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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Divalent Titanium via Reductive N−C Coupling of a Ti IV Nitrido with π ‐Acids

The nitrido-ate complex [(PN) 2 Ti(N){μ 2 -K(OEt 2 )}] 2 (1) (PN − =(N-(2-P i Pr 2 -4-methylphenyl)-2,4,6-Me 3 C 6 H 2 ) reductively couples CO and isocyanides in the presence of DME or cryptand (Kryptofix222), to form rare, five-coordinate Ti II complexes having a linear cumulene motif, [K(L)][(PN) 2 Ti(NCE)] (E=O, L=Kryptofix222, (2); E=NAd, L=3 DME, (3); E=N t Bu, L=3 DME, (4); E=NAd, L=Kryptofix222, (5)). Oxidation of 2–5 with [Fc][OTf] afforded an isostructural Ti III center containing a neutral cumulene, [(PN) 2 Ti(NCE)] (E=O, (6); E=NAd (7), N t Bu (8)) and characterization by CW X-band EPR spectroscopy, revealed unpaired electron to be metal centric. Moreover, 1e − reduction of 6 and 7 in the presence of Kryptofix222cleanly reformed corresponding discrete Ti II complexes 2 and 5, which were further characterized by solution magnetization measurements and high-frequency and -field EPR (HFEPR) spectroscopy. Furthermore, oxidation of 7 with [Fc*][B(C 6 F 5 ) 4 ] resulted in a ligand disproportionated Ti IV complex having transoid carbodiimides, [(PN) 2 Ti(NCNAd) 2 ] (9). Comparison of spectroscopic, structural, and computational data for the divalent, trivalent, and tetravalent systems, including their 15 N enriched isotopomers demonstrate these cumulenes to decrease in order of backbonding as Ti II →Ti III →Ti IV and increasing order of π-donation as Ti II →Ti III →Ti IV , thus displaying more covalency in Ti III species. Lastly, we show a synthetic cycle whereby complex 1 can deliver an N-atom to CO and CNAd.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

CP decomposition for tensors via alternating least squares with QR decomposition

The CP tensor decomposition is used in applications such as machine learning and signal processing to discover latent low-rank structure in multidimensional data. Computing a CP decomposition via an alternating least squares (ALS) method reduces the problem to several linear least squares problems. The standard way to solve these linear least squares subproblems is to use the normal equations, which inherit special tensor structure that can be exploited for computational efficiency. However, the normal equations are sensitive to numerical ill-conditioning, which can compromise the results of the decomposition. In this paper, we develop versions of the CP-ALS algorithm using the QR decomposition and the singular value decomposition, which are more numerically stable than the normal equations, to solve the linear least squares problems. Our algorithms utilize the tensor structure of the CP-ALS subproblems efficiently, have the same complexity as the standard CP-ALS algorithm when the input is dense and the rank is small, and are shown via examples to produce more stable results when ill-conditioning is present. Our MATLAB implementation achieves the same running time as the standard algorithm for small ranks, and we show that the new methods can obtain lower approximation error.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Excited State and Non-linear Optical Properties of NIR Absorbing β-Thiophene-Fused BF{sub 2}-Azadipyrromethene Dyes—Computational Investigation

Density functional theory and time-dependent density functional theory computations were used to understand the electronic and photophysical parameters of NIR β-thiophene-fused BF{sub 2}-azadipyrromethene dyes. The computed data are in good agreement with those obtained experimentally and they provide insights into the origin of red shifted optical spectra compared to the parent aza-BODIPY, low Stokes shift, non-linear optical responses and quantitative description of the singlet–triplet energy gap. The resultant decrease in the HOMO − LUMO energy gap is responsible for the red shift. The possible use as non-linear optical materials is supported by large enhancement in the non-linear optical properties. On the basis of vertical triplet energies, their possible potential therapeutic use as a photosensitizer in photodynamic therapy is proposed. The singlet–triplet energetic gaps suggest that the β-thiophene-fused BF{sub 2}-azadipyrromethene dyes can act as a sensitizer to produce an efficient generation of singlet oxygen. Their optimal use as an efficient singlet fission materials has been proposed on the basis of excitation energies in the ground, lowest singlet and triplet excited states.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Coming to Grips with Ambiguity: Ion Mobility-Mass Spectrometry for Protein Quaternary Structure Assignment

