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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 397 records · Page 22

Synthesis of (hemi)cellulosic lubricant base oils via catalytic coupling and deoxygenation pathways

The past decade has witnessed a significant growth in bioproduct development due to the strong interest in creating a more diverse energy supply, environmental sustainability, and a carbon neutral bioeconomy. The initial biorefinery strategy, which focused mainly on the production of low carbon number drop-in bioproducts, has recently shifted its focus on the production of high carbon number and high performance bioproducts with unique properties and value propositions. One such product is lubricant base oil (LBO), which represents over $150 billion global lubricant market and is used for various industrial, automotive, marine, metal-working, consumer, and specialized applications. The application landscape of lubricants has changed significantly over the past decade because of environmental regulations and the growing demand for sustainable lubricants to mitigate regulatory challenges and improve carbon footprint. Currently, only 3% LBOs are produced from bio-based triglycerides/fatty acids. Because of low oxidation stability and high hydrolytic susceptibility, these bio-based LBOs have limited applications. Thus, research and development and commercialization efforts for (hemi)cellulosic LBOs to meet the market demand have received momentum over the past few years. This review describes strategies to produce (hemi)cellulosic LBOs via carbon–carbon coupling and hydrodeoxygenation chemistries. We emphasize the coupling strategies to create LBOs with a branched architecture to surrogate petroleum-based poly-α-olefins. Here, a structure–property relationship for tuning the key specifications of LBOs as a function of molecular architecture is illustrated. Mechanistic understanding and molecular interactions of multi-furan substrates with the active sites of complex multifunctional catalysts are described. Furthermore, techno-economic and life-cycle analysis is summarized along with standing challenges and future opportunities.

09 BIOMASS FUELS↗

Single-Facet Dominant Anatase TiO 2 (101) and (001) Model Catalysts to Elucidate the Active Sites for Alkanol Dehydration

Alkanol dehydration on Lewis acid-base pairs of transition metal oxide catalysts is a reaction of importance in oxygen removal from biomass-derived feedstocks and their conversion to chemicals in general. However, catalysts with a high degree of structural heterogeneity, such as commercial TiO 2 powders, are not well-suited to establish rigorous structure-function relationships at an atomic level. Here, we provide compelling evidence for the effects of surface orientation of TiO 2 catalyst on elimination reactions of alcohols. Two anatase titania model catalysts, with preferential exposure of (101) and (001) facets, were synthesized and studied for 2-propanol dehydration using kinetic, isotopic, microscopic, and spectroscopic measurements, coupled with DFT calculations. Surface Lewis acid sites were found to be active for 2-propanol dehydration and (101) facets are more reactive than (001) facets under the reaction conditions studied. On both anatase surfaces, 2-propanol was found to dehydrate via concerted E2 elimination pathways, but with different initial states and thus also different intrinsic activation barriers. Molecular 2-propanol dehydration dominates on TiO2 (101) while on TiO 2 (001), 2-propanol simultaneously converts to more stable 2-propoxide before dehydration, which then requires higher activation energies for E2 elimination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interplanetary shock waves and the structure of solar wind disturbances

Observations and theoretical models of interplanetary shock waves are reviewed, with emphasis on the large-scale characteristics of the associated solar wind disturbances and on the relationship of these disturbances to solar activity. The sum of observational knowledge indicates that shock waves propagate through the solar wind along a broad, roughly spherical front, ahead of plasma and magnetic field ejected from solar flares. Typically, the shock front reaches 1 AU about two days after its flare origin, and is of intermediate strength. Not all large flares produce observable interplanetary shock waves; the best indicator of shock production appears to be the generation of both type 2 and type 4 radio bursts by a flare. Theoretical models of shock propagation in the solar wind can account for the typically observed shock strength, transit time, and shape.

