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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 37 records · Page 2

DMFTwDFT: An open-source code combining Dynamical Mean Field Theory with various density functional theory packages

We report Dynamical Mean Field Theory (DMFT) is a successful method to compute the electronic structure of strongly correlated materials, especially when it is combined with density functional theory (DFT). Here, we present an open-source computational package (and a library) combining DMFT with various DFT codes interfaced through the Wannier90 package. The correlated subspace is expanded as a linear combination of Wannier functions introduced in the DMFT approach as local orbitals. In particular, we provide a library mode for computing the DMFT density matrix. This library can be linked and then internally called from any DFT package, assuming that a set of localized orbitals can be generated in the correlated subspace. The existence of this library allows developers of other DFT codes to interface with our package and achieve the charge-self-consistency within DFT+DMFT loops. To test and check our implementation, we computed the density of states and the band structure of well-known solid-state correlated materials, namely LaNiO, SrVO, and NiO. The obtained results are compared to those obtained from other DFT+DMFT implementations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

I Know I'm Right, But Does My Phone?

Transportation is the largest source of green-house gas emissions in the United States. Reducing transportation emissions depends on human travel behavior, which relies on local land use and planning. Travel diaries, consisting of sequences of trips between places for a particular individual, are typically used to instrument human travel behavior. However, these diaries are only as accurate as the underlying methods used to construct them. Travel diary algorithms have been a popular research topic since the advent of GPS tracking surveys. Mode inference algorithms in particular have been well represented in literature. However, these algorithms have typically been validated using prompted recall of pre-segmented trips, which doesn't account for segmentation error, thus disregarding the continuity of mode inference. Furthermore, phone operating systems and applications have adopted battery-conserving techniques, but we are not aware of prior work that has characterized the resulting data collection errors or evaluated procedures to mitigate them. We introduce a framework to evaluate accuracy of trip length computations and mode inference. We develop a temporal alignment procedure in analyzing continuous mode-segmented trajectories for groups of trips. We then apply our framework to evaluate an example set of travel diary algorithms from the open-source OpenPATH travel diary platform against MobilityNet, a public dataset containing information from three artificial timelines that cover 15 different travel modes. Our results show that inference based on an integration with map features results in weighted F_1 scores of 0.60 (iOS) and 0.74 (android). We also show that OpenPATH tends to under count trip length, with mean of signed relative error of -0.0438 on android and -0.0704 on iOS. We hope that other travel diary algorithms will be evaluated using this standardized process, and that the results used to understand and improve the state-of-the-art in this field.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Validation study of RWM stability in DIII-D high- β N plasmas

The n = 1 (n is the toroidal mode number) resistive wall mode (RWM) stability is numerically investigated for two DIII-D high-β N discharges 176440 and 172461, utilizing the MARS-F (Liu et al 2000 Phys. Plasmas 7 3681) and MARS-K (Liu et al 2008 Phys. Plasmas 15 112503) codes. Systematic validation efforts are attempted, for the first time, for discharges with very slow or vanishing toroidal flow for a large fraction of the plasma volume. While gaining physics insights in accessing stable operation regime at β N exceeding the Troyon no-wall limit in these slow-rotation experiments, the predictive capability of fluid and non-perturbative magnetohydrodynamic-kinetic hybrid models for the RWM is further confirmed. The MARS-F fluid model, with a strong but numerically tunable viscosity mimicking ion Landau damping of parallel sound waves, finds complete stabilization of the n = 1 RWM in the considered DIII-D plasmas under the experimental flow conditions. Similarly, either full stabilization (for discharge 176440) or marginal stability (for discharge 172461) of the mode is computed by the MARS-K hybrid model, which is first-principle based without free model parameters. In particular, all drift kinetic resonances, including those of thermal and energetic particles, are found to synergistically act to marginally stabilize the RWM in discharge 172461. These MARS-F/K modeling results explain the experimentally observed stable operational regime in DIII-D, as far as the RWM stability is concerned. Extensive numerical sensitivity studies, with respect to the plasma toroidal flow speed as well as the radial location of the resistive wall, are also carried out to further support the validation study.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A generalized Selberg zeta function for flat space cosmologies

