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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 145 records · Page 8

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NASA NTRS1982

New advances in the partial-reflection-drifts experiment using microprocessors

Improvements to the partial reflection drifts experiment are completed. The results of the improvements include real time processing and simultaneous measurements of the D region with coherent scatter. Preliminary results indicate a positive correlation between drift velocities calculated by both methods during a two day interval. The possibility now exists for extended observations between partial reflection and coherent scatter. In addition, preliminary measurements could be performed between partial reflection and meteor radar to complete a comparison of methods used to determine velocities in the D region.

Ruggerio, R. L.↗

NASA NTRS2021

Salvaging Data Records with Missing Data: Data Imputation using the Multivariate t Distribution

When doing multivariate data analysis, one commonobstacle is the presence of incomplete observations, i.e., observationsfor which one or more key fields are blank. Missing datais often countered by deleting entire observations that containmissing data. The negative effects of deleting entire observationsare multiple: deleting observations reduces sample size andcan also result in biased inferences even if data is missing atrandom. In addition, knowledge contained within incompleteobservations is knowledge lost when they are deleted– and theeffort spent collecting that knowledge is effort wasted. Data imputationmethods, or methods of statistically “filling-in” missingdata, can help combat small sample sizes by using the existinginformation in partially complete observations with the end goalof producing less biased and higher confidence inferences. Whena sample from a multivariate normal population is only partiallycomplete, and the missing data meets appropriate assumptions(missing at random), robust data imputation of the missing datacan be implemented with monotone data augmentation (MDA)using the multivariate t distribution.Missing data imputation is applied to data from the NASA InstrumentCost Model (NICM) using the MDA algorithm underthe assumption of having a multivariate t distribution with fixeddegrees of freedom. A sensitivity analysis to the degrees offreedom parameter is presented to demonstrate robustness ofthe multivariate t distribution when dealing with small samplesas compared to the multivariate normal distribution.

DiNicola, Michael↗

DOE OSTI2026

Mixed Nd 4+/3+ and Cluster Magnetism in Hexagonal Perovskite 12R-Ba 4 NdMn 3 O 12−γ

Hexagonal perovskite oxides with 12R stacking host well-separated face-sharing octahedral metal trimers with short metal–metal distances, leading in some cases to large degrees of magnetic frustration and cluster magnetism. Introducing magnetic ions in proximity to these trimers can influence the degree of frustration and cluster magnetism, but the extent to which the magnetism can be tuned by varying neighboring metal cations remains an open question. In this work, we test the impacts of using Nd in proximity to Mn trimers in the hexagonal perovskite 12R-Ba 4 NdMn 3 O 12−γ . Given this stoichiometry, Nd should assume the 4+ oxidation state with a spin state of S = 1, which would be the first realization of Nd 4+ in an oxide environment. Through detailed bulk magnetic, X-ray absorption spectroscopic, and powder neutron diffraction (PND) measurements, we find that Nd 4+ is realized in this material, but there is also partial reduction to Nd 3+ , which is charge-balanced by O vacancies. Magnetometry measurements indicate an antiferromagnetic ordering temperature T N ≈ 16 K, and PND measurements reveal a surprising collinear antiferromagnetic structure with magnetic space group Pc2/m (no. 10.49 in BNS notation), which has not previously been seen in this class of materials. Our results represent a comprehensive analysis of the structural, electronic, and magnetic properties of 12R-Ba 4 NdMn 3 O 12−γ , showing the first observation of partial Nd 4+ in an oxide, and demonstrating that this structural class can host a broad range of magnetic structures which are not easily predicted based on compositional trends.

