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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Impact of natural organic matter on plutonium vadose zone migration from an NH4Pu(V)O2CO3(s) source

Large amounts of plutonium produced at the Savannah River Site (SRS) in the latter half of the last century led to the release of plutonium to the subsurface. Low-level waste containing plutonium has also been disposed of in the SRS vadose zone. The mobility and risk posed by these plutonium sources is not well understood, in part, because of unknown interactions of the various mobile plutonium species with natural organic matter (NOM). This study investigated the influence of NOM on the behavior of plutonium(V) in the vadose zone through a combination of field lysimeter and laboratory studies. Well-defined solid sources of NH4PuVO2CO3(s) placed in 5-L lysimeters containing vadose zone soils NOM-amended or unamended were exposed to natural SRS meteorological conditions for three years. These lysimeters were removed from the field and analyzed using wet chemistry methods and X-ray absorption spectroscopy (XAS). Plutonium desorption from soils recovered from the lysimeters and laboratory batch sorption experiments using Pu-free soils both indicated that surface mediated reduction of Pu(V) to Pu(IV) was influencing Pu sorption behavior. For both lysimeters (amended and unamended with NOM), Pu migrated slowly through the lysimeter core, with > 95% of the Pu remaining within 2 cm of the source. However, without the NOM amendments, Pu was transported significantly farther than in the presence of NOM. Thus, the presence of NOM appeared to decrease the mobility. Working hypotheses to explain this behavior are that 1) formation of ternary surface-NOM-Pu complexes enhanced Pu sorption affinity causing less mobility and/or 2) formation of these ternary surface-NOM-Pu complexes prevented reoxidaiton of Pu(IV) to more mobile Pu(V) in the pore water.

plutonium, organic matter↗
DOE OSTI2020

Thermodynamics of CeSiO 4 : Implications for Actinide Orthosilicates

Zircon (ZrSiO 4 : I4 1 /amd) can accommodate actinides, such as thorium, uranium, and plutonium. The zircon structure has been determined for several of the end member compositions of other actinides, such as plutonium and neptunium. However, the thermodynamic properties of these actinide zircon structure-types are largely unknown due to the difficulties in synthesizing these materials and handling transuranium actinides. Thus, we have completed a thermodynamic study of cerium orthosilicate, stetindite (CeSiO 4 ), a surrogate of PuSiO 4 . For the first time, the standard enthalpy of formation of CeSiO 4 was obtained by high temperature oxide melt solution calorimetry to be -1971.9 ± 3.6 kJ/mol. Stetindite is energetically metastable with respect to CeO 2 and SiO 2 by 27.5 ± 3.1 kJ/mol. The metastability explains the rarity of the natural occurrence of stetindite and the difficulty of its synthesis. Applying the obtained enthalpy of formation of CeSiO 4 from this work, along with those previously reported for USiO 4 and ThSiO 4 , we developed an empirical energetic relation for actinide orthosilicates. Here, the predicted enthalpies of formation of AnSiO 4 are then made with a discussion of future strategies to efficiently immobilize Pu or minor actinides in the zircon structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Synthesis of Layered Gold Tellurides AuSbTe and Au 2 Te 3 and Their Semiconducting and Metallic Behavior

Previous studies on natural samples of pampaloite (AuSbTe) revealed the crystal structure of a potentially cleavable and/or exfoliable material, while studies on natural and synthetic montbrayite (Sb-containing Au 2 Te 3 ) claimed various chemical compositions for this low-symmetry compound. Few investigations of synthetic samples have been reported for both materials, leaving much of their chemical, thermal, and electronic characteristics unknown. Here, in this study, we investigate the stability, electronic properties, and synthesis of the gold antimony tellurides AuSbTe and Au 1.9 Sb 0.46 Te 2.64 (montbrayite). Differential thermal analysis and in situ powder X-ray diffraction revealed that AuSbTe is incongruently melting, while Au 1.9 Sb 0.46 Te 2.64 is congruently melting. Calculations of the band structures and four-point resistivity measurements showed that AuSbTe is a semiconductor and Au 1.9 Sb 0.46 Te 2.64 a metal. Various synthesis attempts confirmed the limited stable chemical composition of Au 1.9 Sb 0.46 Te 2.64 , identified successful methods to synthesize both compounds, and highlighted the challenges associated with single-crystal synthesis of AuSbTe.