Flat space cosmologies (FSCs) are time dependent solutions of three-dimensional (3D) gravity with a vanishing cosmological constant. They can be constructed from a discrete quotient of empty 3D flat spacetime and are also called shifted-boost orbifolds. Using this quotient structure, we build a new and generalized Selberg zeta function for FSCs, and show that it is directly related to the scalar 1-loop partition function. We then propose an extension of this formalism applicable to more general quotient manifolds $\mathcal{M}$/ℤ, based on representation theory of fields propagating on this background. Our prescription constitutes a novel and expedient method for calculating regularized 1-loop determinants, without resorting to the heat kernel. We compute quasinormal modes in the FSC using the zeroes of a Selberg zeta function, and match them to known results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Elastic strain engineering of lattice thermal conductivity of silicon: An ab-initio study

Silicon (Si) is the most essential material in the semiconductor industry. It is important to manage the thermal properties of crystalline Si. Elastic strain engineering (ESE) has proven to be an effective tool in controlling the electrical conductivity of Si in strained-silicon technology; its effects on the thermal conductivity of silicon, therefore, warrants careful investigation. The ESE effect is much more pronounced for nanostructured materials due to the ultralarge elastic strains (on the order of 10%) achievable at the nanoscale. In this work, the lattice thermal conductivity (κ L ) of Si under hydrostatic, biaxial, and uniaxial strain states is studied with ab-initio simulations, and the values of strain-dependent κ L compare well with experimental results and existing molecular dynamics simulations. To understand the mechanisms of strain-modulated κ L , the phonon bands, scattering rate, and Grüneisen parameters of phonon modes are computed. It is shown that strain can significantly change the anharmonicity of the crystal system, thus changing phonon scattering rates and κ L . Our results demonstrate that ESE can reduce silicon κ L by up to approximately 90%. Furthermore, uniaxial and biaxial strains can induce highly anisotropic thermal conductivity in Si, with relative variations up to 58.5% and 14.5%, respectively.

Anisotropy in Thermal Conductivity↗

Pressure Effects on the Relaxation of an Excited Ethane Molecule in High-Pressure Bath Gases

Here, we use molecular dynamics to calculate the rotational and vibrational energy relaxation of C 2 H 6 in Ar, Kr, and Xe bath gases over a pressure range of 10 to 400 atm and at temperatures of 300 K and 800 K. The C 2 H 6 is instantaneously excited by 80 kcal/mol randomly distributed into both vibrational and rotational modes. The computed relaxation rates show little sensitivity to the identity of the noble gas in the bath. Vibrational relaxation rates show a non-linear pressure dependence at 300 K. At 800 K the reduced range of bath gas densities covered by the range of pressures do not yet show any non-linearity in the pressure dependence. Rotational relaxation is characterized with two relaxation rates. The slower rate is comparable to the vibrational relaxation rate. The faster rate has a linear pressure dependence at 300 K but an irregular, nonlinear pressure dependence at 800 K. To understand this, a model was developed based on approximating the periodic box used in the molecular dynamics simulations by an equal-volume collection of cubes where each cube is sized to allow only single occupancy by the noble gas or the molecule. Combinatorial statistics then leads to a pressure and temperature dependent analytic distribution of the bath gas species the molecule encounters in a collision. This distribution, the dissociation energy of molecule/bath gas complexes and bath gas clusters, and the computed energy release per collision combine to show that only at 300 K is the energy release sufficient to dissociate likely complexes and clusters. This suggests that persistent and pressure-dependent clusters and complexes at 800 K may be responsible for the non-linear pressure dependence of rotational relaxation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advancing density functional tight-binding method for large organic molecules through equivariant neural networks

