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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Controlling kinetic and diffusive length-scales during absorptive hydrogen removal in methane dehydroaromatization on MoC x /H-ZSM-5 catalysts

Addition of Zr metal absorbent to MoC x /H-ZSM-5 in the form of staged-bed, stratified-bed, and interpellet physical mixtures effectively scavenges H 2 from catalyst proximity, enhancing maximum single-pass benzene + naphthalene yield during methane dehydroaromatization (DHA) reactions to 14-16% compared to 8% in formulations without zirconium. The coupling of spatially-distinct catalytic and absorptive functions is achieved by dispersive/diffusive transport which conveys H 2 to staged Zr both co- and counter-current to bulk advection, thereby suppressing axial H 2 partial pressure profiles along the catalyst bed and enhancing net aromatization rates. We evince hitherto unreported significance of dispersive hydrogen transport during methane DHA by measurement of Péclet number, Pe = 1.32, in H 2 tracer studies with step-change or impulse input to inert catalyst proxies. Kinetic limits to methane pyrolysis are quantified by Damköhler number, Da, for synthesis of benzene, Da B = 0.15, and naphthalene, Da N = 0.03, determined from kinetic studies which rigorously account for reversibility of DHA reactions. Here, detailed reaction-transport models synthesize interplay of kinetic, diffusive, and convective length-scales captured by Péclet and Damköhler number to predict influence of catalyst-absorbent proximity and process flow-conditions on aromatization rates. Systematic control of catalyst bed-length, L, or linear flow velocity, u, predictably alters Pe and Da to effect improvements in methane conversion with and without Zr metal, corroborating results from simulation of the reaction-transport model.

03 NATURAL GAS↗
DOE OSTI2019

Controlled Design of Phase- and Size-Tunable Monodisperse Ni 2 P Nanoparticles in a Phosphonium-Based Ionic Liquid through Response Surface Methodology

Nanoparticles of nickel phosphide are finding wide ranging utility as catalysts for hydrodesulfurization, hydrogen evolution reaction, and hydrodeoxygenation of bio-oils. Herein, we present a methodology to tailor monodisperse nickel phosphide nanoparticles in terms of size and phase through the use of a statistical response surface methodology. Colloidal nickel phosphide nanoparticles were synthesized by replacing octadecene (ODE), a commonly used organic solvent, by a more sustainable phosphonium-based ionic liquid (IL). The replacement of ODE with the phosphonium-based IL resulted in faster crystallization at lower temperatures to yield phase-pure, monodisperse Ni2P nanoparticles. Using a first-order design, the PPh3/Ni precursor ratio was identified as the most critical factor influencing the resulting size and phase of the nanoparticles. Optimization using a Doehlert matrix for second-order design yielded a second-degree polynomial equation used to predict the mean diameter of the nanoparticles (over a range of 4-12 nm) as a function of the PPh3/Ni precursor ratio and the temperature used during synthesis. The resulting model was validated by performing reactions using randomly chosen sets of conditions; the experimentally determined nanoparticle sizes were in excellent agreement with the theoretical sizes predicted by our model. This demonstrates the utility of a multivariate experimental design as a powerful tool in the development of synthetic strategies toward the preparation of colloidal nanoparticles with highly controlled size, size distribution, and phase.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Reduction of Plutonium(VI) to (V) by Hydroxamate Compounds at Environmentally Relevant pH

