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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The AWAKEN wind farm benchmark, Part 2: Modeling results

Accurately modeling wind farm performance in complex atmospheric flows remains a challenge. This paper presents the modeling results of the American WAKE experimeNt (AWAKEN) wind farm benchmark, a collaborative effort involving 16 research groups from academia and industry within the International Energy Agency Wind Technology Collaboration Programme Task 57. The study evaluates a diverse suite of simulation tools, ranging from fast-running engineering wake models to high-fidelity large-eddy simulations, against a diurnal case study observed during the AWAKEN campaign. The benchmark utilized a three-phase structure to progressively assess model performance as observational data availability increased. Initial blind predictions showed that higher-fidelity models did not uniformly outperform simpler simulation tools. A distinct spatial bias was observed where models struggled to resolve the interplay between a low-level jet, wakes, and terrain-induced flow acceleration. In subsequent phases, leveraging additional measurements for model improvement led to a reduction in mean absolute error across the model ensemble; however, this effect was most pronounced in engineering wake models, where targeted calibration reduced error by up to 40~\%. Overall, the study demonstrates that inflow characterization remains a primary prerequisite for accuracy, particularly for models relying on coarse forcing datasets. While the limited ability to resolve local terrain-flow interactions under single-day conditions represent a recognized constraint, the overall findings on wake modeling and real-world validation still provide valuable guidance for model application and for mitigating this limitation.

Bodini, Nicola↗
DOE OSTI2023

Enhanced thermoelectric performance of SnSe by controlled vacancy population

Abstract The thermoelectric performance of SnSe strongly depends on its low-energy electron band structure that provides high density of states in a narrow energy window due to the multi-valley valence band maximum (VBM). Angle-resolved photoemission spectroscopy measurements, in conjunction with first-principles calculations, reveal that the binding energy of the VBM of SnSe is tuned by the population of Sn vacancy, which is determined by the cooling rate during the sample growth. The VBM shift follows precisely the behavior of the thermoelectric power factor, while the effective mass is barely modified upon changing the population of Sn vacancies. These findings indicate that the low-energy electron band structure is closely correlated with the high thermoelectric performance of hole-doped SnSe, providing a viable route toward engineering the intrinsic defect-induced thermoelectric performance via the sample growth condition without an additional ex-situ process. Graphical Abstract

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Stabilized Oxygen Vacancy Chemistry toward High-Performance Layered Oxide Cathodes for Sodium-Ion Batteries

Anionic redox has emerged as a transformative paradigm for high-energy layered transition-metal (TM) oxide cathodes, but it is usually accompanied by the formation of anionic redox-mediated oxygen vacancies (OVs) due to irreversible oxygen release. Additionally, external factor-induced OVs (defined as intrinsic OVs) also play a pivotal role in the physicochemical properties of layered TM oxides. However, an in-depth understanding of the interplay between intrinsic and anionic redox-mediated OVs and the corresponding regulation mechanism of the dynamic evolution of OVs is still missing. Herein, we disclose the strong interrelationship between these OVs and demonstrate that the presence of intrinsic OVs in the TMO2 layers could induce weak integrity of the TM-O frameworks and unlock additional diffusion paths to trigger the generation and migration of anionic redox-mediated OVs. Accordingly, an OV stabilization strategy is proposed by deliberately introducing high-valence Nb5+, which could serve as an important building block in anchoring the oxygen sublattice and preventing the formation of a percolating OV migration network, thereby suppressing the formation/diffusion of anionic redox-mediated OVs. Consequently, superb structural integrity and improved electrochemical performance with reversible anionic redox chemistry are achieved. This work advances our understanding of the role of OVs for developing high-performance energy storage systems utilizing anionic redox.