Multiprotein complexes are central to our understanding of cellular biology, as they play critical roles in nearly every biological process. Despite many impressive advances associated with structural characterization techniques, large and highly-dynamic protein complexes are too often refractory to analysis by conventional, high-resolution approaches. To fill this gap, ion mobility-mass spectrometry (IM-MS) methods have emerged as a promising approach for characterizing the structures of challenging assemblies due in large part to the ability of these methods to characterize the composition, connectivity, and topology of large, labile complexes. In this Critical Insight, we present a series of bioinformatics studies aimed at assessing the information content of IM-MS datasets for building models of multiprotein structure. Our computational data highlights the limits of current coarse-graining approaches, and compelled us to develop an improved workflow for multiprotein topology modeling, which we benchmark against a subset of the multiprotein complexes within the PDB. This improved workflow has allowed us to ascertain both the minimal experimental restraint sets required for generation of high-confidence multiprotein topologies, and quantify the ambiguity in models where insufficient IM-MS information is available. We conclude by projecting the future of IM-MS in the context of protein quaternary structure assignment, where we predict that a more complete knowledge of the ultimate information content and ambiguity within such models will undoubtedly lead to applications for a broader array of challenging biomolecular assemblies. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

The role of precursor decomposition in the formation of samarium doped ceria nanoparticles via solid-state microwave synthesis

The impact on the final morphology of ceria (CeO 2 ) nanoparticles made from different precursors (commercial: cerium acetate/nitrate) and in house: cerium tri(methylsilyl)amide (Ce-TMSA)) via a microwave solid state reaction has been determined. In all instances, powder X-ray diffraction indicated that the cubic fluorite CeO 2 phase (PDF# 04–004-9150, with the space group Fm-3 m) had formed. Scanning electron microscopy (SEM) images revealed spherical nanoparticles were produced from the Ce-TMSA precursor. The commercial acetate and nitrate precursors produced particles with irregular morphology. The roles of the precursor decomposition and binding energy in the synthesis of the nanocrystals with various morphologies, as well as a possible growth mechanism, were evaluated based on experimental and computational data. The formation of spherical shaped nanoparticles was determined to be due to the preferential single-step decomposition of the Ce-TMSA as well as the low activation energy to overcome decomposition. Due to the complicated decomposition of the commercial precursors and high activation energy the resulting particles adopted an irregular morphology. Highly uniform samarium doped ceria (Sm x Ce 1-x O 2-δ ) nanospheres were also synthesized from Ce-TMSA and samarium tri(methylsilyl)amide (Sm-TMSA). The effects of reaction time and temperature, on the final morphology were observed through SEM. The rapid single-step decomposition of TMSA-based precursors as observed through thermogravimetric analysis (TGA) and confirmed through the calculation of potential energy surfaces and binding energies from density functional theory (DFT) calculations, indicated that nanoparticle formation follows LaMer’s classical nucleation theory.

36 MATERIALS SCIENCE↗
DOE OSTI2025

DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys

Designing ductile materials for extreme environments such as fusion reactors requires a deep understanding of the complex interplay between electronic structure, mechanical stability, and wide compositional space. Here, in this work, we introduce DuctGPT, a physics-informed, GPT-powered machine learning platform that enables rapid and accurate prediction of ductility across a wide range of refractory multi-principal element alloys (MPEAs). Trained on both experimental and high-fidelity computational data, DuctGPT integrates descriptors such as density of states at the Fermi level, elastic constants, and valence electron concentration to capture the fundamental mechanisms governing ductile versus brittle behavior. Using this framework, we screen over 1000 compositions in of body-centered cubic (BCC) MPEAs, including two new alloy classes, i.e., NbTa-rich (NbTa $>$ 50 at.%) NbTa-Ti-V and W-rich ($>$ 50 at.%) W-Ti-V MPEAs, to rapidly identify promising alloy compositions with enhanced ductility. Validation against experimental data confirms the model's ability to predict ductility with high fidelity and low uncertainty. By leveraging conversational AI and robust physical modeling, DuctGPT provides a blueprint for the next generation of alloy design assistants, enabling human-AI collaboration in the accelerated discovery of ductile, high-performance materials for fusion, aerospace, and advanced manufacturing.