Natural organic matter is known to influence the mobility of plutonium (Pu) in the environment via complexation and reduction mechanisms. Hydroxamate siderophores have been specifically implicated due to their strong association with Pu. Hydroxamate siderophores can also break down into di and mono-hydroxamates and may influence Pu oxidation state, and thereby its mobility. In this study we explored the reactions of Pu(VI) and Pu(V) with a mono-hydroxamate compound (acetohydroxamic acid, AHA) and a tri-hydroxamate siderophore desferrioxamine B (DFOB) at environmentally relevant pH (5.5-8.2). Pu(VI) was instantaneously reduced to Pu(V) upon reaction with AHA. The presence of hydroxylamine was not observed at these pHs; however, AHA was consumed during the reaction. This suggests that the reduction of Pu(VI) to Pu(V) by AHA is facilitated by direct one electron transfer. Importantly, further reduction to Pu(IV) or Pu(III) was not observed, even with excess AHA. We believe that further reduction of Pu(V) did not occur because Pu(V) does not form a strong complex with hydroxamate compounds at circum-neutral pH. Experiments performed using desferrioxamine B (DFOB) yielded similar results. Broadly, this suggests that Pu(V) reduction to Pu(IV) in the presence of natural organic matter is not facilitated by hydroxamate functional groups and that other natural organic matter moieties likely play a more prominent role.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

To address surface reaction network complexity using scaling relations machine learning and DFT calculations

Surface reaction networks involving hydrocarbons exhibit enormous complexity with thousands of species and reactions for all but the very simplest of chemistries. We present a framework for optimization under uncertainty for heterogeneous catalysis reaction networks using surrogate models that are trained on the fly. The surrogate model is constructed by teaching a Gaussian process adsorption energies based on group additivity fingerprints, combined with transition-state scaling relations and a simple classifier for determining the rate-limiting step. The surrogate model is iteratively used to predict the most important reaction step to be calculated explicitly with computationally demanding electronic structure theory. Applying these methods to the reaction of syngas on rhodium(111), we identify the most likely reaction mechanism. Lastly, propagating uncertainty throughout this process yields the likelihood that the final mechanism is complete given measurements on only a subset of the entire network and uncertainty in the underlying density functional theory calculations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Non-chemisorbed gold–sulfur binding prevails in self-assembled monolayers

Gold–thiol contacts are ubiquitous across the physical and biological sciences in connecting organic molecules to surfaces. When thiols bind to gold in self-assembled monolayers (SAMs) the fate of the hydrogen remains a subject of profound debate—with implications for our understanding of their physical properties, spectroscopic features and formation mechanism(s). Exploiting measurements of the transmission through a molecular junction, which is highly sensitive to the nature of the molecule–electrode contact, we demonstrate here that the nature of the gold–sulfur bond in SAMs can be probed via single-molecule conductance measurements. Critically, we find that SAM measurements of dithiol-terminated molecular junctions yield a significantly lower conductance than solution measurements of the same molecule. Through numerous control experiments, conductance noise analysis and transport calculations based on density functional theory, we show that the gold–sulfur bond in SAMs prepared from the solution deposition of dithiols does not have chemisorbed character, which strongly suggests that under these widely used preparation conditions the hydrogen is retained.

Inkpen, Michael S.↗
DOE OSTI2019

Synthesis of [18F]-γ-Fluoro-α,β-unsaturated Esters and Ketones via Vinylogous 18F-Fluorination of α-Diazoacetates with [18F]AgF

This communication reports a method for the vinylogous radiofluorination of α-diazoacetates to generate [18F]-γ-fluoro-α,β-unsaturated esters and ketones in moderate to good radiochemical yields. The method uses no-carrier-added [18F]AgF and is compatible with aromatic and non-aromatic substrates and a number of different functional groups. The labeling method is showcased in the synthesis of a fluorinated cholest-5-en-3-one derivative as well as a difluorinated product pertinent to drug discovery.

Chemistry↗
DOE OSTI2019

Probing the interplay between geometric and electronic-structure features via high-harmonic spectroscopy

We present molecular-frame measurements of the recombination dipole matrix element (RDME) in CO 2 , N 2 O, and carbonyl sulfide (OCS) molecules using high-harmonic spectroscopy. Both the amplitudes and phases of the RDMEs exhibit clear imprints of a two-center interference minimum, which moves in energy with the molecular alignment angle relative to the laser polarization. Here, we find that whereas the angle dependence of this minimum is consistent with the molecular geometry in CO 2 and N 2 O, it behaves very differently in OCS; in particular, the phase shift which accompanies the two-center minimum changes sign for different alignment angles. Our results suggest that two interfering structural features contribute to the OCS RDME, namely, (i) the geometrical two-center minimum and (ii) a Cooper-like, electronic-structure minimum associated with the sulfur end of the molecule. We compare our results to ab initio calculations using time-dependent density functional theory and present an empirical model that captures both the two-center and the Cooper-like interferences. We also show that the yield from unaligned samples of two-center molecules is, in general, reduced at high photon energies compared to aligned samples, due to the destructive interference between molecules with different alignments.

