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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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All FORTRAN version of NASA structural analysis program NASATRAN is implemented on DEC VAX-series computer. Applications of NASATRAN extend to almost every type of linear structure and construction. Two special features are available in VAX version; program is executed from terminal in manner permitting use of VAX interactive debugger, and links are interactively restarted when desired by first making copy of all NASATRAN work files.
Research carried out is grouped under two topics: (1) Design Optimization, and (2) Integrated Force Method of Analysis. Design Optimization Research Topics are singularity alleviation enhances structural optimization methods, computer based design capability extended through substructure synthesis, and optimality criteria provides optimum design for a select class of structural problems. Integrated Force Method of Analysis Research Topics are boundary compatibility formulation improves stress analysis of shell structures. Brief descriptions of the four topics are appended.
Cementitious materials having high damage tolerance and self-sensing ability are described herein. These materials may replace conventional concrete to serve as a major material component for infrastructure systems with greatly improved resistance to cracking, reinforcement corrosion, and other common deterioration mechanisms under service conditions, and prevents fracture failure under extreme events. These materials can also be used for the repair, retrofitting or rehabilitation of existing concrete structures or infrastructure systems. Furthermore, these materials may offer capacity for distributed and direct sensing of cracking, straining and deterioration with spatially continuous resolution wherever the material is located, without relying on installation of sensors. The present invention relates to multifunctional cementitious structural or infrastructure materials that integrate self-sensing with damage tolerance for improving safety, extending service life, and health monitoring of structures, components, and infrastructure systems.
In this project we aimed to extend methods for protein function prediction to include structural prediction data, and benchmark methods against existing tools. We proposed to apply the method to large metagenome datasets, and develop approaches to examine activity-based protein profiling results for protein function-structure patterns. Nitrogen cycle protein families were previously identified and are used here to provide a proof-of-principle for use of structure prediction in protein function classification.
CN profiles in comet P/Halley were constructed from observations taken at three observatories during an 8 day period in April 1986. These data provide a time series of CN spatial profiles spanning just over one 7.37 day period from 1986 April 7 to April 15 and sample distances from the nucleus from just over 10(exp 3) km to 10(exp 6) km. The effect of the 7.37 day periodic variation on the CN distribution in P/Halley has been examined by using the time-dependent model applied earlier to a subset of the data. Because of the large spatial scale of the data on April 7, 8, and 9 (approx. 10(exp 6) km), and the corresponding transport time in the coma, information present in the spatial profiles regarding the gas production rate actually covers nearly two full periods. These spatially extended profiles clearly show the wavy structures outside 10(exp 5) km. Such structures were predicted in a previous analysis (Combi & Fink 1993) that was based solely on the photometric light curve and on profiles which only extended to distances less than 10(exp 5) km. We are now able to reproduce the highly variable Halley correction for the variation in gas production rate.
The previously developed Ko closed-form aging theory has been reformulated into a more compact mathematical form for easier application. A new equivalent loading theory and empirical loading theories have also been developed and incorporated into the revised Ko aging theory for the prediction of a safe operational life of airborne failure-critical structural components. The new set of aging and loading theories were applied to predict the safe number of flights for the B-52B aircraft to carry a launch vehicle, the structural life of critical components consumed by load excursion to proof load value, and the ground-sitting life of B-52B pylon failure-critical structural components. A special life prediction method was developed for the preflight predictions of operational life of failure-critical structural components of the B-52H pylon system, for which no flight data are available.
Understanding the atomic-scale structure and dynamics of amorphous oxide surfaces is essential for interpreting their chemical reactivity, mechanical stability, and interfacial behavior, yet direct experimental characterization remains challenging. We employ Deep Potential (DP) molecular dynamics to generate large-scale, ab initio -quality models of amorphous Al 2 O 3 bulk glasses and melt-quenched free surfaces, enabling a quantitative analysis of both structure and relaxation dynamics with statistical confidence inaccessible to direct ab initio simulation. The trained DP model reproduces experimental liquid and glass structure, captures the cooling-rate dependence of the bulk glass transition, and corrects systematic biases in the polyhedral populations predicted by widely used classical force fields. At the free surface, mass density recovers to bulk values over ~10 Å, while local coordination requires a slightly wider subsurface region to fully converge. The outermost layer is oxygen-enriched, exhibits altered polyhedral connectivity with contracted Al–O bonds, and hosts a broad population of under-coordinated motifs (notably AlO 3 and OAl 2 ) whose abundances are governed by glass stability. These under-coordinated surface motifs exhibit distinct vibrational signatures and occur as locally paired Lewis acid and Brønsted base sites consistent with bond-valence compensation, yet remain spatially dispersed rather than aggregating into extended clusters. Despite this pronounced structural heterogeneity, surface relaxation and the glass-transition temperature remain comparable to their bulk counterparts, suggesting that the disordered surface is kinetically stable once formed. Together, these results establish a molecular-level picture of amorphous alumina surfaces and demonstrate the capability of machine-learned potentials to resolve structure–property relationships in disordered oxide interfaces.