Semi-empirical quantum-mechanical (QM) methods have become valuable tools for studying complex (bio)molecular systems due to their balance between computational efficiency and accuracy. A key aspect of these methods is their parameterization, which not only governs the reliability of the results but also provides an opportunity to enhance their overall performance. In our previous work [J. Phys. Chem. Lett., 2021, 11, 16], we advanced the third-order semi-empirical density functional tight-binding (DFTB3) method for computing multiple properties of small molecules by developing the machine learning (ML) potential NN rep to bridge the gap between DFTB3 electronic components and those of the hybrid DFT-PBE0 functional. To overcome the limitations of NN rep , we introduce the EquiDTB framework, which leverages physics-inspired equivariant neural networks (NN) to parameterize scalable and transferable many-body Δ TB potentials, replacing the standard pairwise DFTB repulsive potential. This advancement extends the applicability of our ML-corrected DFTB approach to larger molecules and non-covalent systems (including only C, N, O, and H atoms), going beyond the chemical space represented in the training QM datasets. The enhanced performance of EquiDTB over the standard TB methods is demonstrated by the accurate computation of the atomic forces of S66x8 molecular dimers, as well as their interaction energies. Moreover, EquiDTB can be effectively employed to explore the potential energy surfaces of large and flexible drug-like molecules—for example, to determine the minimum energy path between isomers, analyze structural transitions during dynamical simulations, compute vibrational modes, and investigate energetic rankings. The performance for single molecules slightly decreases when the DFTB electronic energy is reduced to first-order but remains superior to standard TB methods. Our work thus demonstrates that an optimal integration of an equivariant NN with QM datasets can advance the DFTB method while maintaining high efficiency, paving the way for reliable (bio)molecular simulations.

Medrano Sandonas, Leonardo [Technische Universität↗

Thermal transport in defective and disordered materials

With significant recent advancements in thermal sciences—such as the development of new theoretical and experimental techniques, and the discovery of new transport mechanisms—it is helpful to revisit the fundamentals of vibrational heat conduction to formulate an updated and informed physical understanding. The increasing maturity of simulation and modeling methods sparks the desire to leverage these techniques to rapidly improve and develop technology through digital engineering and multi-scale, electro-thermal models. With that vision in mind, this review attempts to build a holistic understanding of thermal transport by focusing on the often unaddressed relationships between subfields, which can be critical for multi-scale modeling approaches. For example, we outline the relationship between mode-specific (computational) and spectral (analytical) models. We relate thermal boundary resistance models based on perturbation approaches and classic transmissivity based models. We discuss the relationship between lattice dynamics and molecular dynamics approaches along with two-channel transport frameworks that have emerged recently and that connect crystal-like and amorphous-like heat conduction. Throughout, we discuss best practices for modeling experimental data and outline how these models can guide material-level and system-level design.

42 ENGINEERING↗

Fourier Analyses of High-Order Continuous and Discontinuous Galerkin Methods

In this paper, we present a Fourier analysis of wave propagation problems subject to a class of continuous and discontinuous discretizations using high-degree Lagrange polynomials. This allows us to obtain explicit analytical formulas for the dispersion relation and group velocity and, for the first time to our knowledge, characterize analytically the emergence of gaps in the dispersion relation at specific wavenumbers, when they exist, and compute their specific locations. Wave packets with energy at these wavenumbers will fail to propagate correctly, leading to significant numerical dispersion. We also show that the Fourier analysis generates mathematical artifacts, and we explain how to remove them through a branch selection procedure conducted by analysis of eigenvectors and associated reconstructed solutions. The higher frequency eigenmodes, named erratic in this study, are also investigated analytically and numerically.