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

Atom Probe Tomography for the Observation of Hydrogen in Materials: A Review

Atom probe tomography (APT) is an emerging microscopy technique that has high sensitivity for hydrogen with sub-nanometre-scale spatial resolution, which makes it a unique method to investigate the atomic-scale distribution of hydrogen at interfaces and defects in materials. This article introduces the basics of APT-based hydrogen analysis, particularly the challenge of distinguishing a hydrogen background signal in APT by using hydrogen isotopes, along with strategies to yield high-quality analysis. This article also reviews several important findings on hydrogen distribution in a range of materials, including both structural alloys and functional materials, enabled by using APT. Limitations and future opportunities for hydrogen analysis by APT are also discussed.

42 ENGINEERING↗
DOE OSTI2019

Perfect separation of intraband and interband excitations in PdCoO 2

The temperature dependence of the optical properties of the delafossite PdCoO 2 has been measured in the a-b planes over a wide frequency range. The optical conductivity due to the free-carrier (intraband) response falls well below the interband transitions, allowing the plasma frequency to be determined from the f-sum rule. Drude-Lorentz fits to the complex optical conductivity yield estimates for the free-carrier plasma frequency and scattering rate. Here, the in-plane plasma frequency has also been calculated using density functional theory. The experimentally determined and calculated values for the plasma frequencies are all in good agreement; however, at low temperature the optically determined scattering rate is much larger than the estimate for the transport scattering rate, indicating a strong frequency-dependent renormalization of the optical scattering rate. In addition to the expected in-plane infrared-active modes, two very strong features are observed that are attributed to the coupling of the in-plane carriers to the out-of-plane longitudinal optic modes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Nonperturbative-transverse-momentum effects and evolution in dihadron and direct photon-hadron angular correlations in p + p collisions at $\sqrt{s}$ = 510 GeV

Dihadron and isolated direct photon-hadron angular correlations are measured in p + p collisions at $\sqrt{s}$=510 GeV. Correlations of charged hadrons of 0.7 < p T < 10 GeV/c with $\pi$ 0 mesons of 4 < p T < 15 GeV/c or isolated direct photons of 7 < p T < 15 GeV/c are used to study nonperturbative effects generated by initial-state partonic transverse momentum and final-state transverse momentum from fragmentation. The nonperturbative behavior is characterized by measuring the out-of-plane transverse momentum component p out perpendicular to the axis of the trigger particle, which is the high-p T direct photon or $\pi$ 0 . Nonperturbative evolution effects are extracted from Gaussian fits to the away-side inclusive-charged-hadron yields for different trigger-particle transverse momenta ($p^{trig}_{T}$). The Gaussian widths and root mean square of p out are reported as a function of the interaction hard scale $p^{trig}_{T}$ to investigate possible transverse-momentum-dependent evolution differences between the $\pi$ 0 -h ± and direct photon-h ± correlations and factorization breaking effects. The widths are found to decrease with $p^{trig}_{T}$, which indicates that the Collins-Soper-Sterman soft factor is not driving the evolution with the hard scale in nearly back-to-back dihadron and direct photon-hadron production in p + p collisions. In conclusion, this behavior is in contrast to Drell-Yan and semi-inclusive deep-inelastic scattering measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

An ultrapotent synthetic nanobody neutralizes SARS-CoV-2 by stabilizing inactive Spike