anionic redox↗
DOE OSTI2025

The structure of liquid carbon elucidated by in situ X-ray diffraction

Carbon has a central role in biology and organic chemistry, and its solid allotropes provide the basis of much of our modern technology. However, the liquid form of carbon remains nearly uncharted, and the structure of liquid carbon and most of its physical properties are essentially unknown. But liquid carbon is relevant for modelling planetary interiors and the atmospheres of white dwarfs, as an intermediate state for the synthesis of advanced carbon materials, inertial confinement fusion implosions, hypervelocity impact events on carbon materials and our general understanding of structured fluids at extreme conditions. Here we present a precise structure measurement of liquid carbon at pressures of around 1 million atmospheres obtained by in situ X-ray diffraction at an X-ray free-electron laser. Our results show a complex fluid with transient bonding and approximately four nearest neighbours on average, in agreement with quantum molecular dynamics simulations. The obtained data substantiate the understanding of the liquid state of one of the most abundant elements in the universe and can test models of the melting line. The demonstrated experimental abilities open the path to performing similar studies of the structure of liquids composed of light elements at extreme conditions.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Harnessing Neural Networks for Elucidating X-ray Absorption Structure–Spectrum Relationships in Amorphous Carbon

Improved understanding of structural and chemical properties through local experimental probes, such as X-ray absorption near-edge structure (XANES) spectroscopy, is crucial for the understanding and design of functional materials. In recent years, significant advancements have been made in the development of data science approaches for the automated interpretation of XANES structure–spectrum relationships. However, existing studies have primarily focused on crystalline solids and small molecules, while fewer efforts have been devoted to disordered systems. Thus, in this work, we demonstrate the development of neural network models for predicting and interpreting XANES spectra of amorphous carbon (a-C) from local structural descriptors. Comparison between different structural descriptors expectedly shows that the inclusion of both bond length and bond angle information is necessary for an accurate prediction of the spectra. Among the descriptors considered in this work, we find that the local many-body tensor representation yields the highest accuracy and greatest interpretability so that it can be leveraged to understand the importance of structural motifs in determining XANES spectra. Furthermore, we also discuss performance of neural network models for predicting both local structure features, such as bond lengths and bond angles, and global chemical composition, such as the sp:sp 2 :sp 3 ratio.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomically dispersed zeolite-supported rhodium complex: Selective and stable catalyst for acetylene semi-hydrogenation

In this study, supported rhodium catalysts are known to be unselective for semi-hydrogenation reactions. Here, by tuning the electronic structure of supported mononuclear rhodium sites determined by the metal nuclearity and the electron-donor properties of the support, we report that atomically dispersed HY zeolite-supported rhodium with reactive acetylene ligands affords a stable ethylene selectivity > 90 % for acetylene semi-hydrogenation at 373 K and atmospheric pressure, even when ethylene is present in a large excess over acetylene. Infrared and X-ray absorption spectra and measurements of rates of the catalytic reaction complemented with calculations at the level of density functional theory show how the catalyst performance depends on the electronic structure of the rhodium, influenced by the support as a ligand that is a weak electron donor.

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

Simple processing via thermal treatment and catalyst infiltration to enhance nickel electrode performance for liquid alkaline water electrolyzers

Two simple processes for enhancing liquid alkaline water electrolyzer performance are demonstrated. Both enhance 3D Ni electrodes by introducing a micron-scale rough structure throughout the bulk of the electrode. Oxidation/reduction relies on a simple thermal treatment cycle to create surface roughening through the volumetric expansion during NiO formation and volume contraction during reduction back to Ni metal. Catalyst infiltration introduces a washcoat of additional metal particles throughout the electrode, by flooding the electrode with catalyst precursor and converting it to micron-scale particles via a reducing thermal treatment. Further, the largest improvement in performance (211mV at 1.8Acm -2 ) is observed for infiltrated NiFe-3x catalyst. For Fe-free Ni-only electrodes, oxidation/reduction provides a larger improvement (157 mV at 1.8Acm -2 ) than infiltrated Ni-3X (106mV at 1.8Acm -2 ). For both processes, the observed electrode surface structure and performance is quite sensitive to the thermal treatment temperature.

08 HYDROGEN↗
DOE OSTI2024

Unrecoverable lattice rotation governs structural degradation of single-crystalline cathodes

Transitioning from polycrystalline to single-crystalline nickel-rich cathodes has garnered considerable attention in both academia and industry, driven by advantages of high tap density and enhanced mechanical properties. However, cathodes with high nickel content (>70%) suffer from substantial capacity degradation, which poses a challenge to their commercial viability. Here, leveraging multiscale spatial resolution diffraction and imaging techniques, we observe that lattice rotations occur universally in single-crystalline cathodes and play a pivotal role in the structure degradation. These lattice rotations prove unrecoverable and govern the accumulation of adverse lattice distortions over repeated cycles, contributing to structural and mechanical degradation and fast capacity fade. These findings bridge the previous knowledge gap that exists in the mechanistic link between fast performance failure and atomic-scale structure degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

