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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Li1−xNiO2 Many-body DMC Benchmark Dataset

The dataset contains all numerical data generated in support of the manuscript “Many‑body Benchmark of Electronic Charge and Spin Densities for Li1–xNiO2​” (Journal of Chemical Theory and Computation, DOI: 10.1021/acs.jctc.5c02097, URL: https://pubs.acs.org/doi/10.1021/acs.jctc.5c02097). The materials included in this repository are: 1. Data files used to produce all figures and tables in the main manuscript and supporting information. 2. Benchmark density‑functional theory (DFT) datasets used for the charge‑ and spin‑density analyses. 3. Reference many‑body diffusion Monte Carlo (DMC) calculations and associated input/output files.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Solving the nuclear pairing model with neural network quantum states

In this work, we present a variational Monte Carlo method that solves the nuclear many-body problem in the occupation number formalism exploiting an artificial neural network representation of the groundstate wave function. A memory-efficient version of the stochastic reconfiguration algorithm is developed to train the network by minimizing the expectation value of the Hamiltonian. We benchmark this approach against widely used nuclear many-body methods by solving a model used to describe pairing in nuclei for different types of interaction and different values of the interaction strength. Despite its polynomial computational cost, our method outperforms coupled-cluster and provides energies that are in excellent agreement with the numerically-exact full configuration interaction values.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Multi-fidelity microstructure-induced uncertainty quantification by advanced Monte Carlo methods

Quantifying uncertainty associated with the microstructure variation of a material can be a computationally daunting task, especially when dealing with advanced constitutive models and fine mesh resolutions in the crystal plasticity finite element method (CPFEM). Numerous studies have been conducted regarding the sensitivity of material properties and performance to the mesh resolution and choice of constitutive model. However, a unified approach that accounts for various fidelity parameters, such as mesh resolutions, integration time-steps and constitutive models simultaneously is currently lacking. Further, this paper proposes a novel uncertainty quantification (UQ) approach for computing the properties and performance of homogenized materials using CPFEM, that exploits a hierarchy of approximations with different levels of fidelity. In particular, we illustrate how multi-level sampling methods, such as multi-level Monte Carlo (MLMC) and multi-index Monte Carlo (MIMC), can be applied to assess the impact of variations in the microstructure of polycrystalline materials on the predictions of homogenized materials properties. We show that by adaptively exploiting the fidelity hierarchy, we can significantly reduce the number of microstructures required to reach a certain prescribed accuracy. Finally, we show how our approach can be extended to a multi-fidelity framework, where we allow the underlying constitutive model to be chosen from either a phenomenological plasticity model or a dislocation-density-based model.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Search for leptonic charge asymmetry in $t\overline{t}W$ production in final states with three leptons at $\sqrt{s}$ = 13 TeV

A search for the leptonic charge asymmetry (${A}_{c}^{\ell}$) of top-quark-antiquark pair production in association with a $W$ boson ($t\overline{t}W$) is presented. The search is performed using final states with exactly three charged light leptons (electrons or muons) and is based on $\sqrt{s}$= 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider at CERN during the years 2015–2018, corresponding to an integrated luminosity of 139 fb –1 . A profile-likelihood fit to the event yields in multiple regions corresponding to positive and negative differences between the pseudorapidities of the charged leptons from top-quark and top-antiquark decays is used to extract the charge asymmetry. At reconstruction level, the asymmetry is found to be –0.12 ± 0.14 (stat.) ± 0.05 (syst.). An unfolding procedure is applied to convert the result at reconstruction level into a charge-asymmetry value in a fiducial volume at particle level with the result of –0.11 ± 0.17 (stat.) ± 0.05 (syst.). The Standard Model expectations for these two observables are calculated using Monte Carlo simulations with next-to-leading-order plus parton shower precision in quantum chromodynamics and including next-to-leading-order electroweak corrections. They are ${–0.084}_{–0.003}^{+0.005}$ (scale) ± 0.006 (MC stat.) and ${–0.063}_{–0.004}^{+0.007}$ (scale) ± 0.004 (MC stat.) respectively, and in agreement with the measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Nematic order driven by superconducting correlations

