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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Combining Experimental and Theoretical Techniques to Gain an Atomic Level Understanding of the Defect Binding Mechanism in Hard Carbon Anodes for Sodium Ion Batteries

Sodium ion batteries (NIBs) are an attractive alternative to lithium–ion batteries in applications that require large–scale energy storage due to sodium's high natural abundance and low cost. Hard carbon (HC) is the most promising anode material for NIBs; however, there is a knowledge gap in the understanding of the sodium binding mechanism that prevents a rational design of HC. This study tunes sucrose–derived HC via synthesis temperature then evaluates the structural, physical, and electrochemical properties. Neutron total scattering is used to generate structural models by fitting pair distribution functions (PDF) with a combination of molecular dynamics and reverse Monte Carlo methods. From this model, the number and type of structural features are identified, quantified, and correlated to the galvanostatic charge/discharge. A method of PDF “fingerprinting” binding sites using Na probe atoms is developed and analyzing these PDFs reveals an atomistic view of ion binding sites responsible for “defect” storage mechanisms. Combining these techniques results in an atomic–level study that provides a big picture of the Na–binding mechanism in NIBs, which allows for more precise tuning of the structure–property relationships in the future. Finally, the methodologies developed will also enable new strategies for the analysis of amorphous functional materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Structural Properties of Nanometer‐Sized Gold Nanoparticles on a Silicon Substrate

Properties of gold nanoparticles (Au NPs) supported on Si substrates, which have been the focus of recent attention, depend sensitively on the size, structure, and coordination of Au NPs as well as on the processes of interdiffusion and chemical bonding at the Au–Si interface. There is a great need, therefore, for developing structural techniques capable of imaging such nanosystems in atomic detail. Here, it is discussed how the atomic structure of nanometer‐sized Au NPs deposited on a silicon surface can be determined by using high‐energy X‐ray diffraction measurements in combination with an analysis based on atomic‐pair‐distribution functions and advanced reverse Monte Carlo methods. This approach delivers simple and incisive pictures of the structure of Au clusters on Si and reveals direct structural evidence for the emergence of a Au‐silicide interface following room temperature deposition of Au NPs on Si. This study will contribute to designing Au/Si nanostructures with desirable properties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

A Monte Carlo exploration of threefold base geometries for 4d F-theory vacua

Here, we use Monte Carlo methods to explore the set of toric threefold bases that support elliptic Calabi-Yau fourfolds for F-theory compactifications to four dimensions, and study the distribution of geometrically non-Higgsable gauge groups, matter, and quiver structure. We estimate the number of distinct threefold bases in the connected set studied to be ~ 10 48 . Moreover, the distribution of bases peaks around h 1,1 ~ 82. All bases encountered after "thermalization" have some geometric non-Higgsable structure. We also find that the number of non-Higgsable gauge group factors grows roughly linearly in h 1,1 of the threefold base. Typical bases have ~ 6 isolated gauge factors as well as several larger connected clusters of gauge factors with jointly charged matter. Approximately 76% of the bases sampled contain connected two-factor gauge group products of the form SU(3) x SU(2), which may act as the non-Abelian part of the standard model gauge group. SU(3) x SU(2) is the third most common connected two-factor product group, following SU(2) x SU(2) and G2 x SU(2), which arise more frequently.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Nonlinear sigma models with compact hyperbolic target spaces

We explore the phase structure of nonlinear sigma models with target spaces corresponding to compact quotients of hyperbolic space, focusing on the case of a hyperbolic genus-2 Riemann surface. The continuum theory of these models can be approximated by a lattice spin system which we simulate using Monte Carlo methods. The target space possesses interesting geometric and topological properties which are reflected in novel features of the sigma model. In particular, we observe a topological phase transition at a critical temperature, above which vortices proliferate, reminiscent of the Kosterlitz-Thouless phase transition in the O(2) model [1, 2]. Unlike in the O(2) case, there are many different types of vortices, suggesting a possible analogy to the Hagedorn treatment of statistical mechanics of a proliferating number of hadron species. Below the critical temperature the spins cluster around six special points in the target space known as Weierstrass points. In conclusion, the diversity of compact hyperbolic manifolds suggests that our model is only the simplest example of a broad class of statistical mechanical models whose main features can be understood essentially in geometric terms.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Non-global logarithms, factorization, and the soft substructure of jets