Hundhausen, A. J.↗

Microstructural evolution and intermetallic formation in Zn-3Mg (wt%) powder mixture processed by high-pressure torsion

Severe plastic deformation (SPD) techniques have been used extensively over the past 40 years for producing strong metals and alloys. High-pressure torsion (HPT) is one of the most promising SPD techniques for achieving high strength through nanoscale grain refinement and phase transformation. In this research, a mixture of pure zinc (Zn) and magnesium (Mg) powders, Zn-3Mg (wt%), was HPT-processed under a pressure of 6 GPa for 1, 5, 10, 20, and 30 turns at room temperature to achieve a high strength biodegradable material. In order to understand the effects of pre-consolidation on the resulting microstructure and hardness, HPT processing was performed on loose powders placed in the die and also on a pre-compacted powder mixture and the resulting HPT disks were characterized by X-ray diffraction, scanning electron microscopy, atom probe tomography, and Vickers microhardness. In both cases, the HPT disk microstructures contained nanoscale grains, and stable and metastable strain-induced intermetallics, but an unusual softening appeared at large shear strains. Grain size, grain morphology, and the formation of different intermetallics were analyzed to explain the unusual hardness distribution, and it was found that an inverse Hall-Petch relationship between hardness and grain size exists. It is suggested that thermally-activated phenomena such as grain boundary sliding contributed to the strain-induced softening of this nano-structured biomaterial due to its low melting point. Finally, the current results are compared with those for HPT-processed cast alloys and hybrids of the same composition.

36 MATERIALS SCIENCE↗

Activities of the Center for the Space Processing of Engineering Materials

Topics addressed include: containerless processing and purification; directional and rapid solidification; high temperature alloys; oxidation resistant niobium alloys; metallic bonding; effects of solidification mode on structure-property relationships; and dispersion strengthened metal alloys. Each of the projects is reported by company association and follow according to alphabetical order of the company names.

Source record↗

Operando XAS and DFT Uncover Structure-Performance Relationships in Re/TiO 2 for Selective CO 2 Hydrogenation to Methanol

The conversion of CO 2 into value-added chemicals, such as methanol, offers a promising pathway toward a renewable energy future. However, a precise kinetic control and a highly selective catalyst are necessary to overcome the thermodynamic preference for CO 2 hydrogenation to methane. Rhenium-based catalysts, particularly Re/TiO 2 , demonstrate high activity and selectivity for methanol under high-pressure conditions. For example, at 100 bar and 200 °C, a methanol selectivity of 97−99% was obtained. Catalysts with 1 wt % Re and 5 wt % Re/ TiO 2 were used to study the effect of cluster sizes. At 250 °C, the 1 wt % catalyst achieves 97% selectivity at 23% conversion, whereas 5 wt % Re/TiO 2 achieves 74% selectivity at 40% conversion, corresponding to a drop in space-time yield from 65 to 16 g CH 3 OH ·g Re −1 ·h −1 , respectively. X-ray absorption spectroscopy provided insights into the structure of the active sites, while density functional theory calculations revealed the effects of cluster size on the energy barriers for H 2 activation, CH 3 OH dissociation, and CH 3 OH desorption, all of which directly influence conversion and selectivity. These results underscore the importance of balancing cluster size for optimal catalyst performance and provide insights into the design of efficient and selective catalysts for renewable methanol production.

XAS↗

Relationship between Sodium Content and Copper Activity for High Voltage Stability in O3-Type Layered Oxide Cathodes