How Do Ionic Liquids “Fold” Ionenes? Computational and Experimental Analysis of Imidazolium Polymers Based on Ether and Alkyl Chain Variations Dissolved in an Ionic Liquid

Molecular dynamics (MD) simulations and complementary experiments are used here to understand the inter- and intramolecular structure and conformational properties of ionenes (i.e., cationic polymers formed from condensation reactions) dissolved in an ionic liquid (IL), 1-ethyl-3-methylimidazolium bistriflimide [C 2 mim + ][Tf 2 N - ]. The simulated structural properties are benchmarked against experimental analyses of these same polymers, mainly using dynamic light scattering (DLS) experiments. Four different imidazolium ionenes are considered, corresponding to variations in the chemistry and structure of the repeat units including: (1) poly (decylimidazolium) (PD 10 ); (2) poly (tetraethyleneglycolimidazolium) (PE 10 ); (3) alternating copolymer (P(ED) 5 ); and (4) a block copolymer (PE 5 D 5 ). Detailed computational analyses of the polymer structure and conformational properties were performed, including the radius of gyration, end-to-end distance, torsional distributions, and site-site and spatial distribution functions. Overall, there is a competition between intramolecular associations between the imidazolium groups and the ether sites in the polymers versus the intermolecular interactions of the polymer imidazolium groups with the surrounding anion molecules. The polymer with only ether linkages (PE 10 ) results in the most intramolecular interactions, leading to significant coiling behavior and chain contraction. These strong interactions reduce chain flexibility, but they also result in much more linear chain configurations and alignment of the imidazolium groups. The polymer structure is strongly affected as the concentration of alkyl groups is increased, and we find that the polymer architecture (alternating versus block copolymer) also has an important influence. Furthermore, these detailed observations are important for understanding the connection between the molecular design of imidazolium polymers and their emergent structural properties, which could lead to unique opportunities for creating polymer composites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Molecular engineering of dispersed nickel phthalocyanines on carbon nanotubes for selective CO 2 reduction

Electrochemical reduction of CO 2 is a promising route for sustainable production of fuels. A grand challenge is developing low-cost and efficient electrocatalysts that can enable rapid conversion with high product selectivity. Here we design a series of nickel phthalocyanine molecules supported on carbon nanotubes as molecularly dispersed electrocatalysts (MDEs), achieving CO 2 reduction performances that are superior to aggregated molecular catalysts in terms of stability, activity and selectivity. The optimized MDE with methoxy group functionalization solves the stability issue of the original nickel phthalocyanine catalyst and catalyses the conversion of CO 2 to CO with >99.5% selectivity at high current densities of up to -300 mA cm -2 in a gas diffusion electrode device with stable operation at -150 mA cm -2 for 40 h. The well-defined active sites of MDEs also facilitate the in-depth mechanistic understandings from in situ/operando X-ray absorption spectroscopy and theoretical calculations on structural factors that affect electrocatalytic performance.

42 ENGINEERING↗
DOE OSTI2024

Predicting Adhesion Energies of Metal Nanoparticles to Support Surfaces, Which Determines Metal Chemical Potential versus Particle Size and Thus Catalyst Performance

Improved catalysts and electrocatalysts composed of transition metal nanoparticles dispersed on high-area supports are essential for energy and environmental technologies. The chemical potential of the metal atoms in these supported nanoparticles is an important descriptor that correlates with both their catalytic activity and deactivation rate. This descriptor (μ M ) is predictably determined by the particle size and the adhesion energy per unit area at the metal/support interface (E adh ). We show here that the adhesion energies for different metals on a given support scale linearly with a simple property of the metal: for oxides, it is proportional to the metal oxophilicity, and for the carbon support, it increases linearly with metal carbophilicity (both divided by the area per metal atom). Furthermore, these relationships allow predicting E adh for other metal/support combinations, thus allowing estimation of μ M versus particle size and thereby better structure-based predictions of catalysts’ performance, which can aid in designing improved catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Machine Learning Assisted Synthesis of Metal–Organic Nanocapsules