AI/ML↗
DOE OSTI2021

Neutron thermalization in nuclear graphite: A modern story of a classic moderator

Graphite has been of great interest since the dawn of the nuclear era. In this work, we will focus on the thermal neutron scattering of two types of nuclear graphite that have different microstructures, namely, the historic PGA which has a very anisotropic medium-grained needle coke, and the new G347A which is a near-isotropic fine-grained graphite. We report the results of room temperature inelastic neutron scattering measurements for the scattering function, double differential scattering cross-section, and phonon density of states. The obtained results are discussed in conjunction with results extracted from first-principles lattice dynamics simulations of crystalline graphite, using the incoherent approximation and by also including the coherent-one phonon contribution. Excellent agreements have been found between the measured and calculated scattering functions and phonon densities of states. The inclusion of the coherent-one phonon scattering shows a significant improvement of the calculated scattering functions, double differentials, and inelastic scattering cross-sections. We also highlight the physical concerns about the current thermal neutron scattering ENDF/B-VIII of nuclear graphite library and its corresponding phonon density of states. This work aims to provide a new presentation of neutron thermalization by graphite and offers a new set of high quality experimental and computational data for consideration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Effect of solutes on the lattice parameters and elastic stiffness coefficients of body-centered tetragonal Fe

In this study, we compute changes in the lattice parameters and elastic stiffness coefficients C ij of body-centered tetragonal (bct) Fe due to Al, B, C, Cu, Mn, Si, and N solutes. Solute strain misfit tensors determine changes in the lattice parameters as well as strain contributions to the changes in the C ij . We also compute chemical contributions to the changes in the C ij , and show that the sum of the strain and chemical contributions agree with more computationally expensive direct calculations that simultaneously incorporate both contributions. Octahedral interstitial solutes, with C being the most important addition in steels, must be present to stabilize the bct phase over the body-centered cubic phase. We therefore compute the effects of interactions between interstitial C solutes and substitutional solutes on the bct lattice parameters and C ij for all possible solute configurations in the dilute limit, and thermally average the results to obtain effective changes in properties due to each solute. Finally, the computed data can be used to estimate solute-induced changes in mechanical properties such as strength and ductility, and can be directly incorporated into mesoscale simulations of multiphase steels to model solute effects on the bct martensite phase.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A general predictive methodology for fuel-mixture properties up to supercritical conditions

A predictive thermodynamic model is utilized for the calculation of fuel properties of oxymethylene dimethyl ethers (OME 3–4 ), surrogates for gasoline, diesel and aviation fuel, as well as alcohol blends with gasoline and diesel. The alcohols used for these blends are methanol, ethanol, propanol, butanol and pentanol; their mixing ratio ranges from 10 to 50% by volume. The model is based on the Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EoS) and Vapor Liquid Equilibrium (VLE) calculations at constant temperature, density and composition. The model includes the association term, with the assumption of two association sites (2B scheme), to enable the modeling of alcohols. The pure-component parameters are estimated based on the Group Contribution (GC) method of various sources, as well as a parametrization model specifically designed for the case of OME 3–4 . The results of the computational model for the density, vapor pressure and distillation curves at various conditions, including high-pressure, high-temperature (HPHT), are compared to experimental and computational data available in the literature. In the cases where no measurements are available for the surrogates, experimental data for the corresponding target fuel are used, taking into consideration the inherent deviation in properties between real and surrogate fuel. Overall, the results are in good agreement with the data from the literature, with the average deviation not exceeding 12% for temperature (Kelvin) on the distillation curves, 10% for density and 46% for vapor pressure and the general trend being captured successfully. The use of different pure component parameter estimation techniques can further improve the prediction quality in the cases of OME3–4 and the aviation fuel surrogate, especially for the vapor pressure, leading to an average deviation lower than 18%. These results demonstrate the predictive capabilities of the model, which extend to a wide range of fuel types and pressure/temperature conditions. Through this investigation, the present work aims to establish the limits of applicability of this thermodynamic property prediction methodology.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Reduction of uranyl and uranyl-organic complexes mediated by magnetite and ilmenite: A combined electrochemical AFM and DFT study

Reduction of mobile aqueous uranyl complexes can be hindered by the strength of the uranyl-ligand complex and the resistivity of the complexes to electron transfer. Semiconducting solids, such as magnetite (Fe 3 O 4 ) and ilmenite (FeTiO 3 ), can facilitate otherwise-slow electron transfer between the reductant and oxidant, especially if these species are adsorbed on their surfaces as inner-sphere complexes. Electrons can then be shuttled through the surface or the structure. This process can be facilitated by either finding a new electron transfer path or by weakening or destroying the ligand-uranyl complex. Using in situ electrochemical atomic force microscopy (EC-AFM), we imaged reduction products of uranyl as mediated by magnetite and ilmenite in the absence or presence of the organic ligands, ethylenediaminetetraacetate (EDTA) and oxalate. In situ images of uranyl reduction show gradual nucleation and growth of reduced uranium on the mineral surfaces with decreasing reduction potentials. X-ray photoelectron spectroscopy (XPS) measurements indicate pentavalent uranium as the dominant uranium species resulting from uranyl reduction mediated by magnetite and ilmenite. The reduction potentials of uranyl-organic species relevant to our reaction system, (U VI O 2 ∙oxalate) 0 and (U VI O 2 ∙HEDTA) - , are derived using quantum–mechanical modeling and compared with the midpoint potentials obtained from cyclic voltammetry measurements. The spectroscopic, electrochemical, and computational data suggest that the catalysis of Fe-bearing minerals facilitates the reduction of uranyl-organic complexes. U(VI)-oxalate complexes are redox-active and participate directly in the reduction mediated by magnetite. In the presence of EDTA, reduction of uranyl may proceed in concert with ligand exchange between metals (i.e., U and Fe) on the mineral surface. Finally, the proposed mechanism is the breaking of uranyl-organic bonds upon interaction with the mineral surface followed by the formation of Fe-organic bonds, thereby allowing the reduction of hexavalent uranyl to pentavalent one.