Layered oxides with an O3 framework have attracted attention as cathode materials for sodium-ion batteries due to their high discharge capacity. Yet they are hampered for commercialization by poor cyclability due to structural instability during the sodium (de)intercalation process. The introduction of Cu in small fractions to the transition metal layers has been empirically observed to improve reversible specific capacity and cycling stability. Understanding the redox activity of Cu in O3-type Na x TMO 2 materials is crucial, as it could directly influence the charge compensation mechanism, voltage profile, and structural stability. However, the precise role of Cu in O3-type sodium cathodes under high-voltage cycling conditions (>4.1 V) remains insufficiently understood. To close this gap of knowledge, we studied the effect of Cu in two representative layered oxides with the same O3 stacking but different sodium stoichiometry, Na 0.9 Mn 1/2 Fe 1/3 Cu 1/6 O 2 and NaMn 1/2 Fe 1/3 Cu 1/6 O 2 . X-ray spectroscopy reveals that in Na 0.9 Mn 1/2 Fe 1/3 Cu 1/6 O 2 , Cu exhibits dual redox activity, Cu + /Cu 2+ in the pristine state and Cu 2+ /Cu 3+ upon charging in the sodium-deficient material, whereas only the Cu + /Cu 2+ redox couple is observed in the fully stoichiometric layered oxide. Furthermore, the results indicate that even a slight deficiency in sodium can significantly impact the electrochemical performance and material stability and alter the elemental redox activity of Cu.

Batteries↗

Establishing Self-Dopant Design Principles from Structure–Function Relationships in Self-n-Doped Perylene Diimide Organic Semiconductors

Self-doping is a particular doping method that has been applied to a wide range of organic semiconductors. However, there is a lack of understanding regarding the relationship between dopant structure and function. A structurally diverse series of self-n-doped perylene diimides (PDIs) is investigated to study the impact of steric encumbrance, counterion selection, and dopant/PDI tether distance on functional parameters such as doping, stability, morphology, and charge-carrier mobility. The studies show that self-n-doping is best enabled by the use of sterically encumbered ammoniums with short tethers and Lewis basic counterions. Additionally, water is found to inhibit doping, which concludes that thermal degradation is merely a phenomenological feature of certain dopants, and that residual solvent evaporation is the primary driver of thermally activated doping. In situ grazing-incidence wide-angle X-ray scattering studies show that sample annealing increases the π–π stacking distance and shrinks grain boundaries for improved long-range ordering. These features are then correlated to contactless carrier-mobility measurements with time-resolved microwave conductivity before and after thermal annealing. In conclusion, the collective relationships between structural features and functionality are finally used to establish explicit self-n-dopant design principles for the future design of materials with improved functionality.

36 MATERIALS SCIENCE↗

Dual Context: Leveraging Structured Application Context for Code Generation and Runtime Feature Activation via Chat Interfaces

Integrating artificial intelligence (AI) capabilities into software applications typically involves two common paths. For developers, AI assists in generating and documenting source code and other related software engineering efforts. For users, AI assists them through question-and-answer exchanges via chatbots. Both approaches have their value, but neither effectively leverages the modularity of component-based architectures that modern web application frameworks offer. We implement a proof of concept within a centralized suite of applications used for the Atmospheric Radiation Measurement (ARM) Data Center Operational Tools, where we introduce a third integration path through the ARM Context Engine (ACE). ACE is a context driven system that uses structured contextual specifications to enable Large Language Models (LLMs) to render interactive and feature-rich user interface (UI) components directly within chat responses, alongside or in place of conventional text outputs. These specifications serve two important purposes across what we call code context and UI context. Code context provides AI-assisted development tools with structured application knowledge beyond raw code, including component relationships, architectural patterns and schematic information, enabling the generation of consistent, well-structured code. UI context defines the rules for enabling and rendering component features at runtime based on the user's natural language input, allowing end users to activate capabilities such as data export, filtering, and pagination within chat responses, without requiring code changes or redeployment. We demonstrate, through a comparative evaluation against general-purpose AI chatbots, that context-driven component rendering provides interactive capabilities that text-based responses cannot replicate, including deterministic component behavior, application-consistent design language, and on-demand feature activation. A development effort comparison further shows that features that traditionally require multi-step development cycles can be activated with a single naturallanguage request. In this ongoing work, we present ACE as an emerging approach to AI integration that positions modular, well-documented software architecture as the foundation for AI-ready applications. ACE treats context as a shared resource across both development and user-facing AI, bringing cohesion to conventionally disconnected efforts, bridging developer tooling and end-user capabilities within a single framework.