14 SOLAR ENERGY↗

NASA NTRS1995

Interstellar propagation and electron capture processes of galactic cosmic ray heavy ions in space

The new information on galactic cosmic rays (GCR) derived from the Spacelab-3 cosmic ray experiment 'Anuradha' shows that at 25-125 MeV/N GCR sub-iron and iron (Z = 21-28) particles consists of a mixture of partially ionized and fully ionized ions. Computation of electron capture and loss cross sections in hydrogen in 1-50 MeV/N energy range are made for Fe, Cr, Ti and Ni. From these it is concluded that: (1) these GCR particles must have captured orbital electrons at energies of about 1-5 MeV/N and (2) these particles are then reaccelerated to 300-500 MeV/N most probably in interstellar medium by collision with SNR shock fronts. Some reacceleration may take place also in heliospheric boundary region. It is suggested that these observations of partially ionized GCR ions of about 100 MeV/N in Spacelab-3 provide a direct evidence of reacceleration of GCR.

Miltra, B.↗

NASA NTRS2014

Experimental Measurement of Frozen and Partially Melted Water Droplet Impact Dynamics

High-speed video of single frozen water droplets impacting a surface was acquired. The droplets diameter ranged from 0.4 mm to 0.9 mm and impacted at velocities ranging from 140 m/sec to 309 m/sec. The techniques used to freeze the droplets and launch the particles against the surfaces is described in this paper. High-speed video was used to quantify the ice accretion area to the surface for varying impact angles (30 deg, 45 deg, 60 deg), impacting velocities, and break-up angles. An oxygen /acetylene cross-flow flame used to ensure partial melting of the traveling frozen droplets is also discussed. A linear relationship between impact angle and ice accretion is identified for fully frozen particles. The slope of the relationship is affected by impact speed. Perpendicular impacts, i.e. 30 deg, exhibited small differences in ice accretion for varying velocities, while an increase of 60% in velocity from 161 m/sec to 259 m/sec, provided an increase on ice accretion area of 96% at an impact angle of 60 deg. The increase accretion area highlights the importance of impact angle and velocity on the ice accretion process of ice crystals. It was experimentally observed that partial melting was not required for ice accretion at the tested velocities when high impact angles were used (45 and 60 deg). Partially melted droplets doubled the ice accretion areas on the impacting surface when 0.0023 Joules were applied to the particle. The partially melted state of the droplets and a method to quantify the percentage increase in ice accretion area is also described in the paper.

Impact Dynamics↗

DOE OSTI2024

Operando study of HfO 2 atomic layer deposition on partially hydroxylated Si(111)

The introduction of atomic layer deposition (ALD), to the microelectronics industry has introduced a large number of new possible materials able to be deposited in layers with atomic thickness control. One such material is the high-κ oxide HfO 2 ; thermally stable and ultrathin HfO 2 films deposited by ALD are a significant contender to replace SiO 2 as the gate oxide in capacitor applications. We present a mechanistic study of the first deposition cycle of HfO 2 on the Si(111) surface using tetrakis(dimethylamido) hafnium (TDMAHf) and water as precursors using operando ambient pressure x-ray photoelectron spectroscopy. Here, we show that the hydroxylation of the clean Si(111) surface by residual water vapor, resulting in a 0.3 monolayer coverage of hydroxyls, leads to instantaneous full surface coverage of TDMAHf. The change in the atomic ratio of Hf to C/N found during the first deposition half-cycle, however, does not match the assumed immediate ligand loss through reaction with surface hydroxyls. One would expect an immediate loss of ligands, indicated by a Hf:N ratio of approximately 1:3 as TDMAHf deposits onto the surface; however, a Hf:N ratio of 1:3.6 is observed. The partial hydroxylation on the Si(111) surface leads to binding through the TDMAHf ligand N atoms resulting in both N and CH 3 being found remaining on the surface post water half-cycle. Although there is evidence of ligand exchange reactions occurring at Si–OH sites, it also seems that N binding can occur on bare Si, highlighting the complexity of the substrate/precursor reaction even when hydroxyls are present. Moreover, the initial low coverage of Si–OH/Si–H appears to severely limit the amount of Hf deposited, which we hypothesize is due to the specific geometry of the initial arrangement of Si–OH/Si–H on the rest- and adatoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1988