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

Practical Guide to Chemometric Analysis of Optical Spectroscopic Data

The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least squares (CLS), principal component regression (PCR), and partial least squares (PLS), as well as the univariate Beer’s law method have been described and compared, building students’ understanding by starting with the univariate method and progressing step by step into the multivariate methods. Equations for the production of regression vectors from training set spectral data is described and their use demonstrated for the prediction of constituent concentrations on a separate validation set of spectra. Extreme care is taken to ensure consistency in variable formatting of data matrices. This provides a key foundation to understanding how spectral data are manipulated using these different mathematical approaches for building quantitative regression models. Each method is applied to a real-world data set, and the results are discussed to show students the types of information that can be gleaned from each method. A training set comprised of 20 infrared absorbance spectra containing 3 constituents (benzene, polystyrene, and gasoline) of known composition are used to demonstrate the matrix operations for each regression method. A separate set of 12 real-world napalm samples (containing benzene, polystyrene and gasoline) are used as a validation set to demonstrate the ability to utilize the regression models on an unknown dataset. A toolbox (PNNL Chemometric Toolbox) written in MATLAB language is supplied in the Supplemental Information file and can be used as a companion for understanding the development and deployment of the chemometric algorithms described in this paper. The datasets of the infrared spectra are also supplied, allowing users to build and inspect the chemometric models on their own. Finally, the Toolbox includes scripts to assist users in loading their own datasets into MATLAB and performing CLS, PCR, and PLS on their data.

Upper-Division Undergraduate, Analytical Chemistry↗
DOE OSTI2024

RT-EOM-CCSD Calculations of Inner and Outer Valence Ionization Energies and Spectral Functions

Photoelectron spectroscopy (PES) is a standard experimental method for material characterization, but its interpretation can be hampered by its reliance on standard materials. To facilitate the study of unknown systems, theoretical methods are desirable. Here we present a real-time equation-of-motion coupled cluster (RT-EOM-CC) approach for valence PES, extending our core-level development. Here, we demonstrate that RT-EOM-CC yields ionization energies and spectral functions in good agreement with experiment and CI-based methods, even for some more correlated cases.

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

Generating Protein Structures for Pathway Discovery Using Deep Learning

Resolving the intricate details of biological phenomena at the molecular level is fundamentally limited by both length- and time scales that can be probed experimentally. Molecular dynamics (MD) simulations at various scales are powerful tools frequently employed to offer valuable biological insights beyond experimental resolution. However, while it is relatively simple to observe long-lived, stable configurations of, for example, proteins, at the required spatial resolution, simulating the more interesting rare transitions between such states often takes orders of magnitude longer than what is feasible even on the largest supercomputers available today. One common aspect of this challenge is pathway discovery, where the start and end states of a scientific phenomenon are known or can be approximated, but the mechanistic details in between are unknown. Here, we propose a representation-learning-based solution that uses interpolation and extrapolation in an abstract representation space to synthesize potential transition states, which are automatically validated using MD simulations. The new simulations of the synthesized transition states are subsequently incorporated into the representation learning, leading to an iterative framework for targeted path sampling. Our approach is demonstrated by recovering the transition of a RAS-RAF protein domain (CRD) from membrane-free to interacting with the membrane using coarse-grain MD simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Atomic-Level Features for Kinetic Monte Carlo Models of Complex Chemistry from Molecular Dynamics Simulations

The high computational cost of evaluating atomic interactions recently motivated the development of computationally inexpensive kinetic models, which can be parametrized from MD simulations of complex chemistry of thousands of species or other processes and accelerate the prediction of the chemical evolution by up to four order of magnitude. Such models go beyond the commonly employed potential energy surface fitting methods in that they are aimed purely at describing kinetic effects. So far, such kinetic models utilize molecular descriptions of reactions and have been constrained to only reproduce molecules previously observed in MD simulations. Therefore, these descriptions fail to predict the reactivity of unobserved molecules, for example in the case of large molecules or solids. In this work, we propose a new approach for the extraction of reaction mechanisms and reaction rates from MD simulations, namely the use of atomic-level features. Using the complex chemical network of hydrocarbon pyrolysis as example, it is demonstrated that kinetic models built using atomic features are able to explore chemical reaction pathways never observed in the MD simulations used to parametrize them, a critical feature to describe rare events. Atomic-level features are shown to construct reaction mechanisms and estimate reaction rates of unknown molecular species from elementary atomic events. Through comparisons of the model ability to extrapolate to longer simulation timescales and different chemical compositions than the ones used for parameterization, it is demonstrated that kinetic models employing atomic features retain the same level of accuracy and transferability as the use of features based on molecular species, while being more compact and parametrized with less data. We also find that atomic features can better describe the formation of large molecules enabling the simultaneous description of small molecules and condensed phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Investigating Carboxysome Morphology Dynamics with a Rotationally Invariant Variational Autoencoder