An outstanding problem in QCD and jet physics is the factorization and resummation of logarithms that arise due to phase space constraints, so-called non-global logarithms (NGLs). In this paper, we show that NGLs can be factorized and resummed down to an unresolved infrared scale by making sufficiently many measurements on a jet or other restricted phase space region. Resummation is accomplished by renormalization group evolution of the objects in the factorization theorem and anomalous dimensions can be calculated to any perturbative accuracy and with any number of colors. To connect with the NGLs of more inclusive measurements, we present a novel perturbative expansion which is controlled by the volume of the allowed phase space for unresolved emissions. Arbitrary accuracy can be obtained by making more and more measurements so to resolve lower and lower scales. We find that even a minimal number of measurements produces agreement with Monte Carlo methods for leading-logarithmic resummation of NGLs at the sub-percent level over the full dynamical range relevant for the Large Hadron Collider. Here, we also discuss other applications of our factorization theorem to soft jet dynamics and how to extend to higher-order accuracy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

First-principles-based kinetic Monte Carlo studies of diffusion of hydrogen in Ni–Al and Ni–Fe binary alloys

The diffusion of dilute hydrogen in fcc Ni–Al and Ni–Fe binary alloys was examined using kinetic Monte Carlo method with input kinetic parameters obtained from first-principles density functional theory. The simulation involves the implementation of computationally efficient energy barrier model that describes the configuration dependence of the hydrogen hopping. The predicted hydrogen diffusion coefficients in Ni and Ni 89.4 Fe 10.6 are compared well with the available experimental data. In Ni–Al, the model predicts lower hydrogen diffusivity compared to that in Ni. Overall, diffusion prefactors and the effective activation energies of H in Ni–Fe and Ni–Al are concentration dependent of the alloying element. Furthermore, the changes in their values are the results of the short-range order (nearest-neighbor) effect on the interstitial diffusion of hydrogen in fcc Ni-based alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Temperature-Dependent Configurational Entropy Calculations for Refractory High-Entropy Alloys

The cluster expansion formalism for alloys is used to construct surrogate models for three refractory high-entropy alloys (NbTiVZr, HfNbTaTiZr, and AlHfNbTaTiZr). These cluster expansion models are then used along with Monte Carlo methods and thermodynamic integration to calculate the configurational entropy of these refractory high-entropy alloys as a function of temperature. Many solid solution alloy design guidelines are based on the ideal entropy of mixing, which increases monotonically with N , the number of elements in the alloy. However, our results show that at low temperatures, the configurational entropy of these materials is largely independent of N , and the assumption described above only holds in the high-temperature limit. This suggests that alloy design guidelines based on the ideal entropy of mixing require further examination.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Improving the real-time probabilistic channel flood forecasting by incorporating the uncertainty of inflow using the particle filter

An accurate and reliable real-time flood forecast is crucial for mitigating flood disasters. The errors associated with the inflow boundary forcing data are considered as an important source of uncertainties in hydraulic model. In this paper, a real-time probabilistic channel flood forecasting model is developed with a novel function to incorporate the uncertainty of the forcing inflow. This new approach couples a hydraulic model with the particle filter (PF) data assimilation algorithm, a sequential Bayesian Monte Carlo method. The stage observations at hydrological stations are assimilated at each time step to update the model states in order to improve the next time step’s forecasting. This new approach is tested against a real flood event occurred in the upper Yangtze River. As compared with the open loop simulations, the evaluations of model performance with several deterministic and probabilistic metrics indicate that the accuracy of the ensemble mean prediction and the reliability of the uncertainty quantification are improved pronouncedly as a result of the PF assimilation. Further assessment of the prediction results at different lead times shows that the improvement of model performance deteriorates with the increase of the lead time due to the gradual diminishing of the updating effect for the initial conditions. Based on the analyses of the number of particles and the assimilation frequency, we find that the optimal number of particles can be determined by balancing the model performance and the computation cost, while a high assimilation frequency is preferred to incorporate the emerging observations to update the model states to match the real conditions.

Channel flood forecasting, probabilistic forecast,↗
DOE OSTI2026

High temperature stabilization of ultrafine grain tungsten alloys through synergistic compositional complexities

Thermally-stabilized fine-grained microstructures in tungsten provide a pathway to harnessing enhanced properties such as a reduced ductile-to-brittle transition temperature and improved strength while mitigating the adverse effects of grain growth and recrystallization. Here, in this study, we employ a material design strategy that relies on grain boundary segregation in the nanocrystalline state driven by alloy thermodynamics balanced with impurity scavenging through in situ formation of kinetically-stabilizing metal carbides. A W-Ti-Cr alloy is designed through lattice Monte Carlo methods and subsequently synthesized in a single-phase nanocrystalline state, which upon annealing, evolves into an ultrafine grained microstructure containing chromium grain boundary segregation collectively with a dispersed TiX (X=C,O) phase through the reaction of titanium with carbon and oxygen impurities. In situ synchrotron X-ray diffraction experiments demonstrate that increased Ti promotes stabilization across a larger temperature range but with diminishing returns above 10 at.% Ti. Long-term stability was confirmed through the retention of the ultrafine grained microstructure for a total of 8 days (192 h) at 1300 °C without grain/carbide growth and/or recrystallization. Our results demonstrate that, through strategic tailoring of composition and microstructure, one can harness the benefits of both thermodynamic and kinetic stabilization mechanisms, opening pathways for future alloy formulations that expand the window of stability.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Molten salt reactor core simulation with PROTEUS