58 GEOSCIENCES↗
DOE OSTI2022

Energy and mechanical properties predictions in Fe-Ni binary system by ab initio calculations

Here, the fcc random solid solutions in Fe-Ni binary system were investigated using ab initio calculations. Density functional theory (DFT) was applied along with supercells generated by the Special Quasi-Random Structure (SQS) method to predict the enthalpy of mixing and magnetic and elastic properties. The results were compared with relevant experimental and computational data produced by other groups. The effect of SQS supercell size and relaxation procedure on the predicted properties of the alloys were also studied. Our calculations show that 16-atoms SQS model provides adequate approach to the mixing energy of the alloy. However, calculation of mechanical properties requires larger supercell. Excellent agreement between experimental and calculated elastic properties was found in fcc region of Fe-Ni system.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Extracting a mixing parameter from 2D radiographic imaging of variable-density turbulent flow

We extract a suitably averaged fluctuating density from the two-dimensional radiographic image of a flow. The X-ray attenuation is given by the Beer–Lambert law which exponentially damps the incident beam intensity by a factor proportional to the density, opacity and thickness of the target. By making reasonable assumptions for the mean density, opacity and effective thickness of the target flow, we estimate the density fluctuation contribution to the attenuation. The extracted density fluctuations averaged across the thickness of the flow in the direction of the beam may be used to form the density–specific-volume correlation $b$. In a statistical description of variable-density turbulence, $b$ quantifies the degree of mixedness. The ability to extract a measure of mixedness from experimental data would be a powerful tool that could be used in the validation of mix models. The scheme proposed is tested for DNS data computed for variable density buoyancy-driven mixing. We quantify the deficits in the extracted value of $b$ due to target thickness, Atwood number and modeled signal noise. This analysis justifies using the proposed scheme to infer the mix parameter from thin targets at moderate to low Atwood numbers. Furthermore, to illustrate how the scheme might be used in a practical problem, we demonstrate its application to a radiographic image of counter-shear flow obtained from experiments at the National Ignition Facility.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Robust Machine Learning Inference from X-ray Absorption Near Edge Spectra through Featurization

X-ray absorption spectroscopy (XAS) is a commonly employed technique for characterizing functional materials. In particular, X-ray absorption near edge spectra (XANES) encode local coordination and electronic information, and machine learning approaches to extract this information are of significant interest. To date, most ML approaches for XANES have primarily focused on using the raw spectral intensities as input, overlooking the potential benefits of incorporating spectral transformations and dimensionality reduction techniques into ML predictions. Here, in this work, we focused on systematically comparing the impact of different featurization methods on the performance of ML models for XAS analysis. We evaluated the classification and regression capabilities of these models on computed data sets and validated their performance on previously unseen experimental data sets. Our analysis revealed an intriguing discovery: the cumulative distribution function feature achieves both high prediction accuracy and exceptional transferability. This remarkably robust performance can be attributed to its tolerance to horizontal shifts in the spectra, which is crucial when validating models using experimental data. While this work exclusively focuses on XANES analysis, we anticipate that the methodology presented here will hold promise as a versatile asset to the broader spectroscopy community.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Coordination Chemistry of a Strongly-Donating Hydroxylamine with Early Actinides: An Investigation of Redox Properties and Electronic Structure

Separations of f-block elements are a critical aspect of nuclear waste processing. Redox-based separations offer promise, but challenges remain in stabilizing and differentiating actinides in high oxidation states. The investigation of new ligand types that provide thermodynamic stabilization to high-valent actinides is essential for expanding their fundamental chemistry and to elaborate new separation techniques and storage methods. We report herein the preparation and characterization of Th and U complexes of the pyridyl-hydroxylamine ligand, N-tert-butyl-N-(pyridin-2-yl)hydroxylamine (pyNO–). Electrochemical studies performed on the homoleptic complexes [M(pyNO) 4 ] (M = Th, U) revealed significant stabilization of the U complex upon one-electron oxidation. The salt [U(pyNO) 4 ] + was isolated by chemical oxidation of [U(pyNO) 4 ]; spectroscopic and computational data support assignment as a U V cation.