The interplay of nematicity and superconductivity has been observed in a wide variety of quantum materials. To explore this interplay, we consider a two-dimensional (2D) array of nematogens, local droplets with Z 3 nematicity, coupled to a network of Josephson junction wires. Using finite temperature classical Monte Carlo simulations, we elucidate the phase diagram of this model and show that the development of superconducting correlations and the directional delocalization of Cooper pairs can promote nematogen ordering, resulting in long-range nematic order. We obtain the transport properties of our model within an effective resistor network picture. We discuss these ideas in the context of the 2D electron gas at the (111) KTaO 3 interface and the doped topological insulators Nb x Bi 2 Se 3 and Cu x Bi 2 Se 3 . Overall, our work makes contact with Phil Anderson’s numerous contributions to broken symmetries driven by the saving of kinetic energy, including double exchange ferromagnetism and the interlayer tunneling theory of high Tc csuperconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Pathway for decarbonizing residential building operations in the US and China beyond the mid-century

With global carbon budget targets looming, residential buildings in top economies must become carbon neutral as soon as possible to reserve more emission space for emerging carbon-emitting economies. This study is the first to compare the operational decarbonization process of China’s and the United States (US) residential buildings from 2000 to 2060 by combining the end-use emission model with the decomposing structural decomposition (DSD) method and Monte Carlo simulation. The results show that from 2001 to 2020 China decarbonized 1544 mega-tons of carbon dioxide (MtCO 2 ) and the US decarbonized 1848 MtCO 2 . In the business-as-usual scenario, China will hit its emission peak in 2031 (±3) with 934 (±61) MtCO 2 , while the US will maintain a lock-in level of 736 (±133) MtCO 2 since the 2030s. In the decarbonization scenario, operational carbon neutrality for residential buildings in 2060 is promoted by an increase in clean power generation proportion, building-integrated power generation level, building electrification level, and a reduction in end-use energy intensity, which will contribute 34.4 %, 21.4 %, 14.3 %, and 29.9 % in China and 32.9 %, 33.1 %, 8.2 %, and 25.8 % in the US, respectively. Especially, building-integrated power generation in China only costs about 40 % of what it costs in the US. Besides, high-decarbonization strategies for residential building operations are proposed as references for governments to formulate targeted climate policies. Overall, this study offers data benchmarks for buildings’ carbon neutrality of top economies to further promote synergistic carbon neutrality with the buildings of emerging economies in the age of Post COP27.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Feasibility of DEIM for retrieving the initial field via dimensionality reduction

When parameter estimation is solved in a high-dimensional space, the dimensionality reduction strategy becomes the primary consideration for alleviating the tremendous computational cost. Here, the discrete empirical interpolation method (DEIM) is explored to retrieve the initial condition (IC) by combining the polynomial chaos (PC) based ensemble Kalman filter (i.e. PC-EnKF), where a non-intrusive PC expansion is considered as a surrogate model in place of the forward model in the prediction step of the ensemble Kalman filter, resulting in fewer forward model integrations but with a comparable accuracy as Monte Carlo-based approaches. The DEIM acts as a hyper-reduction tool to provide the low-dimensional input for the high-dimensional initial field, which can be reconstructed using the information on the sparse interpolation grid points that is adaptively obtained through PC-EnKF data assimilation method. Thus an innovative framework to reconstruct the IC is developed. The detailed procedure at each assimilation iteration includes: the determination of the spatial interpolation points, the estimation of the initial values on the interpolation locations using the optimal observations, and the reconstruction of IC in the full space. The current study uses the reconstruction field of initial conditions of the Navier-Stokes equations as an example to illustrate the efficacy of our method. The experimental results demonstrate the proposed algorithm achieves a satisfactory reconstruction for the initial field. The proposed method helps to extend the applicable area of DEIM in solving inverse problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Initial validation of ALFRED: A Monte Carlo code built on Geant4 for TREAT energy deposition