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus enters host cells via an interaction between its Spike protein and the host cell receptor angiotensin-converting enzyme 2 (ACE2). By screening a yeast surface-displayed library of synthetic nanobody sequences, we developed nanobodies that disrupt the interaction between Spike and ACE2. Cryo–electron microscopy (cryo-EM) revealed that one nanobody, Nb6, binds Spike in a fully inactive conformation with its receptor binding domains locked into their inaccessible down state, incapable of binding ACE2. Affinity maturation and structure-guided design of multivalency yielded a trivalent nanobody, mNb6-tri, with femtomolar affinity for Spike and picomolar neutralization of SARS-CoV-2 infection. mNb6-tri retains function after aerosolization, lyophilization, and heat treatment, which enables aerosol-mediated delivery of this potent neutralizer directly to the airway epithelia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

SPERLU Selective Process for Efficient Removal of Lignin and Upgrading (Final Technical Report)

To meet the growing demand for bio-based chemicals and improve the profitability and efficiency of the emerging biorefinery industry, lignin is an abundant and attractive feedstock. Spero Renewables has developed a proprietary and patent-pending technology, the Selective Process for Efficient Removal of Lignin and Upgrading (SPERLU). The technology is a catalytic deconstruction and upgrading of lignin in lignocellulosic biomass or commercially available technical lignin to produce multi-functional phenol (MFP) products. The SPERLU process has been demonstrated and vetted on a lab scale to convert commercially available technical lignin to MFPs in yields of 60-90% (based on lignin). The MFP products can be separated and further upgraded through catalytic or biological means. Spero performed a detailed kinetic study of the SPERLU process and used the resulting kinetic data to design and construct a mini-pilot-scale reactor for routine production of hundreds of grams of MFP products. Spero’s lignin-based MFPs have been demonstrated for use as a drop-in replacement for bisphenol A (BPA) in the synthesis of thermoset polymers. Spero’s lignin-based thermoset polymers exhibit excellent mechanical properties and can be used in many applications. Additionally, a collaboration with the National Renewable Energy Lab (NREL) was used to evaluate the feasibility of upgrading SPERLU products through biological means into valuable chemicals. A comprehensive technoeconomic analysis (TEA) and Life-cycle analysis (LCA) have been completed and support the case for commercialization of the SPERLU technology. Through this project Spero has significantly de-risked the SPERLU technology and is actively planning larger scale pilot projects.

09 BIOMASS FUELS↗
DOE OSTI2025

Advancing Neutrino Simulation Modeling with MARLEY: Insights from the NNSA-MSIIP Internship

Core-collapse supernovae are intense sources of tens-of-MeV neutrinos. However, there is no experimental data to validate the current event generator MARLEY (Model of Argon Reaction Low Energy Yields) that can model supernova neutrinos. To validate the model, I developed a new muon capture feature within the MARLEY simulation framework by coding key functions in C++, Python, and ROOT. I generated and analyzed one million simulated muon capture events and comparing the results to experimental data. To improve the model, I worked on optimizing the model’s parameters to improve its precision using statistical methods.

Wong, Baker [Fermilab]↗
DOE OSTI2022

Search For Excited Cascade Hypersons (¿*-) Using the CLAS12 Spectrometer at Jefferson Laboratory