Carboxysomes are a class of bacterial microcompartments that form proteinaceous organelles within the cytoplasm of cyanobacteria and play a central role in photosynthetic metabolism by defining a cellular microenvironment permissive to CO2 fixation. Critical aspects of the assembly of the carboxysomes remain relatively unknown, especially with regard to the dynamics of this microcompartment. Progress in understanding carboxysome dynamics is impeded in part because analysis of the subtle changes in carboxysome morphology with microscopy remains a low-throughput and subjective process. Here we use deep learning techniques, specifically a Rotationally Invariant Variational Autoencoder (rVAE), to analyze fluorescence microscopy images of cyanobacteria bearing a carboxysome reporter and quantitatively evaluate how carboxysome shell remodelling impacts subtle trends in the morphology of the microcompartment over time. Toward this goal, we use a recently developed tool to control endogenous protein levels, including carboxysomal components, in the model cyanobacterium Synechococcous elongatus PCC 7942. By utilization of this system, proteins that compose the carboxysome can be tuned in real time as a method to examine carboxysome dynamics. We find that rVAEs are able to assist in the quantitative evaluation of changes in carboxysome numbers, shape, and size over time. Further, we propose that rVAEs may be a useful tool to accelerate the analysis of carboxysome assembly and dynamics in response to genetic or environmental perturbation and may be more generally useful to probe regulatory processes involving a broader array of bacterial microcompartments.

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

Comparison of Machine Learning Approaches for Prediction of the Equivalent Alkane Carbon Number for Microemulsions Based on Molecular Properties

The chemical properties of oils are vital in the design of microemulsion systems. The hydrophilic–lipophilic difference equation used to predict microemulsions’ phase behavior expresses the oils’ physiochemical properties as the equivalent alkane carbon number (EACN). The experimental determination of EACN requires knowledge of the temperature dependence of the microemulsion system and the effects of different surfactant concentrations. Thus, the experimental determination is time-intensive and tedious, requiring days to months for proper separations. Furthermore, the experiments require high purity of chemicals because microemulsions are sensitive to impurities. Our work focuses on the quick and reliable predictions of the EACN with machine learning (ML) models. Due to the immaturity of ML chemical predictions, we compare three graph neural networks (GNNs) and a gradient-boosted tree algorithm, known as XGBoost. The GNNs use the molecular structures represented as simplified molecular-input line-entry system (SMILES) codes for the initial input, which allows us to assess whether geometry optimization is necessary for reliable results. The XGBoost model also begins with the SMILES representations of the molecules but uses molecular descriptors instead of geometry optimizations. As a result, the best model tested (crystal graph convolutional neural network with Merck molecular force field-94) has an error of 1.15 EACN units of the true EACN for unknown data with the errors skewed toward zero and an R² score of 0.9

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The Effect of Core-Hole Shape on Attosecond Valence Electron Dynamics

Rapid X-ray ionization of a core electron is known to induce the attosecond motion of valence electrons; however, the effect of core-hole shape on the triggered dynamics remains relatively unknown. In this work, the sub-four fs response of prototypical functionalized/heterocyclic/polycyclic molecules was simulated using real-time time-dependent density functional theory (RT-TDDFT), a sudden approximation core-hole, and phenomenologically Auger–Meitner (AM) decay. These molecules included fluorobenzene, chlorobenzene, bromobenzene, phenol, thiophenol, pyridine, phosphorus, and azulene. It is observed that the valence electron dynamics are essentially independent of the core-hole created, provided that it is ionized from an inner-shell orbital and not an inner-valence orbital. This has broad implications for free-electron laser studies of X-ray pumped attosecond processes since the flexibility in edge allows for a wide range of experimental modalities, core-holes with longer AM lifetimes, and molecular targets.