Novae as distance indicators

Nova shells are characteristically prolate with equatorial bands and polar caps. Failure to account for the geometry can lead to large errors in expansion parallaxes for individual novae. When simple prescriptions are used for deriving expansion parallaxes from an ensemble of randomly oriented prolate spheroids, the average distance will be too small by factors of 10 to 15 percent. The absolute magnitudes of the novae will be underestimated and the resulting distance scale will be too small by the same factors. If observations of partially resolved nova shells select for large inclinations, the systematic error in the resulting distance scale could easily be 20 to 30 percent. Extinction by dust in the bulge of M31 may broaden and shift the intrinsic distribution of maximum nova magnitudes versus decay rates. We investigated this possibility by projecting Arp's and Rosino's novae onto a composite B - 6200A color map of M31's bulge. Thirty two of the 86 novae projected onto a smooth background with no underlying structure due to the presence of a dust cloud along the line of sight. The distribution of maximum magnitudes versus fade rates for these unreddened novae is indistinguishable from the distribution for the entire set of novae. It is concluded that novae suffer very little extinction from the filamentary and patchy distribution of dust seen in the bulge of M31. Time average B and H alpha nova luminosity functions are potentially powerful new ways to use novae as standard candles. Modern CCD observations and the photographic light curves of M31 novae found during the last 60 years were analyzed to show that these functions are power laws. Consequently, unless the eruption times for novae are known, the data cannot be used to obtain distances.

Ford, Holland C.↗

DOE OSTI2023

Understanding Electrochemical Reaction Mechanisms of Sulfur in All‐Solid‐State Batteries through Operando and Theoretical Studies **

Abstract Due to its outstanding safety and high energy density, all‐solid‐state lithium‐sulfur batteries (ASLSBs) are considered as a potential future energy storage technology. The electrochemical reaction pathway in ASLSBs with inorganic solid‐state electrolytes is different from Li‐S batteries with liquid electrolytes, but the mechanism remains unclear. By combining operando Raman spectroscopy and ex situ X‐ray absorption spectroscopy, we investigated the reaction mechanism of sulfur (S 8 ) in ASLSBs. Our results revealed that no Li 2 S 8, Li 2 S 6, and Li 2 S 4 were formed, yet Li 2 S 2 was detected. Furthermore, first‐principles structural calculations were employed to disclose the formation energy of solid state Li 2 S n (1≤ n ≤8), in which Li 2 S 2 was a metastable phase, consistent with experimental observations. Meanwhile, partial S 8 and Li 2 S 2 remained at the full lithiation stage, suggesting incomplete reaction due to sluggish reaction kinetics in ASLSBs.

Cao, Daxian↗

DOE OSTI2023

Understanding Electrochemical Reaction Mechanisms of Sulfur in All‐Solid‐State Batteries through Operando and Theoretical Studies **

25 ENERGY STORAGE↗

DOE OSTI2020

Self-cleaning and de-pollution efficacies of photocatalytic architectural membranes

Photocatalytic self-cleaning “cool” roofs and walls can maintain high albedos, saving building cooling energy, reducing peak power demand, and mitigating the urban heat island effect. Other environmental benefits result from their de-polluting properties. Specimens from two different photocatalytic architectural membranes and a non-photocatalytic control were exposed alongside vertically, facing west, for two years at three California sites, and retrieved quarterly for testing. Photocatalytic materials showed excellent self-cleaning performance, retaining albedos of 0.74 – 0.75. By contrast, the control material exhibited an albedo loss of up to 0.10, with appreciable soiling observed by scanning electron microscopy. De-pollution capacity was assessed by quantifying NO removal and NOx deposition rates at 60 °C. Furthermore, efficacy varied with exposure location, weather conditions, and the nature of the photocatalytic material. Seasonal effects were observed, with partial inhibition during the dry season and reactivation during the rainy season.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Kernel learning backward SDE filter for data assimilation