Herein, we report machine learning algorithms by training data sets from a set of both successful and failed experiments for studying the crystallization propensity of metal–organic nanocapsules (MONCs). Among a variety of studied machine learning algorithms, XGBoost affords the highest prediction accuracy of >90%. The derived chemical feature scores that determine importance of reaction parameters from the XGBoost model assist to identify synthesis parameters for successfully synthesizing new hierarchical structures of MONCs, showing superior performance to a well-trained chemist. This work demonstrates that the machine learning algorithms can assist the chemists to faster search for the optimal reaction parameters from many experimental variables, whose features are usually hidden in the high-dimensional space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Assessment of Grizzly Capabilities for Reactor Pressure Vessels and Reinforced Concrete Structures

Over the last several years, capabilities to simulate the progression and effects of degradation in critical structures in light water reactor (LWR) nuclear power plants have been under development in the Grizzly code. Age-related material degradation is important for a number of systems in LWRs, but the main focus for Grizzly development has been on reactor pressure vessels (RPVs) and concrete structures because of their central role and the difficulty of replacement of these structures if they are found to be degraded to an unacceptable degree. The capabilities for analyzing both RPVs and concrete structures in Grizzly have reached a point where the feature sets are sufficiently complete to perform credible analyses of those types of structures. Because of this, the emphasis has shifted from foundational development to assessing the accuracy of these modeling capabilities on representative problems of interest and on improving the physical basis of those models to improve their ability to predict the actual response of those structural systems. This report documents a first set of test cases that have been developed to assess the Grizzly code on real-world problems for these two types of structures. For RPVs, these test cases consist of a set of benchmark problems where Grizzly is compared to another code. For concrete structures, a set of models of experimental specimens designed to characterize the multidimensional swelling response of reinforced concrete members due to alkali-silica reaction (ASR) has been developed and compared with experimental results. Both the RPV and concrete test cases developed here are much more computationally intensive than the small regression tests that are used in the testing that Grizzly undergoes every time a proposed set of changes is made to ensure that those changes do not adversely affect previously established behavior. A system for regularly running these large problems to monitor the behavior of the code as it is developed has been instituted. While these test cases generally indicate good comparison with the benchmark results, they also indicate areas where further development is warranted.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Temperature-dependent solid electrolyte interphase reactions drive performance in lithium-mediated nitrogen reduction to ammonia

The solid electrolyte interphase (SEI) is a vital component to control mass transport and selectivity in the lithium-mediated reduction of N 2 to NH 3 (Li-N 2 R). Finding strategies that generate the optimal SEI, a complex network of organic and inorganic species, can potentially improve Li-N 2 R performance. Here, we unravel structure-property relationships of the SEI by correlating its composition with the NH 3 faradaic efficiency (FENH3). By modifying the reaction temperature, we alter electrolyte decomposition reactions and observe changes in the SEI that explain FE NH3 trends between electrolyte solvents. We quantify a complex reaction environment at elevated temperatures where SEI formation is counteracted by etching reactions. This tradeoff leads to temporal fluctuations of FE NH3 , but the maximal FE NH3 can reach up to 40%, the highest value reported for batch cells at ambient pressure, thus far. In conclusion, our work underscores the potential of novel electrolytes that steer SEI selectivity and, ultimately, improve Li-N 2 R performance.

electrocatalytic nitrogen reduction↗
DOE OSTI2024

Chemical preintercalation of magnesium ions into ⍺-MoO 3 structure for improved electrochemical stability in Li-ion cells

Chemical preintercalation of layered materials, used as electrodes in intercalation-based energy storage devices, represents a promising strategy to enhance electrochemical stability and extend cycle life. However, standardized synthesis approaches for the chemical preintercalation of diverse ions into various layered materials are lacking, necessitating the development of specific synthesis routes for each ion and layered phase combination. In this study, we present the first successful demonstration of Mg 2+ ion chemical preintercalation into the interlayer region of α-MoO 3 , revealing its stabilizing effect during cycling in non-aqueous Li-ion cells. Using ethanol during hydrothermal treatment facilitated molybdenum reduction, which was critical for Mg 2+ ion preintercalation. Interestingly, we found that Mg preintercalation was accompanied by the incorporation of water. Mg-preintercalated α-MoO 3 exhibited enhanced charge storage capacity, electrochemical stability, and power capability compared to pristine α-MoO 3 electrodes. This improved performance is attributed to the structural stabilization provided by Mg 2+ pillars, which prevent undesirable phase transformations during repeated Li intercalation/deintercalation, and increased Li + ion diffusion due to the shielding of electrostatic interactions between electrochemically cycled ions and the α-MoO 3 lattice, enabled by structural water. In conclusion, our study offers new insights into developing chemical preintercalation synthesis approaches that can be broadly applied to a wide range of pillaring ions and layered material hosts.