Ferrocene is perhaps the most popular and well-studied organometallic molecule, but our understanding of its structure and electronic properties has not changed for more than 70 years. In particular, all previous attempts of chemically oxidizing pure ferrocene by binding directly to the iron center have been unsuccessful, and no significant change in structure or magnetism has been reported. Here, using a metal organic framework host material, we were able to fundamentally change the electronic and magnetic structure of ferrocene to take on a never-before observed physically stretched/bent high-spin Fe(II) state, which readily accepts O 2 from air, chemically oxidizing the iron from Fe(II) to Fe(III). We also show that the binding of oxygen is reversible through temperature swing experiments. Our analysis is based on combining Mößbauer spectroscopy, extended X-ray absorption fine structure, in situ infrared, SQUID, thermal gravimetric analysis, and energy dispersive X-ray fluorescence spectroscopy measurements with ab initio modeling.
We report the use of iron 1s3p resonant X-ray emission processes to conduct spin-selective, high-energy resolution fluorescence detected X-ray absorption near-edge spectroscopy (HERFD-XANES) on an iron-containing, lithium- and manganese-rich, fully earth-abundant cathode material, Li 1.3 Mn 0.5 Fe 0.2 O 2 (0.7Li 2 MnO 3 ·0.3LiFeO 2 ). Coupling this technique with conventional Mn K-edge XANES and detailed extended X-ray absorption fine structure (EXAFS) analysis from both the Mn and Fe vantage points, we gain fundamental insights into the redox processes and migration tendencies of transition metals in this cathode material at the bulk level. We show that during the first charge, Fe 3+ undergoes oxidation to form Fe 4+ prior to the activation plateau. Toward the end of activation, a significant fraction of the iron is present as tetrahedral Fe 3+ . This observation reveals that iron migration from octahedral to tetrahedral sites and iron reduction are initiated during activation. Upon first discharge from the activated state, a continuous and overlapping reduction of both Fe and Mn is observed, with Fe largely restored back as an octahedrally coordinated Fe 3+ . The manganese local environment gradually changes to a distorted cooperative Jahn–Teller Mn 3+ structure during discharge, with the clear presence of two Mn–O as well as two Mn–Mn correlation distances at 2.0 V. The significant reduction of manganese in the very first discharge is distinctly different from that seen in typical nickel-based lithium-manganese-rich materials but is similar to that observed for pure Li 2 MnO 3 . In conclusion, these findings shed light on key structure–property correlations in the cathode material and point to a causative relationship between the redox mechanisms as well as structural changes endured by the material and relatively poor performance during extended electrochemical cycling.
Liquid electrolytes in batteries are typically treated as macroscopically homogeneous ionic transport media, despite having complex chemical composition and atomistic solvation structures, thus leaving a knowledge gap of microstructural characteristics. A promising electrolyte system design has recently been developed with the title of a localized high-concentration electrolyte (LHCE). These electrolytes are a summation of three components – a charge-carrying salt, a solvent that solvates the salt, and a diluent that is sparingly interactive with the salt in terms of ion solvation. This creates the perception of a high-concentration electrolyte (HCE) with high anion-cation interactions that supports a salt-derived, stable solid-electrolyte interphase, while an LHCE improves bulk electrolyte properties, such as ionic conductivity and viscosity, when compared to an HCE. Much trial by error design of this LHCE concept has been supported by simulations to confirm ionic interactions, cycling data to confirm cell stability, and post-mortem analysis to provide evidence of mechanisms. However, a systematic design to extend the capabilities of LHCEs is still to be desired. Here, we analyzed a specific LHCE mixture to dictate the best viable mixture that extends the localization of solvation structures while maintaining viable cell-level capabilities. We seek to observe and understand solvent-to-salt interactions that impact electrolyte performance. These interactions range from single-ion solvation, multidentate interactions (i.e., solvation-driven clustering), to more widespread network-level interactions. With the support of both experimental and computational analysis of different electrolyte features, we have begun a methodology of formulating the most ideal LHCE mixtures for improving the cyclability of high-capacity battery chemistries.