The Nuclear Energy Advance Modeling and Simulation Program (NEAMS) of the US Department of Energy (DOE) aims to develop advanced simulation tools to aid the development of advanced nuclear technologies. The high-fidelity PROTEUS code was developed in the NEAMS program for reactor physics analysis. This paper tests the applicability of the PROTEUS code to simulate a Molten Salt Reactor (MSR). The OpenMC code based on the Monte Carlo Method was employed to generate the cross sections and to provide stochastic solutions for verification. The PROTEUS code was successfully employed to simulate the steady-state performance of an MSR represented by the ThorCon core design. The 2D lattice, 2D core, and 3D full core calculations performed by PROTEUS show good agreement with that predicted by OpenMC. Furthermore, for the nodal option within PROTEUS, the precursor drift model was also tested, and this effect resulted in a reduction of the k-eff by 300 pcm.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

SCALE capabilities for high temperature gas-cooled reactor analysis

The SCALE code system’s ability to address stochastic distributions of fuel particles within a graphite matrix has been revisited in both multigroup (MG) features and continuous-energy (CE) Monte Carlo methods. Furthermore, this paper describes current and emergent SCALE capabilities within the CSAS sequence to address double-heterogeneous systems and presents verification and validation studies of these methods and data. Good agreement was obtained for a high temperature gas-cooled reactor (HTGR) fuel pebble model between CSAS MG eigenvalue calculations and corresponding CE reference solutions. Code-to-code comparisons for this HTGR pebble model showed good agreement of CSAS-KENO and CSAS-Shift CE calculations and the Serpent and MCNP codes in terms of eigenvalues and reaction rate ratios. Validation studies based on two HTGR experiments resulted in good agreement between MG and CE results, as well as between experiment and calculation, although the level of agreement was significantly influenced by the applied ENDF/B nuclear data library.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Catalytic resonance theory for the kinetics of photon-promoted catalysis

The illumination of catalytic surfaces with a continuous or pulsed stream of photons dynamically modulates surface chemistry for faster rates, non-equilibrium conversion, or product selectivity control. To establish fundamental principles of dynamic photon-modulated catalysis, the photocatalytic conversion of a generic surface reaction was simulated using the kinetic Monte Carlo method to understand the kinetic implications of an independent stream of photons that promotes surface product desorption. The time-averaged photocatalytic rate at differential conditions for varying photon flux and temperatures indicated three kinetic regimes described by product thermal desorption control, surface reaction control, and an intermediate kinetic regime with a zero slope Arrhenius plot, consistent with a degree of rate control dominated by the photon arrival frequency (i.e., per-site photon flux). Here, the maximum photocatalytic rate occurred orders of magnitude above the Sabatier limit at the resonance frequency, identified as the photon arrival frequency matching the surface reaction rate constant.

Canavan, Jesse R. [University of Minnesota, Minnea↗
DOE OSTI2017

Topology optimization under uncertainty via non-intrusive polynomial chaos expansion

This paper presents a systematic approach for topology optimization under uncertainty that integrates non-intrusive polynomial chaos expansion with design sensitivity analysis for reliability-based and robust topology optimization. Uncertainty is introduced in loading and in geometry to address the manufacturing variability. The manufacturing variability is modeled via a thresholding technique in which the threshold field is represented by a reduced dimensional random field. Response metrics such as compliance and volume are characterized as polynomial chaos expansions of the underlying uncertain parameters thus allowing accurate and efficient estimation of statistical moments, failure probabilities and their sensitivities. The number of simulations is reduced for linear structures under loading uncertainty by means of superposition. Efficiency of the non-intrusive polynomial chaos approach is highlighted by comparison with the Monte Carlo method in terms of the number of simulations. To demonstrate the effect of uncertainty, optimized designs that consider uncertainty are compared to those that do not. Finally, comparisons of polynomial chaos expansion to existing analytical methods on a benchmark numerical example are also provided for reliability-based and worst case designs.

