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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Anion-dependent phase behavior of methylimidazolium-based ionic liquids mixed with water: Correlation between local molecular structure and mesoscale behaviors

The mesoscopic phase behavior of decylmethylimidazolium (C 10 mim) ionic liquids (ILs) bearing three monovalent anions—thiocyanate (SCN − ), nitrate (NO 3 − ), and chloride (Cl − )—mixed with water at relatively high IL contents (50–95 wt%) was investigated. Small-angle and wide-angle X-ray scattering (SAXS/WAXS) were employed to follow the evolution of both local and mesoscale structures across this composition range. In the absence of water, C 10 mimSCN and C 10 mimCl behaved as disordered liquids, whereas C 10 mimNO 3 spontaneously formed a hexagonally ordered cylindrical mesophase and displayed a sticky-solid macroscopic appearance. Upon addition of water, C 10 mimSCN remained a viscous liquid and only weakly ordered lamellar domains were observed. This limited ordering is attributed to the lack of hydrogen bonding and weak interaction energy between SCN − anions and C 10 mim + cations. In contrast, the trigonal-planar NO 3 − and point-like Cl − anions promoted the formation of well-defined hexagonal mesophases up to 35–45 wt% water. The formation of hydrogen bonding of the two anions with imidazolium ring protons likely enabled the creation of compact ion clusters that effectively exclude water molecules from the immediate vicinity of the IL aggregates. These findings demonstrate that the interaction energy between ion pairs dictate IL-water interactions and therefore control the transition from disordered liquids to ordered mesophases in IL/water mixtures with high IL contents. In conclusion, the combined SAXS/WAXS analysis reveals a correlation between local intermolecular structure and the emergence of mesoscopic order, providing a systematic framework for tailoring mesoscale structures in alkylimidazolium-based IL/water systems.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Modeling of Local BEAM Structure for Evaluation of MMOD Impacts to Support Development of a Health Monitoring System

This report summarizes initial modeling of the local response of the Bigelow Expandable Activity Module (BEAM) to micrometeorite and orbital debris (MMOD) impacts using a structural, non-linear, transient dynamic finite element code. Complementary test results for a local BEAM structure are presented for both hammer and projectile impacts. Review of these data provided guidance for the transient dynamic model development. The local model is intended to support predictions using the global BEAM model, described in a companion report. Two types of local models were developed. One mimics the simplified Soft-Goods (fabric envelop) part of the BEAM NASTRAN model delivered by the project. The second investigates through-the-thickness modeling challenges for MMOD-type impacts. Both the testing and the analysis summaries contain lessons learned and areas for future efforts.

Lyle, Karen H.↗
DOE OSTI2024

Impurity effects on local electronic structure of twisted bilayer cuprates

It has been recently proposed that a fully gapped d-wave superconducting phase emerges in twisted bilayer cuprates when twist angle is in the vicinity of 45°. By considering a twisted bilayer model with a moiré cell, we study the local electronic structure around a single-site impurity and impurity dimer in both topologically trivial and nontrivial superconducting states. Here we find that the topological nontrivial superconducting phase is robust against single scalar-potential impurity scattering but is very sensitive to the interlayer impurity dimer scattering, which avoids and enforces the creation of the subgap quasiparticle state. This behavior is intrinsic to the bilayer structure and topological nature, in contrast to the other types of impurities that inevitably bring subgap quasiparticle states. We expect that our results can contribute to the understanding of electronic properties of twisted bilayer cuprates systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2005

Constrained spectral clustering under a local proximity structure assumption

This work focuses on incorporating pairwise constraints into a spectral clustering algorithm. A new constrained spectral clustering method is proposed, as well as an active constraint acquisition technique and a heuristic for parameter selection. We demonstrate that our constrained spectral clustering method, CSC, works well when the data exhibits what we term local proximity structure.

domain knowledge↗
DOE OSTI2022

Beyond Local Solvation Structure: Nanometric Aggregates in Battery Electrolytes and their Effect on Electrolyte Properties