Tadimeti, Vijay [ORNL]↗

Single Atom Catalysts: A Review of Characterization Methods

Abstract Single atom catalysts (SACs) harbor a potential to exceed nanoparticle catalysts in terms of activity, stability and selectivity in a growing number of chemical reactions. Although their investigation is attracting significant attention, important fundamental questions focusing on key physicochemical properties of SACs (e. g., structure – property relationships, structural dynamics, reaction‐driven restructuring) remain unanswered. A main challenge for research in the field is how to reliably characterize the environments of single atoms in the presence of complicating factors such as low weight loadings, strong metal‐support interactions, and atomic and multiscale heterogeneity of bonding in the single atom sites. This review addresses this challenge – identifying catalytically relevant features of physicochemical properties of single atoms (charge state, electronic structure, atomic configuration, bonding interactions with a support) and surveying advanced tools/methods for characterizing them. The review places a strong emphasis on multimodal methods exploiting X‐ray absorption, emission and photoelectron spectroscopies, and provides several examples from the authors’ research that demonstrate their use as powerful tools for SAC characterization.

Kottwitz, Matthew↗

Quantification of [MTBD][beti] loading and its effects on Pt/HSC electrode performance in hydrogen fuel cells

High surface area carbon-supported platinum catalysts (Pt/HSC) are widely used in polymer electrolyte membrane fuel cells but often suffer from limited proton and oxygen transport within porous domains. To address these challenges, we integrate the ionic liquid [MTBD][beti] into Pt/HSC catalyst layers using two deposition methods-one-pot and sequential deposition-to tune IL distribution within micropores and mesopores. A combination of ex situ and in operando techniques were employed to elucidate electrode structure-performance relationships across a range of IL loadings. Sequential deposition achieved more efficient pore filling and higher IL retention at lower IL:C ratios, enabling enhanced proton conductivity and protection of active sites. Compared to the IL-free Pt/HSC, IL-modified electrodes demonstrated up to 28% improvement in mass activity and enhanced high-current-density performance under low relative humidity, while maintaining comparable performance under humidified conditions. Electrochemical impedance spectroscopy and CO displacement experiments reveal that improvements are linked to reduced ionic resistance and lower sulfonate adsorption on Pt sites, rather than changes in electrochemical surface area. However, excessive IL loading leads to mass transport losses. These results highlight the importance of selective pore filling and efficient IL distribution in achieving kinetic gains without compromising ionic and gas transport.

08 HYDROGEN↗

Ensemble Manufacturing Techniques for Steam Turbine Components Across Length Scales

Faster design to manufacturing requirements were sought for steam turbine components to meet the changing demands of today’s power grid of improved efficiency through operating temperature increases and enhanced operational flexibility from baseload to cyclic operations. Advances in multiple advanced manufacturing (AM) process enabled redesign of turbine components for extreme environments with the potential to reduce cost. AM is of particular interest to improve component functionality, higher temperature capability, and superior durability in large scale steam turbine applications. AM methods have an immense potential to open-up the design space by working directly with the 3D model to produce near-net shapes, enable fast design-manufacturing iterations, thereby significantly reducing product cost and lead-time up to 25 % from current baseline. However, these benefits cannot be fully realized due to the potential for unknown AM processing defects and their resultant effect upon component performance in service. Siemens is partnering with Oak Ridge National Laboratory (ORNL), Electric Power Research Institute (EPRI), and Connecticut Center for Advanced Technology (CCAT) to advance the knowledge of complex process-material interactions for desired microstructures and properties that are closely interlinked to component geometries across different length scales. The proposed program utilized an ensemble of multidisciplinary technologies to accelerate the development of materials, high-throughput experiments for their qualification, and design flexibility/topology optimization for repair/redesign of components to address critical failure mechanisms for improved performance and increased reliability of existing power plant components. The proposed activities, if successfully demonstrated for identified components, will enable paradigm shift in customized manufacturing and accelerated qualification/certification towards increased steam turbine component durability, increased turbine efficiency, and reduced CO 2 emissions in load-following environments compared to today’s technology. Technology maturation is built into the project as successful research will include customized process-component down-selection enabling AM methodologies to be incorporated directly into the existing supply chain. The specific activities of the proposed effort are: 1. Topology optimization of down-selected steam turbine parts that are amenable to additive and hybrid manufacturing for cost/performance improvement. 2. Process-structure-property relationships for five AM processes for steam turbine materials of interest to compare with conventional materials. 3. Perform part/assembly build process using advanced additive/hybrid machine tools followed by quality inspection of the built components for insight into qualification for production scale-up. Steam turbine rig testing of printed components under targeted, well monitored and characterized environmental conditions of for performance comparison of baseline and redesigned components.