42 ENGINEERING↗
DOE OSTI2016

Multi-objective optimization techniques to design the Pareto front of organic dielectric polymers

Here, we present two Monte Carlo algorithms to find the Pareto front of the chemical space of a class of dielectric polymers that is most interesting with respect to optimizing both the bandgap and dielectric constant. Starting with a dataset generated from density functional theory calculations, we used machine learning to construct surrogate models for the bandgaps and dielectric constants of all physically meaningful 4-block polymers (that is, polymer systems with a 4-block repeat unit). We parameterized these machine learning models in such a way that the surrogates built for the 4-block polymers were readily extendable to polymers beyond a 4-block repeat unit. By using translational invariance, chemical intuition, and domain knowledge, we were able to enumerate all possible 4, 6, and 8 block polymers and benchmark our Monte Carlo sampling of the chemical space against the exact enumeration of the surrogate predictions. We obtained exact agreement for the fronts of 4-block polymers and at least a 90% agreement for those of 6 and 8-block polymers. We present fronts for 10-block polymer that are not possible to obtain by direct enumeration. We note that our Monte Carlo methods also return polymers close to the predicted front and a measure of the closeness. Both quantities are useful information for the design and discovery of new polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Neural network model of neutral beam injection in the EAST tokamak to enable fast transport simulations

The neutral beam injection (NBI) system in EAST produces energetic neutral particles, which collide with electrons and ions in tokamak plasmas and heat the plasmas through Coulomb collisions. Moreover, it drives a non-inductive source of current, due to the charge-exchange collision between neutral particles and ions, and injects toroidal torque, which generates a toroidal rotation of the plasma. The effect caused by the NBI system, such as plasma heating, current drive, total neutron rate, momentum transfer, and shine-through, are modeled by a comprehensive module called NUBEAM. However, NUBEAM is computationally intensive since it relies on Monte Carlo methods. In this work, a neural network model has been developed as a surrogate model for NUBEAM in EAST. The database for neural-network model training, validation and testing is generated by running TRANSP for experimental discharges from recent EAST campaigns (after the latest NBI upgrade) while using the NUBEAM module. Simulation results illustrate that the trained neural network has the capability of replicating the predictions made by NUBEAM while demanding a significantly shorter execution time. Finally, these results indicate that surrogate models like the one proposed in this work could enable fast transport simulations for EAST after integrating them into a control-oriented predictive code such as COTSIM.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

First operation and validation of simulations for the divertor cryo-vacuum pump in Wendelstein 7-X

Ten cryo-vacuum pumps (CVPs) were installed in the subdivertor region of each island divertor in the stellarator Wendelstein 7-X (W7-X) and operated for the first time during the recently completed plasma campaign OP2.1. A pumping speed of 70 ± 1 $\frac{m^3}{s}$ was measured during dedicated tests with known hydrogen gas injection. Based on a conductance model, the estimated pumping speed ranges from 86-93 $\frac{m^3}{s}$ for different sticking coefficients between 0.6 and 0.8. After completion of the initial tests the CVPs were operated successfully throughout the campaign, with regeneration performed once a week. Neutral gas pressures in the subdivertor in the range of 10 −4 mbar are well within the molecular flow regime and limit the particle exhaust capabilities of the CVPs. Simulations of the neutral gas pressure in the three-dimensional complex geometry of the subdivertor were performed using the DIVGAS code based on the direct simulation Monte Carlo method and a model implemented in the steady-state thermal package in ANSYS, which are in agreement with the measured values during plasma operation.

Cryo-vacuum pumping↗
DOE OSTI2017

Equilibrium clumped-isotope effects in doubly substituted isotopologues of ethane

We combine path-integral Monte Carlo methods with a new intramolecular potential energy surface to quantify the equilibrium enrichment of doubly substituted ethane isotopologues due to clumped-isotope effects. Ethane represents the simplest molecule to simultaneously exhibit 13C–13C, 13C–D, and D–D clumped-isotope effects, and the analysis of corresponding signatures may provide useful geochemical and biogeochemical proxies of formation temperatures or reaction pathways. Utilizing path-integral statistical mechanics, we predict equilibrium fractionation factors that fully incorporate nuclear quantum effects, such as anharmonicity and rotational-vibrational coupling which are typically neglected by the widely used Urey model. The magnitude of the calculated fractionation factors for the doubly substituted ethane isotopologues indicates that isotopic clumping can be observed if rare-isotope substitutions are separated by up to three chemical bonds, but the diminishing strength of these effects suggests that enrichment at further separations will be negligible. The Urey model systematically underestimates enrichment due to 13C–D and D–D clumped-isotope effects in ethane, leading to small relative errors in the apparent equilibrium temperature, ranging from 5 K at 273.15 K to 30 K at 873.15 K. We additionally note that the rotameric dependence of isotopologue enrichment must be carefully considered when using the Urey model, whereas the path-integral calculations automatically account for such effects due to configurational sampling. These findings are of direct relevance to future clumped-isotope studies of ethane, as well as studies of 13C–13C, 13C–D, and D–D clumped-isotope effects in other hydrocarbons.

Geochemistry & Geophysics↗