Electrolytes are an essential component of all electrochemical storage and conversion devices, such as batteries. In the history of battery development, the complex nature of electrolytes has often been a bottleneck. Fundamental knowledge of electrolyte systems encompasses elucidation of structure-property relationships of the solution species. Recently, nanometric aggregates have been observed in several classes of electrolytes, including super-concentrated, redox-flow, multivalent, polymer, and ionic liquid-based electrolytes. Compared with the well-studied local solvation structures such as contact ion pairs and solvent-separated ions, these aggregates impose unique effects on the ion distribution and transport both within bulk electrolytes and at electrode/electrolyte interfaces. This Perspective highlights the discovery of the aggregates in various battery electrolytes and their impact on electrolyte properties. We also present an outlook for future studies of this emerging field of nanometric aggregates and the need for the development of new experimental and computational tools to study their properties.

Yu, Zhou↗
DOE OSTI2024

Tuning Local Atomic Structures in MoS 2 Based Catalysts for Electrochemical Nitrate Reduction

In recent years, there has been a substantial surge in the investigation of transition-metal dichalcogenides such as MoS 2 as a promising electrochemical catalyst. Inspired by denitrification enzymes such as nitrate reductase and nitrite reductase, the electrochemical nitrate reduction catalyzed by MoS 2 with varying local atomic structures is reported. Further, it is demonstrated that the hydrothermally synthesized MoS 2 containing sulfur vacancies behaves as promising catalysts for electrochemical denitrification. With copper doping at less than 9% atomic ratio, the selectivity of denitrification to dinitrogen in the products can be effectively improved. X-ray absorption characterizations suggest that two sulfur vacancies are associated with one copper dopant in the MoS 2 skeleton. DFT calculation confirms that copper dopants replace three adjacent Mo atoms to form a trigonal defect-enriched region, introducing an exposed Mo reaction center that coordinates with Cu atom to increase N 2 selectivity. Apart from the higher activity and selectivity, the Cu-doped MoS 2 also demonstrates remarkably improved tolerance toward oxygen poisoning at high oxygen concentration. Finally, Cu-doped MoS 2 based catalysts exhibit very low specific energy consumption during the electrochemical denitrification process, paving the way for potential scale-up operations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hydrogen in disordered titania: connecting local chemistry, structure, and stoichiometry through accelerated exploration

Hydrogen incorporation in native surface oxides of metal alloys often controls the onset of metal hydriding, with implications for materials corrosion and hydrogen storage. A key representative example is titania, which forms as a passivating layer on a variety of titanium alloys for structural and functional applications. These oxides tend to be structurally diverse, featuring polymorphic phases, grain boundaries, and amorphous regions that generate a disparate set of unique local environments for hydrogen. Here, we introduce a workflow that can efficiently and accurately navigate this complexity. First, a machine learning force field, trained on ab initio molecular dynamics simulations, was used to generate amorphous configurations. Density functional theory calculations were then performed on these structures to identify local oxygen environments, which were compared against experimental observations. Second, to classify subtle differences across the disordered configuration space, we employ a graph-based sampling procedure. Finally, local hydrogen binding energies and hopping kinetics are computed using exhaustive density functional theory calculations on representative configurations. Here, we leverage this methodology to show that hydrogen binding energetics are described by local oxygen coordination, which in turn is affected by stoichiometry, and form the basis of hopping kinetics and diffusion. Together these results imply that hydrogen incorporation and transport in TiO x can be tailored through compositional engineering, with implications for improving the performance and durability of titanium-derived alloys in hydrogen environments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Machine Learning Full NMR Chemical Shift Tensors of Silicon Oxides with Equivariant Graph Neural Networks