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

Elucidation of the Structure and Vibrational Spectroscopy of Synthetic Metaschoepite and Its Dehydration Product

We confirm that synthetic uranyl hydroxide hydrate metaschoepite [(UO)2 4 O(OH) 6 ]·5H 2 O is unstable against dehydration under dry conditions, and we present a structural and vibrational spectroscopic study of synthetic metaschoepite and its ambient temperature dehydration product. Complementary structural (X-ray diffraction and neutron diffraction) and vibrational spectroscopic techniques (Raman spectroscopy, infrared spectroscopy, and inelastic neutron scattering) are used to probe different components of these species. Analysis of the dehydration product suggests that it contains both pentagonally coordinated and hexagonally coordinated uranyl ions, necessitating that some uranyl ions undergo a coordination change during the dehydration of pentagonally coordinated metaschoepite. Vibrational spectra of metaschoepite and its dehydration product are interpreted with power spectra generated from ab initio molecular dynamics trajectories, allowing assignment of all major features. We identify the uranyl symmetric stretching modes of the four distinct uranyl ions in synthetic metaschoepite and clarify the assignment of lower energy Raman modes in both structures. Finally, the coanalysis of experimental and computational data reveals a strong coupling between the uranyl stretching modes and hydroxide bending modes in the anhydrous structure, leading to the presence of several high-energy combination bands in the inelastic neutron scattering data.

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

In the Mix : A Workshop Merging Computational Chemistry and Electrochemistry Alongside Data Science

As chemistry expands to more complex and interdisciplinary areas, a new generation of diverse researchers must engage with science and learn effective cross-disciplinary collaboration and communication. To these ends, we designed and implemented In the Mix, a graduate student-led, two-day workshop for undergraduate students promoting collaborative science in the context of energy storage innovations. Here, the interactive workshop was designed for future and emerging researchers to gain hands-on experience with data science, computational chemistry, and electrochemistry techniques that are critical for developing materials for battery technologies. Participants also visited commercial renewable energy facilities to help them connect discovery-based research with industry and broader societal considerations. The workshop content and structure ensured that participants experienced the interrelatedness of the fields and understood the importance of collaborative research to yield scientific advances with real-world applications. An external team evaluated the workshop and participants’ perceptions of their experiences. While our research context was energy storage, the workshop goals and outcomes are applicable to other contexts. Interdisciplinary, experiential workshops are a key avenue to broadening participation in science and research, and the ideas presented here can be readily modified for other scientific contexts and/or incorporated as broader impact activities.

25 ENERGY STORAGE↗
DOE OSTI2024

Diffusion-Limited Kinetics in Reactive Systems

A proper representation of chemical kinetics is vital to understanding, modeling, and optimizing many important chemical processes. In liquid and surface phases, where diffusion is slow, the rate at which the reactants diffuse together limits the overall rate of many elementary reactions. Commonly, the textbook Smoluchowski theory is utilized to estimate effective rate coefficients in the liquid phase. On surfaces, modelers commonly resort to much more complex and expensive Kinetic Monte Carlo (KMC) simulations. Here, in this study, we extend the Smoluchowski model to allow the diffusing species to undergo chemical reactions and derive analytical formulas for the diffusion-limited rate coefficients for 3D, 2D, and 2D/3D interface cases. With these equations, we are able to demonstrate that when species react faster than they diffuse they can react orders of magnitude faster than predicted by Smoluchowski theory, through what we term “the reactive transport effect”. We validate the derived steady-state equations against particle Monte Carlo (PMC) simulations, KMC simulations, and non-steady-state solutions. Furthermore, using PMC and KMC simulations, we propose corrections that agree with all limits and the computed data for the 2D and 2D/3D interface steady-state equations, accounting for unique limitations in the associated derived equations. Additionally, we derive equations to handle couplings between diffusion-limited rate coefficients in reaction networks. We believe these equations should make it possible to run much more accurate mean-field simulations of liquids, surfaces, and liquid–surface interfaces accounting for diffusion limitations and the reactive transport effect.

Johnson, Matthew Sean↗