97 MATHEMATICS AND COMPUTING↗

Exploration of superconducting multi-mode cavity architectures for quantum computing

Superconducting radio-frequency (SRF) cavities coupled to transmon circuits have proven to be a promising platform for building high-coherence quantum information processors. An essential aspect of this realization involves designing high quality factor three-dimensional superconducting cavities to extend the lifetime of quantum systems. To increase the computational capability of this architecture, we are exploring a multimode approach. This paper presents the design optimization process of a multi-cell SRF cavity to perform quantum computation based on an existing design developed in the scope of particle accelerator technology. We perform parametric electromagnetic simulations to evaluate and optimize the design. In particular, we focus on the analysis of the interaction between a nonlinear superconducting circuit known as the transmon and the cavity. This parametric design optimization is structured to serve as a blueprint for future studies on similar systems.

Reineri, Alessandro↗

Serpent transient analyses of GIACINT geometrical change experiments

This paper simulates seven transient experiments with geometrical movements performed at the GIACINT facility of Belarus. These experiments include three slow control rods insertion in more than 25 s, one fast control rod insertion in less than 1 s, and three water moderator draining transients. In the fast control rod insertion experiment, the control rods are first pushed by a mechanical spring and then let fall by gravity in the assembly. In this experiment, the control rods speed varies because of the initial spring force, the gravitational acceleration, and the water buoyancy force. In all other transient experiments, the geometry change occurs with a constant speed. The Serpent computer program was utilized to simulate these transient experiments with geometrical changes by performing two separate computations. One time-independent computation is performed in criticality mode and the other time-dependent computation is performed in dynamic-source mode. The first computation writes the neutron population and delayed neutron precursors for starting the transient simulation. The second computation divides the transient time into several time bins, reads the two files from the first computation, and updates them at the end of each time bin. The Serpent simulation results obtained for this set of experiments are in good agreement with the time dependent experimental measurements. In addition, Serpent and MCNP simulations results show an excellent agreement for the water moderator transient

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Computational determination of a primary diffusion mode in γ U-10Mo under irradiation

Low enriched uranium (< 20 % 235 U)-molybdenum (U-Mo) monolithic fuel is the primary candidate for high performance research and test reactors, and is in the process of being qualified to replace highly enriched uranium (≥ 20 % 23 5U) fuel. As part of the qualification process, it is critical to understand and predict the behavior of fission gas bubbles under irradiation, which affects fuel swelling and fuel failure. Mechanistic fuel models are being developed that can both reproduce the existing experimental data for fuel swelling, and be further applied to irradiation conditions beyond the experimental scope. Diffusion of species under irradiation conditions is an important parameter in the mechanistic fuel models; however, no temperature-relevant experimental diffusion data exists. In the present work, radiation-enhanced diffusion coefficients of U, Mo, and Xe in λU-10wt.%Mo were calculated in the temperature range between 300 K and 1400 K via rate-theory models and molecular dynamics simulations with an embedded-atom method interatomic potential for the U-Mo-Xe system. Accordingly, total diffusion coefficients under relevant irradiation conditions are determined using previously obtained intrinsic thermal diffusion and radiation-driven diffusion coefficients, as well as the newly calculated radiation-enhanced diffusion coefficients presented herein. Radiation-enhanced diffusion of U and Mo was dominant in the intermediate temperature range, whereas radiation-enhanced diffusion of Xe did not significantly contribute to total diffusion of Xe at the relevant fission rate densities. Radiation-enhanced diffusion of Xe became faster than both intrinsic thermal diffusion and radiation-driven diffusion at a fission rate density of 5 x 10 22 fissions/m 3 /s, which is higher than the typical fission rate density range in research reactors. The temperature regime that radiation-enhanced diffusion of each element dominated was dependent on the fission rate density. Finally, the total diffusion coefficients of U, Mo, and Xe, updated in this work, will be utilized as parameters in the mechanistic fuel models to help predict the behavior of fission gas bubbles under irradiation more accurately.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Toroidal modeling of Alfvén eigenmodes excited by runaway electrons in DIII-D and ITER