The nuclear magnetic resonance (NMR) chemical shift tensor is a highly sensitive probe of the electronic structure of an atom and furthermore its local structure. Recently, machine learning has been applied to NMR in the prediction of isotropic chemical shifts from a structure. Current machine learning models, however, often ignore the full chemical shift tensor for the easier-to-predict isotropic chemical shift, effectively ignoring a multitude of structural information available in the NMR chemical shift tensor. Here we use an equivariant graph neural network (GNN) to predict full 29 Si chemical shift tensors in silicate materials. The equivariant GNN model predicts full tensors to a mean absolute error of 1.05 ppm and is able to accurately determine the magnitude, anisotropy, and tensor orientation in a diverse set of silicon oxide local structures. When compared with other models, the equivariant GNN model outperforms the state-of-the-art machine learning models by 53%. The equivariant GNN model also outperforms historic analytical models by 57% for isotropic chemical shift and 91% for anisotropy. The software is available as a simple-to-use open-source repository, allowing similar models to be created and trained with ease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Lattice and Local Electronic Structure Modulation Enables Ultra-Long-Life Li-Rich Cathode Materials

Effectively alleviating severe performance deterioration including rapid capacity decay and continuous voltage fading of Li-rich layered oxide (LLO) cathodes by suppressing the irreversible oxygen release and transition metal (TM) migration is a critical challenge during prolonged cycling. Herein, we report a Sb-doped LLO (SLLO) cathode with shortened TM oct –TM oct distance and modulated local electronic structure, which can significantly enhance the oxygen vacancy formation energy and TM migration energy barriers. Therefore, the SLLO cathode showcases an impressive energy density of 1052 Wh kg –1 at 0.2 C and an outstanding rate capability of 214 mAh g –1 at 5 C with a remarkable capacity retention of 79.2% even after 1000 cycles. It should be pointed out that it exhibits greatly enhanced voltage stability with an outstanding voltage retention of 86.2% after cycling 1600 times at 10 C. In conclusion, this work provides a prototype for significantly enhancing the reversibility in electrochemical reactions of high-capacity layered cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2023

The Local Electronic Structure of Supercritical CO 2 from X-ray Raman Spectroscopy and Atomistic-Scale Modeling

Supercritical CO 2 is encountered in several technical and natural systems related to biology, geophysics, and engineering. While the structure of gaseous CO 2 has been studied extensively, the properties of supercritical CO 2 , particularly close to the critical point, are not well-known. Here, in this work, we combine X-ray Raman spectroscopy, molecular dynamics simulations, and first-principles density functional theory (DFT) calculations to characterize the local electronic structure of supercritical CO 2 at conditions around the critical point. The X-ray Raman oxygen K-edge spectra manifest systematic trends associated with the phase change of CO 2 and the intermolecular distance. Extensive first-principles DFT calculations rationalize these observations on the basis of the 4sσ Rydberg state hybridization. X-ray Raman spectroscopy is found to be a sensitive tool for characterizing electronic properties of CO 2 under challenging experimental conditions and is demonstrated to be a unique probe for studying the electronic structure of supercritical fluids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Local spin structure in the layered van der Waals materials MnPS 𝑥 ⁢Se 3−𝑥

Two-dimensional (2D) layered materials, whether in bulk form or reduced to just a single layer, have potential applications in spintronics and capacity for advanced quantum phenomena. A prerequisite for harnessing these opportunities lies in gaining a comprehensive understanding of the spin behavior in 2D materials. The low dimensionality motivates an understanding of the spin correlations over a wide length scale, from local to long-range order. In this context, we focus on the magnetism in bulk MnPSe 3 and MnPS 3 , 2D layered van der Waals antiferromagnetic semiconductors. These materials have similar honeycomb Mn layers and magnetic ordering temperatures, but distinct spin orientations and exchange interactions. Here, we utilize neutron scattering to gain deeper insights into the local magnetic structures and spin correlations in the paramagnetic and ordered phases by systematically investigating a MnPS 𝑥 ⁢Se 3−𝑥 (𝑥 = 0, 1, 1.5, 2, 3) series of powder samples using total neutron scattering measurements. By employing magnetic pair distribution function analysis, we unraveled the short-range magnetic correlations in these materials and explored how the nonmagnetic anion S/Se mixing impacts the magnetic correlations. The results reveal that the magnetism can be gradually tuned through alteration of the nonmagnetic S/Se content, which tunes the atomic structure. The change in magnetic structure is also accompanied by a control of the magnetic correlation length within the 2D honeycomb layers. Complimentary inelastic neutron scattering measurements allowed a quantification of the change in the magnetic exchange interactions for the series and further highlighted the gradual evolution of spin interactions in the series MnPS 𝑥 ⁢Se 3−𝑥 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Orbital hybridisation effects in B2 phase Cr doped Co 2 MnAl