36 MATERIALS SCIENCE↗

Steps toward determination of the size and structure of the broad-line region in active galactic nuclei. III - Further observations of NGC 5548 at optical wavelengths

The results of the second year of an intensive ground-based spectroscopic and photometric study of variability in the bright Seyfert 1 galaxy NGC 5548 are reported in order to study the relationship between continuum and emission-line variability. Relative to the first year of the monitoring program, the nucleus of NGC 5548 was considerably fainter and the continuum variations slower during the second year, but the continuum H-beta cross-correlation results for the two years are nearly identical. The variations in the broad H-beta emission-line lag behind those in the continuum by somewhat less than 20 days, as concluded from the first year's data.

Peterson, B. M.↗

The observed characteristics of flare energy release. I - Magnetic structure at the energy release site

It is shown that flaring activity as seen in X-rays usually encompasses two or more interacting magnetic bipoles within an active region. Soft and hard X-ray spatiotemporal evolution is considered as well as the time dependence of the thermal energy content in different magnetic bipoles participating in the flare, the hardness and impulsivity of the hard X-ray emission, and the relationship between the X-ray behavior and the strength and 'observable shear' of the magnetic field. It is found that the basic structure of a flare usually consists of an initiating closed bipole plus one or more adjacent closed bipoles impacted against it.

Machado, Marcos E.↗

Microstructurally Strained Pyrochlore–Perovskite Biphasic Electrocatalysts for the Oxygen Evolution Reaction

Efficiency of water splitting for hydrogen production is often limited by the sluggish kinetics of multiple electronic transfers required in the heterogeneous oxygen evolution reaction (OER). Catalyst design for reducing the high OER overpotential remains a major scientific challenge. Lattice-strain engineering, a method for tuning the electronic structure and surface geometric configuration of active sites, may greatly affect the interaction between adsorbates and catalytic surfaces for high activity and stability. Here, in this study, we present the synthesis of biphasic oxides of YPrSrRuMnO x , which consists of distinct phases of Y 2 Ru 2 O 7 pyrochlore and (Pr 0.7 Sr 0.3 )MnO 3 perovskite, and the development of a suitable analytical approach to study the strain–catalytic property relationship. Linear sweep voltammetry results reveal that the biphasic oxide exhibits approximately 3.1 times greater mass activity and 2.4 times larger turnover frequency (TOF) than single-phase Y 2 Ru 2 O 7 in the 0.1 M HClO 4 electrolyte. The biphasic catalyst is also about 3 times more stable than the single-phase oxide under acidic conditions. X-ray photoelectron spectroscopy, nitrogen isotherm, and electrochemical surface area analyses indicate that the oxidation state, specific surface area, and electrochemical surface area do not cause enough difference in the observed enhancement of OER performance. We examined the effects of microstrain on electrocatalysis, originating from lattice mismatch between different phases, using three different structural models. Specifically, we compared the Williamson–Hall method, standard stress–strain analysis, and Rietveld refinement in analyzing the structure–property relationship. Strain mapping using geometric phase analysis (GPA) further revealed significant microstrain and lattice dislocations localized near phase boundaries in the biphasic oxide, in contrast to the uniform strain in single-phase materials. The results reveal that the increased microstrain correlates well with the improved OER performance, as the biphasic oxide catalyst exhibits 2–3 times greater microstrain than Y 2 Ru 2 O 7 pyrochlore.