Ni oxides and oxyhydroxides (NiO x ) have been studied for a long time as cathode materials for alkaline batteries and electrocatalysts for the oxygen evolution reaction (OER). Yet, understanding of the connection between their atomic and electronic structures and electrochemical performance or stability is still incomplete. In this work, we use first-principles density functional theory (DFT) calculations to revisit the structure, electronic properties, and OER activity of β-NiOOH, the catalytically active phase of NiO x . Following extensive DFTbased screening, we identify a hitherto overlooked structure characterized by a uniform distribution of H atoms on the NiO 2 layers. All the Ni 3+ cations in this structure exhibit an identical t g 6 e g 1 electronic configuration with an occupied 3d z2 orbital. Comparison of the calculated bond lengths with extended X-ray absorption fine structure (EXAFS) data unequivocally supports this structure relative to all other low-energy configurations. Based on this structure, we uncover and detail defect-dominated OER mechanisms on the basal β-NiOOH (001) surface, with overpotentials as low as 0.39 V. The present results should provide a valuable contribution to ongoing efforts for understanding and developing enhanced transition-metal hydroxide catalysts for the OER.
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In this study, we present a comprehensive quantitative analysis of stability bands for dendritic arrays during directional solidification of a transparent succinonitrile-0.46 wt % camphor alloy, spanning a broad range of pulling velocities. Taking advantage of the microgravity environment aboard the International Space Station where most convection effects are suppressed, we obtain unique measurements that quantify the stable primary spacing range of spatially extended three-dimensional dendritic array structures under purely diffusive growth conditions. Through carefully designed velocity jump experiments and detailed examination of sub-grain boundary dynamics, we characterize key instabilities, including elimination and tertiary branching, shedding new light on the mechanisms governing dynamic dendritic spacing selection in extended 3D arrays. Phase field simulations are performed to characterize the stability limits of dendritic array structures for quantitative comparison with the flight experiments. Although the simulations capture general trends, significant deviations are noted at the upper stability boundary, indicating the influence of additional, unexplored factors. These findings contribute to a deeper understanding of dendritic growth dynamics and offer valuable benchmark data that could aid in refining predictive models and improving control of dendritic microstructures in metallurgical applications.
The effect of crystallizing solution chemistry on the chemistry of subsequently as-grown materials was investigated for Mo-substituted iron oxides prepared by thermally activated co-precipitation. In the presence of Mo ions, we find that varying the oxidation state of the iron precursor from Fe(II) to Fe(III) causes a progressive loss of atomic long-range order with the stabilization of 2-4 nm particles for the sample prepared with Fe(III). The oxidation state of the Fe precursor also affects the distribution of Fe and Mo cations within the spinel structure. Increasing the Fe precursor oxidation state gives decreased Fe-ion occupation and increased Mo-ion occupation of tetrahedral sites, as revealed by the extended X-ray absorption fine structure. The stabilization of Mo within tetrahedral sites appears to be unexpected, considering the octahedral preferred coordination number of Mo(VI). The analysis of the atomic structure of the sample prepared with Fe(III) indicates a local ordering of vacancies and that the occupation of tetrahedral sites by Mo induces a contraction of the interatomic distances within the polyhedra as compared to Fe atoms. Moreover, the occupancy of Mo into the thermodynamic site preference of a Mo dopant in Fe 2 O 3 assessed by density functional theory calculations points to a stronger preference for Mo substitution at octahedral sites. Hence, we suggest that the synthetized compound is thermodynamically metastable, that is, kinetically trapped. Such a state is suggested to be a consequence of the tetrahedral site occupation by Mo ions. The population of these sites, known to be reactive sites enabling particle growth, is concomitant with the stabilization of very small particles. Furthermore, we confirmed our hypothesis by using a blank experiment without Mo ions, further supporting the impact of tetrahedral Mo ions on the growth of iron oxide nanoparticles. Our findings provide new insights into the relationships between the Fechemistry of the crystallizing solution and the structural features of the as-grown Mo-substituted Fe-oxide materials.