In this paper, we develop a kernel learning backward SDE filter method to estimate the state of a stochastic dynamical system based on its partial noisy observations. A system of forward backward stochastic differential equations is used to propagate the state of the target dynamical model, and Bayesian inference is applied to incorporate the observational information. Further, to characterize the dynamical model in the entire state space, we introduce a kernel learning method to learn a continuous global approximation for the conditional probability density function of the target state by using discrete approximated density values as training data. Numerical experiments demonstrate that the kernel learning backward SDE is highly effective.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Simulations and Experiments Reveal Effect of Nanopores on Helium Diffusion in Quartz

The diffusion properties of noble gases in minerals are widely used to reconstruct the thermal histories of rocks. In this work, we combine density functional theory (DFT) calculations with laboratory experiments to investigate controls on helium diffusion in quartz. DFT calculations for perfect α-quartz predict substantially lower activation energies and frequency factors for helium diffusion than observed in laboratory experiments, especially in the [001] direction. These results imply that no helium could be retained in quartz at Earth surface temperatures, which conflicts with observations of partial cosmogenic 3 He retention over geologic time scales. Here, we implement a model of helium diffusion in α-quartz modulated by nanopore defects that disrupt energetically favorable diffusion pathways. In this model, we find that laboratory-determined diffusivities can be most closely reproduced when a helium atom encounters ~70 nanopore sites per million interstitial sites. The results of our model indicate that diffusion of helium in natural quartz, like other noble gases in other minerals, can be significantly modulated by extended defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Real-time observations of TRIP-induced ultrahigh strain hardening in a dual-phase CrMnFeCoNi high-entropy alloy

Abstract Strategies involving metastable phases have been the basis of the design of numerous alloys, yet research on metastable high-entropy alloys is still in its infancy. In dual-phase high-entropy alloys, the combination of local chemical environments and loading-induced crystal structure changes suggests a relationship between deformation mechanisms and chemical atomic distribution, which we examine in here in a Cantor-like Cr 20 Mn 6 Fe 34 Co 34 Ni 6 alloy, comprising both face-centered cubic ( fcc ) and hexagonal closed packed ( hcp ) phases. We observe that partial dislocation activities result in stable three-dimensional stacking-fault networks. Additionally, the fraction of the stronger hcp phase progressively increases during plastic deformation by forming at the stacking-fault network boundaries in the fcc phase, serving as the major source of strain hardening. In this context, variations in local chemical composition promote a high density of Lomer-Cottrell locks, which facilitate the construction of the stacking-fault networks to provide nucleation sites for the hcp phase transformation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Cascade of electronic transitions in magic-angle twisted bilayer graphene

Magic-angle twisted bilayer graphene exhibits a variety of electronic states, including correlated insulators, superconductors and topological phases. Understanding the microscopic mechanisms responsible for these phases requires determination of the interplay between electron–electron interactions and quantum degeneracy (the latter is due to spin and valley degrees of freedom). Signatures of strong electron–electron correlations have been observed at partial fillings of the flat electronic bands in recent spectroscopic measurements, and transport experiments have shown changes in the Landau level degeneracy at fillings corresponding to an integer number of electrons per moiré unit cell. However, the interplay between interaction effects and the degeneracy of the system is currently unclear. Here in this paper we report a cascade of transitions in the spectroscopic properties of magic-angle twisted bilayer graphene as a function of electron filling, determined using high-resolution scanning tunnelling microscopy. We find distinct changes in the chemical potential and a rearrangement of the low-energy excitations at each integer filling of the moiré flat bands. These spectroscopic features are a direct consequence of Coulomb interactions, which split the degenerate flat bands into Hubbard sub-bands. We find these interactions, the strength of which we can extract experimentally, to be surprisingly sensitive to the presence of a perpendicular magnetic field, which strongly modifies the spectroscopic transitions. The cascade of transitions that we report here characterizes the correlated high-temperature parent phase from which various insulating and superconducting ground-state phases emerge at low temperatures in magic-angle twisted bilayer graphene.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Structural transformation of metal oxo species within UiO-66 type metal–organic frameworks