25 ENERGY STORAGE↗
DOE OSTI2024

Design of non-fluorinated proton exchange membranes from Poly(Terphenyl fluorenyl isatin) with fluorene-linked sulfonate groups and microblock structures

Proton exchange membranes (PEMs) are essential components in energy storage and conversion devices, such as fuel cells and electrolyzers. Here, in this study, we developed a series of non-fluorinated PEMs from poly(terphenyl fluorenyl isatin) with fluorene-pendent disulfonate groups. These polymers feature a microblock structure composed of hydrophobic blocks, hydrophilic blocks, and alternating blocks, arising from the differences in reactivity, concentration, and solubility between the hydrophobic p-terphenyl and hydrophilic disulfonated fluorene monomers. As a result, the sulfonic acid groups are unevenly distributed along the polymer chains, forming densely charged regions (IEC = 3.52 meq/g) with large ion clusters and lightly charged regions (IEC = 2.16 meq/g) with small ion clusters. This microstructure, combined with the degree of sulfonation, significantly influences the overall properties of the membranes, including robust mechanical strength (47.1–63.2 MPa), high thermal stability (up to 270 °C), low swelling ratio (18–25% at 80 °C), and high proton conductivity (136–169 mS/cm in deionized water at 80 °C). The PFLSH60 membrane demonstrated comparable fuel cell performance to Nafion 212. Its hydrogen crossover current density was more than two times lower (0.86 mA/cm 2 for PFLSH60 compared to 1.83 mA/cm 2 for Nafion 212) under testing conditions of 80 °C and 100% RH. This significantly reduced crossover improves fuel utilization in fuel cell stacks. This work offers valuable insights into the design of robust, high-performance PEMs by systematically analyzing the relationships between membrane structure, properties, and performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Alcoholysis of nylon 6 waste to ε-caprolactam promoted by phosphoric acid

Nylon 6 is widely used in high-performance materials. However, the inherent structural rigidity of nylon 6 inhibits catalytic depolymerization to its monomer, ε-caprolactam. Here, in this study, we demonstrate an acid-catalyzed alcoholysis process that depolymerizes nylon 6 to ε-caprolactam, achieving yields up to 74% using n-propanol as solvent and phosphoric acid as catalyst at 220°C for 2 h. We further applied the process to commercial nylon-containing products, demonstrating ε-caprolactam yields of 67% to 76%. Process modeling and techno-economic analysis estimated a minimum selling price of recycled nylon 6 at $\$$1.79/kg, 30% lower than the 5-year average market price of virgin nylon 6. These estimates depend on assumed costs and process performance and may vary with future conditions. Life cycle assessment indicated that nylon 6 produced via alcoholysis can reduce greenhouse gas emissions by up to 63% compared with primary production. Overall, this study demonstrates a facile, cost-effective, and environmentally beneficial process for nylon 6 chemical recycling.

09 BIOMASS FUELS↗
DOE OSTI2024

Agrivoltaic Racking Design Optimization Based on Wind and Snow Loading Finite Element Analysis

The racking structure of photovoltaic (PV) systems plays a critical role in ensuring the PV panels generate power properly as it provides integral structural support and sometimes even solar tracking ability. Distinct applications of PV systems require variations of racking structure designs, which yield different mechanical performances under external loading conditions from the environment, such as heavy wind and snow. Past works, such as Reddy et al. [1], have analyzed the pressure effects of wind and snow loading on the racking structure of conventional rooftop and utility PV systems, but there is little knowledge of how various agrivoltaic racking systems perform, in terms of stress and strain, under the same loading conditions. There is also a knowledge gap in the industry on a set of optimized agrivoltaic racking design standards. This study investigates the mechanical performance of various existing racking systems and proposes novel designs that are optimized for agrivoltaics applications under wind and snow loading.

Liao, Quanhuan↗