The number of experimentally observed doubly strange Cascade states to date is far fewer than has been predicted theoretically. The CLAS12 Very Strange physics program (E12- 11-005A) at the Thomas Jefferson National Accelerator Facility aims to study the electroproduction of these states using the newly upgraded CEBAF Large Acceptance Spectrometer for 12 GeV (CLAS12) in experimental Hall B. In this project, the reaction ep ! e0K+K+??? ! e0K+K+K?(?=?0) is studied using CLAS12 Run Group A (RG-A) data sets taken by impinging electron beams of 10:2 and 10:6 GeV energies on an LH2 target. Scattered electrons are detected with either the Forward Detector (FD), covering a polar angle range of 5? to 35? to study electroproduction, or with the Forward Tagger (FT), covering a polar angle range of 2:5? to 4:5?, to study quasi-real photoproduction. The CLAS12 detector with nearly a 4? solid angle coverage is used to detect scattered electrons and charged kaons in the ?final state. ?=?0 hyperons are reconstructed using the missing mass technique to explore intermediate doubly-strange hyperons (???) that decay to K? and ?=?0. No statistically significant ??? states other than the ???(1530) were found in the missing mass spectra based on the currently available statistics in the CLAS12-FD acceptance only. A maximum log-likelihood method is implemented to determine the statistical significance and the upper limits on the ???(1820) electroproduction cross section by constructing 95% confidence level boundaries on the ???(1820) yields. Additional research was conducted to investigate the upper limit electroproduction cross section of the reaction ep ! e0K+K+??? ! e0K+K+K?(?=?0) as a function of the electroproduced ??? mass and the differential cross section ( d?dMM(e0K+K+) ) as a function of missing mass MM(e0K+K+) for electroproduction and quasi-real photoproduction processes.

Khanal, Achyut↗
DOE OSTI2020

Importance of van der Waals interactions for ab initio studies of topological insulators

We investigate the lattice and electronic structures of the bulk and surface of the prototypical layered topological insulators Bi 2 Se 3 and Bi 2 Te 3 using ab initio density functional methods, and systematically compare the results of different methods of including van der Waals (vdW) interactions. We show that the methods utilizing semi-empirical energy corrections yield accurate descriptions of these materials, with the most precise results obtained by properly accounting for the long-range tail of the vdW interactions. The bulk lattice constants, distances between quintuple layers and the Dirac velocity of the topological surface states (TSS) are all in excellent agreement with experiment. In Bi 2 Te 3 , hexagonal warping of the energy dispersion leads to complex spin textures of the TSS at moderate energies, while in Bi 2 Se 3 these states remain almost perfectly helical away from the Dirac point, showing appreciable signs of hexagonal warping at much higher energies, above the minimum of the bulk conduction band. Furthermore, our results establish a framework for unified and systematic self-consistent first principles calculations of topological insulators in bulk, slab and interface geometries, and provides the necessary first step toward ab initio modeling of topological heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Linking Plant and Microbial Traits to Soil Carbon for Reliable and Resilient Bioenergy Systems

Bioenergy systems in the United States offer a dual opportunity to supply renewable feedstocks while enhancing ecosystem services such as hydrologic regulation, erosion control, and soil carbon (C) storage. National assessments highlight the potential to grow perennial energy crops to improve soil function and ecosystem resilience. Realizing this potential requires understanding the ecological mechanisms that govern how C is added, transformed, and stabilized in soils. Plant traits determine the quantity, depth, and chemistry of organic inputs, while microbial processes—including carbon use efficiency, necromass formation, and trophic interactions—mediate their transformation and partitioning among soil carbon pools. These biological pathways are shaped by soil physical and chemical properties, including aggregation, texture, and mineralogy, and by environmental drivers such as temperature, moisture, and disturbance, leading to context-dependent outcomes across landscapes. Management practices that diversify feedstocks, minimize disturbance, and maintain soil cover can promote both biomass production and C retention, while microbial amendments and rhizosphere engineering offer emerging, but often context-dependent, tools to optimize plant–microbe interactions. Trade-offs between biomass yield and soil carbon storage may arise when systems favor rapid aboveground productivity at the expense of belowground inputs and microbial processing, underscoring the importance of trait combinations that support both functions. Advances in monitoring, reporting, and verification—spanning precision agriculture, remote sensing, and biosensing—are improving predictive capacity through microbial-explicit process models and model–experiment (ModEx) frameworks. By connecting soil, plant, and microbial processes with advances in modeling and biosensing, this review outlines research priorities focused on trait-based parameterization and ModEx integration. These priorities will support the design of bioenergy systems that are both reliable and resilient, enhancing renewable energy production and ecosystem sustainability.

bioenergy systems↗
DOE OSTI2020

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