aromatic compounds↗
DOE OSTI2020

Anharmonic phonon dispersion in polyethylene

The second-order Green's function method for anharmonic crystals has been applied to an infinite, periodic chain of polyethylene taking into account up to quartic force constants. The frequency-independent approximation to the Dyson self-energy gives rise to numerous divergent resonances, which are fortuitous. Instead, solving the Dyson equation self-consistently with a frequency-dependent self-energy resists divergences from resonances or zero-frequency acoustic vibrations. Here, the calculated anharmonic phonon dispersion, which nonetheless displays many true resonances, and anharmonic phonon density of states furnish hitherto unknown details that explain smaller features of observed vibrational spectra.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Radiolytic Evaluation of 3,4,3-LI(1,2-HOPO) in Aqueous Solutions

We report the octadentate hydroxypyridinone ligand 3,4,3-LI(1,2-HOPO) (abbreviated as HOPO) has been identified as a promising candidate for both chelation and f-element separation technologies, two applications that require optimal performance in radiation environments. However, the radiation robustness of HOPO is currently unknown. Here, we employ a combination of time-resolved (electron pulse) and steady-state (alpha self-radiolysis) irradiation techniques to elucidate the basic chemistry of HOPO and its f-element complexes in aqueous radiation environments. Chemical kinetics were measured for the reaction of HOPO and its Nd(III) ion complex ([Nd III (HOPO)] - ) with key aqueous radiation-induced radical transients (eaq - , H · atom, and · OH and NO 3 · radicals). The reaction of HOPO with eaq - is believed to proceed via reduction of the hydroxypyridinone moiety, while transient adduct spectra indicate that reactions with the H · atom and · OH and NO 3 · radicals proceeded by addition to HOPO's hydroxypyridinone rings, potentially allowing for the generation of an extensive suite of addition products. Complementary steady-state 241 Am(III)-HOPO complex ([ 241 Am III (HOPO)] - ) irradiations showed the gradual release of 241 Am(III) ions with increasing alpha dose up to 100 kGy, although complete ligand destruction was not observed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Investigating Electron Conductivity Regimes in the Bacterial Cytochrome Wire OmcS

The anaerobic bacterium Geobacter sulfurreducens produces extracellular, electronically conductive cytochrome polymer wires that are conductive over micron length scales. Structure models from cryo-electron microscopy data show OmcS wires form a linear chain of hemes along the protein wire axis, which is proposed as the structural basis supporting their electronic properties. However, the mechanism by which this heme arrangement supports long-range electronic conduction remains unknown. Structure models from cryo-electron microscopy data show these wires form a linear chain of hemes along the protein wire axis, which is proposed as the structural basis supporting their electronic properties. Existing computational models using static heme redox potentials and coupling energies fail to explain experimental observations, predicting conductances 10,000 to 100,000 times lower than measured values. Here, we investigate how dynamic disorder affects site energies, interheme coupling, and long-range electronic conductivity within these cytochrome wires. We introduce an approach to extract charge carrier site information directly from Kohn–Sham density functional theory, without employing projector schemes, and show that site and coupling energies are highly sensitive to changes in interheme geometry and the surrounding electrostatic environment. Unlike models that incorporate dynamic disorder as a thermally averaged quantity, our quantum charge carrier model incorporates proxies for dynamic disorder through decoherence corrections, yielding predicted diffusion coefficient closer to what is expected from experiment and comparable with other organic-based electronic materials. Based on these simulations, we propose that the instantaneous fluctuations of the local electrostatic environment can transiently lift energy degeneracies and delocalize charge carriers. Furthermore, these studies reveal how incorporating dynamic fluctuations associated with the environment resolves the discrepancy between theory and experiment in microbial cytochrome wires and highlight design principles for bioinspired, heme-based conductive materials.

Bioinorganic chemistry↗
DOE OSTI2026

Phosphoserine Charge State Drives Ion Condensation and Spatial Polyamine Presentation in Multirepeat Silaffin