The non-perturbative MHD-kinetic hybrid code MARS-K (Liu et al 2014 Phys. Plasmas 21 056105) is updated to include relativistic effects for kinetic fast particles, enabling the code to model excitation of Alfvén eigenmodes (AEs) by runaway electrons (REs) in post-disruption tokamak plasmas. Applying the updated code to RE beams in both DIII-D and ITER, a zoo of AE modes triggered by trapped REs due to precessional drift-kinetic resonances is computed while scanning the RE energy. At fixed RE energy, multiple unstable roots are also excited. These AE modes possess radially different eigenmode structures, ranging from global modes to core-localized ones. The computed mode frequency is in the Alfvén frequency range, increasing with the assumed RE energy in a staircase fashion and quantitatively matching the experimental measurement (in DIII-D). At the (more relevant) high-frequency range (above 1 MHz), the modeled eigenmodes are identified as compressional AEs (CAEs) in DIII-D and a mixture of CAE and shear Alfvén waves in ITER.

Alfvén eigenmodes↗

Quasinormal modes of charged fields in Reissner-Nordström backgrounds by Borel-Padé summation of Bender-Wu series

We extend recent work of Hatsuda on the computation of quasinormal mode frequencies via analytic continuation of bound state energies and Borel-Pade resummation of the Bender-Wu perturbation series to the case of charged fields in the background of Reissner-Nordstrom black holes. We compare the quasinormal mode frequencies obtained in this manner to calculations using Leaver's method of continued fractions, and find good agreement for damped modes (DMs) with imaginary part remaining finite in the extremal limit. Here, we also present numerical evidence that the frequencies of certain zero-damped modes (ZDMs) with imaginary part tending to zero in the extremal limit can be computed when constructing the Bender-Wu expansion about a peak of the potential inside the outer horizon of the black hole.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A comparison of surrogate constitutive models for viscoplastic creep simulation of HT-9 steel

Mechanistic microstructure-informed constitutive models for the mechanical response of polycrystals are a cornerstone of computational materials science. However, as these models become increasingly more complex – often involving coupled differential equations describing the effect of specific deformation modes – their associated computational costs can become prohibitive, particularly in optimization or uncertainty quantification tasks that require numerous model evaluations. To address this challenge, surrogate constitutive models that balance accuracy and computational efficiency are highly desirable. Data-driven surrogate models, that learn the constitutive relation directly from data, have emerged as a promising solution. In this work, we develop two local surrogate models for the viscoplastic response of a steel: a piecewise response surface method and a mixture of experts model. These surrogates are designed to adapt to complex material behavior, which may vary with material parameters or operating conditions. The surrogate constitutive models are applied to creep simulations of HT-9 steel, an alloy of considerable interest to the nuclear energy sector due to its high tolerance to radiation damage, using training data generated from viscoplastic self-consistent (VPSC) simulations. In conclusion, we define a set of test metrics to numerically assess the accuracy of our surrogate models for predicting viscoplastic material behavior, and show that the mixture of experts model outperforms the piecewise response surface method in terms of accuracy.

36 MATERIALS SCIENCE↗

Experimental Guesswork with Quantum Side Information Using Twisted Light

Guesswork is an information–theoretic quantity which can be seen as an alternate security criterion to entropy. Recent work has established the theoretical framework for guesswork in the presence of quantum side information, which we extend both theoretically and experimentally. We consider guesswork when the side information consists of the BB84 states and their higher-dimensional generalizations. With this side information, we compute the guesswork for two different scenarios for each dimension. We then performed a proof-of-principle experiment using Laguerre–Gauss modes to experimentally compute the guesswork for higher-dimensional generalizations of the BB84 states. We find that our experimental results agree closely with our theoretical predictions. This work shows that guesswork can be a viable security criterion in cryptographic tasks and is experimentally accessible in a number of optical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