Here we investigate here the magnetic, transport, local structural and electronic properties of Co 2 Mn 1−x Cr x Al (x = 0, 0.05, 0.1 and 0.2). Our results show that all the compounds stabilise in B2 phase and are ferromagnets. The results reveal disorder at the structural and magnetic levels. X-ray absorption near edge structure (XANES) analysis reveal signature of antisite disorder between Mn and Al atoms with equal ratio. The electronic structure calculations suggest enhancement in the half metallicity, localisation of electrons at the Fermi level and an increment in density of states with doping. The combined results of electronic structure calculations and XANES studies suggest transfer of electrons to the Co site. The results of high temperature resistivity measurements suggest the conduction electrons are undergoing transition from delocalisation to weak localisation to activated behaviour with Cr doping. The extended x-ray absorption spectroscopic analysis shows that the local structure around Mn atom is different from the global structure as obtained from the x-ray diffraction results. The behaviour of the edge region is in line with the trend as obtained from the compositional analysis. We observe link between the hybridisation of 3d like states at the Mn, Cr sites with that at the Co site and the transport properties. This could help in understanding the unusual decrement in the lattice parameter with doping. These results reveal the role of local structure in understanding the physical properties of such systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Experimental evidence of runaway electron tail generation via localized helical structure in pellet-triggered tokamak disruptions

A novel detector, using stacked BGO crystals, is developed for runaway electron (REs) studies in the DIII-D tokamak. It is able to resolve fast dynamics of high-energy tail formation of REs with an ultra-high time resolution of ~1 μs. As a cost, the detector estimates the `effective' energy of a given shape of γ-ray spectra and sacrifices the energy resolution. In aid of the new measurement capability, a rapid, inhomogeneous growth of RE tail is observed in detail during a major disruption triggered by an argon pellet. It is found that both the population and energy of a well-confined RE tail significantly oscillate at the early period of the growth. The oscillation phase is locked to a slow rotating magnetohydrodynamic instability, which is briefly destabilized for only ~1 ms at the early period of the current quench. The oscillation ceases promptly, when the mode disappears. As a result, the data suggests that the high-energy RE tail is well-confined and accelerated via a localized helical structure in the plasma core.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Doping Metallic Grain Boundaries to Control Atomic Structure and Damage Tolerance

Grain boundaries often act as sites for crack and void nucleation during plastic deformation of metallic materials. While it is known that grain boundary character and structure can greatly influence this damage nucleation process, the current level of control over such details is limited. The objective of this project was to obtain a fundamental understanding of how metallic grain boundary structure can be controlled through intelligent doping, with the idea of inducing planned amorphous grain boundary phases or complexions. The effect of amorphous complexion structure on dislocation accommodation mechanisms was studied, to improve the field’s understanding of damage nucleation at a promising type of interface. Different microstructural descriptors were studied, as grain boundaries can have large variations and complexity of local structure, and influence the mechanical damage resistance of these features was tested. Nanocrystalline systems that contain amorphous grain boundary complexions were prioritized, as these have more extreme variations in interfacial structure and damage tolerance, with an emphasis on isolating the importance of complexion population (type, thickness, etc.), network topology, local structure, and local chemistry. This research used a combination of computational, experimental, and characterization techniques to isolate and understand the importance of nanoscale grain boundary structure and interfacial chemistry. Amorphous grain boundary complexions were found to clearly increase a material’s resistance to mechanical damage, with the local distribution of structural short-range order within the complexions found to be an important descriptor for damage and the proposed focus of future work in this area.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Integrating Machine Learning Potential and X-ray Absorption Spectroscopy for Predicting the Chemical Speciation of Disordered Carbon Nitrides