Diatom silaffins direct silica biomineralization through heavily post-translationally modified repeat domains, yet how these modifications reshape the multirepeat conformational ensemble remains unknown. We report all-atom MD simulations of a 195-residue construct spanning repeats R1–R7 of Sil1p from Cylindrotheca fusiformis, carrying the full complement of native PTMs: phosphoserine (pSer), long-chain polyamines (LCPA), dimethyllysine (MLY), and trimethylhydroxylysine phosphate (TPL). We simulated three variants (Native, P1/singly deprotonated phosphate, and P2/doubly deprotonated phosphate) at two NaCl concentrations in triplicate for 500 ns each. All systems disorder from the AlphaFold 3 starting structure. Phosphate charge state, not ionic strength, is the dominant control of ensemble compaction and ion organization. Doubly deprotonated phosphate organizes an extensive Na + condensation shell (∼100 ions, 20% of box Na + ) and a heterogeneous bridging network that integrates both pSer and TPL phosphate groups. The resulting ensemble is compact with LCPA side chains exhibiting above-median solvent accessibility in 84% of simulation frames in P2 at 300 mM. This is higher than any other condition we simulated and indicates that polyamine groups are preferentially surface-presented in the most compact, ion-organized state. A charge-neutralization control confirms that this compact state is a structured intermediate maintained by the bridging network, not a simple collapsed globule. Here, this repeat-scale spatial organization is not captured by single-repeat peptide studies. Understanding the dynamics, mechanism, and spatial organization of PTM-rich silaffin at the repeat scale is a step closer to hierarchical biomimetic materials beyond simple silica morphologies.

Amines↗
DOE OSTI2020

Aromaticity as a Guide to Planarity in Conjugated Molecules and Polymers

Conjugated molecules and polymers have the ability to be transformative semiconducting materials; however, to reach their full potential a detailed understanding of the factors governing the molecular structure is crucial for establishing design principles for improved materials. Creating planar or “locking” structures is of particular interest for tuning electronic properties. While noncovalent locks are an effective strategy for increasing planarity, the precise interactions leading to these planar structures are often unknown or mischaracterized. Here, we demonstrate that aromaticity can be used to investigate, interpret, and modify the complex physical interactions which lead to planarity. Furthermore, we clearly illustrate the important role aromaticity has in determining the structure through torsional preferences and find that modern noncovalent locks utilize hyperconjugation to alter aromaticity and increase planarity. We envision that our approach and our explanation of prevalent noncovalent locks will assist in the design of improved materials for organic electronics.

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

Polymer Chain Diffusion in All-Polymer Nanocomposites: Confinement vs Chain Acceleration

All-polymer nanocomposites, in which soft, polymer-based nanoparticles are dispersed in the polymer matrix, have received great interest lately due to their potential use in a range of applications, including drug delivery and self-healing materials. However, the impact of this new class of nanoparticles on the dynamics of a linear polymer matrix in an all-polymer nanocomposite is still largely unknown. In this work, we report that the addition of polystyrene soft nanoparticles accelerates the diffusion of high molecular weight linear PS chains over a range of nanoparticle loadings. Our results show that at nanoparticle loadings below 1%, the diffusion of the linear matrix increases, presumably via a constraint release mechanism. At loadings above 1%, the increase in diffusion is mitigated by confinement effects of the nanoparticles. Thus, the response of these all-polymer nanocomposites is dominated by the balance of entropic confinement of the chain, which slows diffusion and a constraint release mechanism that speeds up the diffusion. However, the diffusion of the linear chain in the all-polymer nanocomposite is faster than that of the same chain in the melt at all loadings, diverging from the behavior of most nanocomposites with hard, impenetrable nanoparticles. Thus, the mechanism that accelerates the chain diffusion dominates in these systems. This behavior is unusual and fundamentally different than what has been reported for nanocomposites with hard inorganic nanoparticles, indicating that new perspectives are needed for these materials where the control of loading can either accelerate or decelerate the dynamics of the matrix in a distinctive manner.

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

Critical Assessment of the Thermodynamics of Vacancy Formation in Fe 2 O 3 Using Hybrid Density Functional Theory

Fe 2 O 3 hematite is a technologically important material with applications in energy storage as well as being the key phase formed in the rust of iron-based materials. Despite this central importance, there is much that is still unknown regarding the properties of defects in Fe 2 O 3 and consequently oxide growth. In this work, using screened hybrid density functional theory (HSE06), we consider the thermodynamics of vacancies in Fe 2 O 3 , considering the effects of ionic and electronic chemical potentials on both iron and oxygen vacancy formation. We find that, in the oxygen-rich limit, iron vacancies are easier to form, though the difference in formation energy between the two vacancies is only about 1 eV. In contrast, in the Fe-rich limit, oxygen vacancies have an extremely low formation energy, only 0.07 eV at mid-gap, and would spontaneously form as the Fermi level is reduced, while Fe vacancies require over 5 eV to form. Consistent with experiment, this indicates that Fe 2 O 3 is relatively easily reduced but not oxidized. However, the theoretical picture is very different when considering other exchange–correlation functionals (GGA + U or SCAN), emphasizing the critical role of the exchange–correlation functional in describing this system accurately.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