In this study, we presented an AISID method extending AlphaFold-Multimer’s success in structure prediction towards identifying specific protein interactions with an optimized AISIDscore. The method was tested to identify the binding proteins in 18 human TNFSF (Tumor Necrosis Factor superfamily) members for each of 27 human TNFRSF (TNF receptor superfamily) members. For each TNFRSF member, we ranked the AISIDscore among the 18 TNFSF members. The correct pairing resulted in the highest AISIDscore for 13 out of 24 TNFRSF members which have known interactions with TNFSF members. Out of the 33 correct pairing between TNFSF and TNFRSF members, 28 pairs could be found in the top five (including 25 pairs in the top three) seats in the AISIDscore ranking. Surprisingly, the specific interactions between TNFSF10 (TNF-related apoptosis-inducing ligand, TRAIL) and its decoy receptors DcR1 and DcR2 gave the highest AISIDscore in the list, while the structures of DcR1 and DcR2 are unknown. The data strongly suggests that AlphaFold-Multimer might be a useful computational screening tool to find novel specific protein bindings. This AISID method may have broad applications in protein biochemistry, extending the application of AlphaFold far beyond structure predictions.
Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often nondifferentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or time consuming to evaluate a single instance, and hence classical approaches based on exhaustive grid or random search are too data intensive. This resulted in strong interest toward active learning methods such as Bayesian optimization (BO) where the adaptive exploration occurs based on human learning (discovery) objective. However, classical BO is based on a predefined optimization target, and policies balancing exploration and exploitation are purely data driven. In practical settings, the domain expert can pose prior knowledge of the system in the form of partially known physics laws and exploration policies often vary during the experiment. Here, we propose an interactive workflow building on multifidelity BO (MFBO), starting with classical (data-driven) MFBO, then expand to a proposed structured (physics-driven) structured MFBO (sMFBO), and finally extend it to allow human-in-the-loop interactive interactive MFBO (iMFBO) workflows for adaptive and domain expert aligned exploration. These approaches are demonstrated over highly nonsmooth multifidelity simulation data generated from an Ising model, considering spin–spin interaction as parameter space, lattice sizes as fidelity spaces, and the objective as maximizing heat capacity. Detailed analysis and comparison show the impact of physics knowledge injection and real-time human decisions for improved exploration with increased alignment to ground truth. Here, the associated notebooks allow to reproduce the reported analyses and apply them to other systems.
The Light Water Reactor Sustainability (LWRS) Program, sponsored by the U.S. Department of Energy (DOE), plays a pivotal role in enhancing the sustainability, safety, and economic viability of the nation's fleet of nuclear power plants. This program collaborates extensively with industry, vendors, suppliers, regulatory agencies, and research and development organizations within the nuclear energy sector. The overarching goals of the LWRS program are twofold: to provide innovative science and technology-based solutions to the nuclear industry, surpassing current performance models, and to manage the aging of systems, structures, and components (SSCs) to extend the operational lifetimes of nuclear power plants safely, efficiently, and economically. The program focuses on five research and development pathways: Plant Modernization: This pathway seeks to enhance the economic viability of nuclear power plants in evolving energy markets through innovation, efficiency improvements, and digital transformation. The integration of digital technologies into plant operations is a central theme, aiming to create a seamless digital environment that improves plant economics and safety. Flexible Plant Operation and Generation: Research efforts in this pathway explore opportunities for light-water reactors (LWRs) to directly supply energy to industrial processes, diversifying revenue generation approaches and improving economic sustainability.
Cobalt-59 nuclei are known for extremely thermally sensitive chemical shifts (δ), which in the long term could yield novel magnetic resonance thermometers for bioimaging applications. In this manuscript, we apply extended X-ray absorption fine structure (EXAFS) spectroscopy for the first time to probe the exact variations in physical structure that produce the exceptional thermal sensitivity of the 59 Co NMR chemical shift. We apply this spectroscopic technique to five Co(III) complexes: [Co(NH3)6]Cl3 (1), [Co(en) 3 ]Cl 3 (2) (en = ethylenediamine), [Co(tn) 3 ]Cl 3 (3) (tn = trimethylenediamine), [Co(tame) 2 ]Cl 3 (4) (tame = 1,1,1-tris(aminomethyl)ethane), and [Co(diNOsar)]Cl 3 (5) (diNOsar = dinitrosarcophagine). The solution-phase EXAFS data reveal increasing Co–N bond distances for these aqueous complexes over a ~50 °C temperature window, expanding by Δr (Co–N) = 0.0256(6) Å, 0.0020(5) Å, 0.0084(5) Å, 0.0006(5) Å, and 0.0075(6) Å for 1–5, respectively. Computational analyses of the structural changes reveal that increased connectivity between the donor atoms encourages complex structural variations. Finally, these results imply that rich temperature-dependent structural variations define 59 Co NMR thermometry in macrocyclic complexes.