Studying the coordination of actinide-based metal oxo clusters can provide valuable insights for nuclear energy technologies and radioactive waste containment. Metal–organic frameworks serve as a platform to directly interrogate the structure and properties of understudied actinide elements, including thorium. Examples of structural evolutions within Th oxo species within MOFs are rare yet relevant for nuclear waste speciation in solution. Herein, we report the serendipitous discovery of the structural evolution of Th-UiO-66 containing a hexanuclear Th node to a mononuclear Th(bdc) 2 (dmf) 2 upon the evaporation of solvent from the reaction. We observe a partial reversal of Th(bdc) 2 (dmf) 2 back to Th-UiO-66 upon hydrothermal treatment, indicating the complex dynamics of Th oxo species in solution. As a result, we report that isolated Ce-UiO-66 similarly transforms to a newly isolated 1D Ce III carboxylate chain MOF named NU-351 under the same conditions as Th-UiO-66, while Zr-UiO-66 and Hf-UiO-66 retain their structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Entanglement engineering of optomechanical systems by reinforcement learning

Entanglement is fundamental to quantum information science and technology, yet controlling and manipulating entanglement—so-called entanglement engineering—for arbitrary quantum systems remains a formidable challenge. There are two difficulties: the fragility of quantum entanglement and its experimental characterization. We develop a model-free deep reinforcement-learning (RL) approach to entanglement engineering, in which feedback control together with weak continuous measurement and partial state observation is exploited to generate and maintain desired entanglement. We employ quantum optomechanical systems with linear or nonlinear photon–phonon interactions to demonstrate the workings of our machine-learning-based entanglement engineering protocol. In particular, the RL agent sequentially interacts with one or multiple parallel quantum optomechanical environments, collects trajectories, and updates the policy to maximize the accumulated reward to create and stabilize quantum entanglement over an arbitrary amount of time. The machine-learning-based model-free control principle is applicable to the entanglement engineering of experimental quantum systems in general.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Multi-Modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation

As data collection and simulation capabilities advance, multi-modal learning, the task of learning from multiple modalities and sources of data, is becoming an increasingly important area of research. Surrogate models that learn from data of multiple auxiliary modalities to support the modeling of a highly expensive quantity of interest have the potential to aid outer loop applications such as optimization, inverse problems, or sensitivity analyses when multi-modal data are available. We develop two multi-modal Bayesian neural network surrogate models and leverage conditionally conjugate distributions in the last layer to estimate model parameters using stochastic variational inference (SVI). We provide a method to perform this conjugate SVI estimation in the presence of partially missing observations. Here, we demonstrate improved prediction accuracy and uncertainty quantification compared to unimodal surrogate models for both scalar and time series data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Transmission Data-Driven User-Defined Model for Inverter-based and Conventional Power Plants

Recent events in Odessa [1], [2] have shed light on the complexities of integrating large Inverter-Based Resource (IBR) plants with the transmission system, prompting NERC to stress continuous performance monitoring by transmission operators. Challenges such as plant control updates, IBR model revisions, Phase-locked loop loss of synchronism, and protection events have been identified, underscoring the need for enhanced monitoring protocols by regulatory bodies. The recent FERC 901 order underscores the importance of accurate data exchange regarding IBRs for reliability studies. However, limited access to IBR plant-related data hampers effective decision-making for transmission operators (TOP). This paper proposes a method for constructing data-driven User-Defined dynamic Models (UDM) for power plants for validating multiple-event data using field measurements from interconnection bus locations. The problem is formulated as a power plant model identification problem and a multi-task learning approach under partial input observability assumptions is proposed in this work. This approach aims to predict aggregated responses of conventional and IBR power plants during various dynamic physical events which is useful for planning studies under diverse disturbance conditions. Ultimately, this methodology emphasizes the importance of plant visibility to operators in addressing power system challenges, facilitating improved planning and operational studies.

Mahapatra, Kaveri [BATTELLE (PACIFIC NW LAB)]↗