurity admixture, it was possible to tailor the current quench rate, which is an important requirement for future large devices such as ITER. Progress was also made modelling the force reduction of VDEs induced by massive gas injection on AUG. The H-mode density limit was characterised in terms of safe operational space with a newly developed active feedback control method that allowed the stability boundary to be probed several times within a single discharge without inducing a disruptive termination. Regarding integrated operation scenarios, the role of density peaking in the confinement of the ITER baseline scenario (high plasma current) was clarified. The usual energy confinement scaling ITER98(p,y) does not capture this effect, but the more recent H20 scaling does, highlighting again the importance of developing adequate physics based models. Advanced tokamak scenarios, aiming at large non-inductive current fraction due to non-standard profiles of the safety factor in combination with high normalised plasma pressure were studied with a focus on their access conditions. A method to guide the approach of the targeted safety factor profiles was developed, and the conditions for achieving good confinement were clarified. Based on this, two types of advanced scenarios (‘hybrid’ and ‘elevated’

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Radiation Effects Model for Ultra-Thin Silicon Solar Cells

This work is focused on investigation of radiation effects in Ultra-Thin Silicon solar cells with a particular emphasis on electron irradiation. The study is motivated by the application of these solar cells, developed by Solestial, Inc., for powering space missions, including those led by NASA, the Department Of Defence (DOD), and commercial satellite missions. Our research encompasses both experimental and theoretical approaches, addressing unique challenges posed by ultra-thin solar cell technology that deviates from the traditional models. From the experimental point of view, the test structures were irradiated with 1 MeV electrons up to the fluence of 1E+15 e/cm$^{2}$. Radiation effects due to accumulated electron dose were noticed as a drop in open-circuit voltage (Voc). An analytical expression for modeling the Voc characteristic of the UT-Si cell after exposure to electron irradiation was formulated and subsequently compared with experimental data. The theoretical foundation of the proposed approach builds upon the Non-Ionising Energy Loss (NIEL) concept, a fundamental parameter in addressing radiation damage modelling and survivability predictions.

Fedoseyev, Alex↗

On the parameter combinations that matter and on those that do not: data-driven studies of parameter (non)identifiability

Abstract We present a data-driven approach to characterizing nonidentifiability of a model’s parameters and illustrate it through dynamic as well as steady kinetic models. By employing Diffusion Maps and their extensions, we discover the minimal combinations of parameters required to characterize the output behavior of a chemical system: a set of effective parameters for the model. Furthermore, we introduce and use a Conformal Autoencoder Neural Network technique, as well as a kernel-based Jointly Smooth Function technique, to disentangle the redundant parameter combinations that do not affect the output behavior from the ones that do. We discuss the interpretability of our data-driven effective parameters, and demonstrate the utility of the approach both for behavior prediction and parameter estimation. In the latter task, it becomes important to describe level sets in parameter space that are consistent with a particular output behavior. We validate our approach on a model of multisite phosphorylation, where a reduced set of effective parameters (nonlinear combinations of the physical ones) has previously been established analytically.

Evangelou, Nikolaos↗

Taylor-Expansion-Based Robust Power Flow in Unbalanced Distribution Systems: A Hybrid Data-Aided Method

Traditional power flow methods often adopt certain assumptions designed for passive balanced distribution systems, thus lacking practicality for unbalanced operation. moreover, their computation accuracy and efficiency are heavily subject to unknown errors and bad data in measurements or prediction data of distributed energy resources (ders). to address these issues, this paper proposes a hybrid data-aided robust power flow algorithm in unbalanced distribution systems, which combines taylor series expansion knowledge with a data-driven regression technique. the proposed method initiates a linearization power flow model to derive an explicitly analytical solution by modified taylor expansion. to mitigate the approximation loss that surges due to the der integration and bad data, we further develop a data-aided robust support vector regression approach to estimate the errors efficiently. comparative analysis in the 13-bus and 123-bus ieee unbalanced feeders shows that the proposed hybrid algorithm achieves superior computational efficiency, with guaranteed accuracy and robustness against outliers.

data-driven↗

Shifts in bacterial traits under chronic nitrogen deposition align with soil processes in arbuscular, but not ectomycorrhizal-associated trees

Nitrogen (N) deposition increases soil carbon (C) storage by reducing microbial activity. These effects vary in soil beneath trees that associate with arbuscular (AM) and ectomycorrhizal (ECM) fungi. Variation in carbon C and N uptake traits among microbes may explain differences in soil nutrient cycling between mycorrhizal associations in response to high N loads, a mechanism not previously examined due to methodological limitations. Here, we used quantitative Stable Isotope Probing (qSIP) to measure bacterial C and N assimilation rates from an added organic compound, which we conceptualize as functional traits. As such, we applied a trait-based approach to explore whether variation in assimilation rates of bacterial taxa can inform shifts in soil function under chronic N deposition. We show taxon-specific and community-wide declines of bacterial C and N uptake under chronic N deposition in both AM and ECM soils. N deposition-induced reductions in microbial activity were mirrored by declines in soil organic matter mineralization rates in AM but not ECM soils. Our findings suggest C and N uptake traits of bacterial communities can predict C cycling feedbacks to N deposition in AM soils, but additional data, for instance on the traits of fungi, may be needed to connect microbial traits with soil C and N cycling in ECM systems. In conclusion, our study also highlights the potential of employing qSIP in conjunction with trait-based analytical approaches to inform how ecological processes of microbial communities influence soil functioning.

59 BASIC BIOLOGICAL SCIENCES↗