electrocatalysts↗

Fox Trails

1. This software utilizes python pandas to pull data from P6 databases or XER files. The software transforms the datasets into multiple main tables by joining, filtering, iteratively flattening hierarchical structured data, and pivoting datasets to give simple flat output tables. The activity table includes all of the information related to an activity including activity codes, global, EPS, and project codes, UDFs, and WBS information as separate columns. This includes the code id, code value and sequence number for all levels in hierarchical codes. The resource table is similar to the activity table and includes all of the information related to resources on activities including UPFs and resource codes. The resource time phased table takes the resource information and time phases it for the budget, forecast, late, and actual dates/units/costs that closely matches P6's user interface's values as it implements the resource curve and calendars. The wbs table contains the WBS structure broken out by levels and includes UDFs, codes, and notebook topics. The final P6 data table is the relationships table which simply contains the relationships. 2. When a user updates the tool with data (via giving it P6 project names with database username/password information or XER files) the system creates the data in #1, then creates a networkx graph with the activity data imbedded in the node data and the relationships added as edges. Each edge also has it's float calculated (working time distance between the predecessor and successor) and attached to the edge. Activities are also tagged as a potential start of a path based on their constraints, constraint dates, remaining start date, and activity status. When a user enters an activity ID into the UI, it runs a shortest path calculation on the network graph between each node tagged as potential start to the entered activity id based on the float tagged on the edge. Each path returned by the algorithm contains all of the nodes on the path in order, as well as the total float of the edges that make the path. This data is then collected and returned to the user in the form of a gantt chart with groupings for each path that includes the total float for each group. 3. Similar to 2, if the user passes through a reference dataset each activity set in the path is checked to see if it had a path in the reference dataset, if that path was the primary path between the start and end activities, and what has changed regarding logic and durations. These changes are color coded and summarized before sent to the user to be displayed by the UI for simple discovery. 4. Utilizing the data from #1, the user can submit desired grouping code(s) and filters to the system. The system will then pull the activities, resources, and relationships and create a gantt chart based on the groupings sent and filtered based on the filters sent. 5. The system will produce a gantt chart in a similar method to #4, but allows interactivity with the data. As the user interacts with the gantt chart, the software captures the changes and stores it with the user making the change so that project controls and implement those changes in P6.

Fox, Ben↗

Photometric and spectral properties of some T Tauri stars

Photometric and spectroscopic data have been obtained for selected T Tauri members of the Taurus-Aurigae cloud and the Orion complex. A correlation between the intensity ratio of calcium and hydrogen emission lines and the infrared excess at 3.5 microns is found for these stars, which indicates a causal relationship between 'chromospheric activity' and emission processes in the circumstellar shells. It is argued that a comparison with properties of well-studied novae could lead to a better understanding of the physical structure of T Tauri stars.

Warner, J. W.↗

An implicit method for the nonlinear modelling and simulation of piezoceramic actuators displaying hysteresis

Experiments have shown that piezoceramic materials display a nonlinear relationship between the applied electric field and the actuation strain. This relationship also displays a substantial hysteresis upon reversal of the applied field. In this paper, piezoceramic actuator models are incorporated into the structural equations of motion to arrive at a set of nonlinear actively controlled structural equations of motion. A new implicit algorithm for determining the time history of the actively controlled structure is presented. The algorithm employs the trapezoidal rule for stepping the equations forward in time. The algorithm is compared to an explicit algorithm and is shown to provide greater numerical accuracy. In addition, the numerical stability and convergence characteristics are presented via example. The new algorithm displays convergence and stability properties that are comparable to the standard trapezoidal rule used for dynamic systems without hysteresis.

Leigh, Timothy D.↗