Precise determination of atomic structural information in functional materials holds transformative potential and broad implications for emerging technologies. Spectroscopic techniques, such as X-ray absorption near-edge structure (XANES), have been widely used for material characterization; however, extracting chemical information from experimental probes remains a significant challenge, particularly for disordered materials. We present an integrated approach that combines atomic simulations, data-driven techniques, and experimental measurements to investigate chemical speciation of amorphous carbon nitride systems as a case study. Here, we discuss the development of machine learning potentials that can efficiently explore the vast configuration space of amorphous carbon nitrides. By employing statistical methods, this structural database enables the elucidation of the most representative local structures and how they evolve with chemical compositions and density. Density functional theory simulations are used to establish a correlation between the local structure and spectroscopic signatures, which then serve as the basis for interpreting and extracting chemical content from experimental data. Although our framework is specifically demonstrated for XANES and carbon nitrides, the approach described herein is readily adaptable as applied to other experimental characterization probes and materials classes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tracking copper nanofiller evolution in polysiloxane during processing into SiOC ceramic

Polymer-derived ceramics (PDCs) remain at the forefront of research for a variety of applications including ultra-high-temperature ceramics, energy storage and functional coatings. Despite their wide use, questions remain about the complex structural transition from polymer to ceramic and how local structure influences the final microstructure and resulting properties. This is further complicated when nanofillers are introduced to tailor structural and functional properties, as nanoparticle surfaces can interact with the matrix and influence the resulting structure. The inclusion of crystalline nanofiller produces a mixed crystalline–amorphous composite, which poses characterization challenges. With this study, we aim to address these challenges with a local-scale structural study that probes changes in a polysiloxane matrix with incorporated copper nanofiller. Composites were processed at three unique temperatures to capture mixing, pyrolysis and initial crystallization stages for the pre-ceramic polymer. We observed the evolution of the nanofiller with electron microscopy and applied synchrotron X-ray diffraction with differential pair distribution function (d-PDF) analysis to monitor changes in the matrix's local structure and interactions with the nanofiller. The application of the d-PDF to PDC materials is novel and informs future studies to understand interfacial interactions between nanofiller and matrix throughout PDC processing.

Chemistry↗
NASA NTRS1975

The effects of localized damping on structural response

The effect of localized structural damping on the excitability of higher order normal modes of the large space telescope was investigated. A preprocessor computer program was developed to incorporate Voigt structural joint damping models in a NASTRAN finite-element dynamic model. A postprocessor computer program was developed to select critical modes for low-frequency attitude control problems and for higher frequency fine-stabilization problems. The mode selection is accomplished by ranking the flexible modes based on coefficients for rate gyro, position gyro, and optical sensors, and on image-plane motions due to sinusoidal or random power spectral density force and torque inputs.

Merchant, D. H.↗
DOE OSTI2025

Local orthorhombic phase in zirconium oxide nanocrystals: insights from X-ray pair distribution function analysis

Zirconium dioxide (ZrO 2 ) and hafnium dioxide (HfO 2 ) have emerged as promising alternatives to conventional ferroelectric materials. Understanding the crystal phases of these oxides under different conditions is crucial for optimizing their properties. There are several theories for the (anti)ferroelectric properties; however, comprehensive analysis, particularly at the local structure level, is lacking. In this study, we investigate the local structure of ZrO 2 nanocrystals using X-ray pair distribution function (PDF) analysis, revealing an unexpected local orthorhombic distortion irrespective of crystallite size. This finding suggests the potential existence of an intermediate orthorhombic phase during the microscopic switching pathway observed in previous studies. Additionally, we explore the influence of crystallite size and surface effects on the PDF. These results contribute to a deeper understanding of the structural dynamics in ZrO 2 and offer insights for the design of next-generation ferroelectric materials.

Pokratath, Rohan (ORCID:0000000268383939)↗