Predicting the energy deposited in the specimen during an experiment in the Transient Reactor Test (TREAT) Facility is a complex problem due to the nature of the transients occurring in the reactor. In addition, the many particles contributing to energy deposition have different behavior in time and space. ALFRED, a new Geant4 based code, is developed to transport and simulate each particle generated in the core. This code is verified against OpenMC (Open Monte Carlo) on the Godiva benchmark and a simple TREAT model. Next, the energy deposition in TREAT is calculated: 181.05 ± 0.01 MeV for the “instantaneous” energy deposition (which accounts for the energy deposited within 1 s after neutron emission) in fuel and 189.90 ± 0.01 MeV for the total energy deposition in fuel. We discuss these results in this paper with previous calculations and experimental evaluations. This work demonstrates ALFRED’s potential as a high-fidelity tool for computing the spatial and temporal energy deposition in TREAT paving the way for a better understanding of the energy coupling factors in TREAT.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

A Comprehensive Monte Carlo Framework for Jet-Quenching

This article presents the motivation for developing a comprehensive modeling framework in which different models and parameter inputs can be compared and evaluated for a large range of jet-quenching observables measured in relativistic heavy-ion collisions at RHIC and the LHC. Here, the concept of a framework is discussed within the context of recent efforts by the JET Collaboration, the authors of JEWEL, and the JETSCAPE collaborations. The framework ingredients for each of these approaches is presented with a sample of important results from each. The role of advanced statistical tools in comparing models to data is also discussed, along with the need for a more detailed accounting of correlated errors in experimental results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Revealing Intermetallic Active Sites of PtNi Nanocatalysts for Reverse Water Gas Shift Reaction

Bimetallic nanoparticles have gained great interest due to their potential applications in catalysis. By combining Lattice Boltzmann Modeling (LBM), Density Functional Theory (DFT) calculations, and kinetic Monte Carlo (KMC) simulation, here we rationalize the superior performance of supported Pt-Ni alloy nanostructures over Pt and Ni alone during the reverse Water Gas Shift (rWGS) reaction, which was observed previously. The LBM simulation including the diffusion and flow of the reacting gas molecules within the supporting nanoporous channels in SBA-15 indicates that the simple combination of contributions from Ni and Pt alone is not enough to result in the observed promotion in rWGS activity and selectivity of the Pt-Ni alloy. Instead, the synergy between Pt and Ni via a unique intermetallic motif is responsible according to the DFT and KMC simulation. In conclusion, compared to the monometallic counterparts, the intermetallic-introduced ensemble effect at the low-coordinated Pt-Ni hybrid site of Pt-Ni alloy nanocatalysts enables the enhanced activation of CO 2 and promoted removal of CO/H 2 O as gas phase product.

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

Local Chemical Clustering Enabled Ultrahigh Capacitive Energy Storage in Pb-Free Relaxors

Designing Pb-free relaxors with both a high capacitive energy density (W rec ) and high storage efficiency (η) remains a remarkable challenge for cutting-edge pulsed power technologies. Local compositional heterogeneity is crucial for achieving complex polar structure in solid solution relaxors, but its role in optimizing energy storage properties is often overlooked. Here, in this paper, we report that an exceptionally high W rec of 15.2 J cm –3 along with an ultrahigh η of 91% can be achieved through designing local chemical clustering in Bi 0.5 Na 0.5 TiO 3 –BaTiO 3 -based relaxors. A three-dimensional atomistic model derived from neutron/X-ray total scattering combined with reverse Monte Carlo method reveals the presence of subnanometer scale clustering of Bi, Na, and Ba, which host differentiated polar displacements, and confirming the prediction by density functional theory calculations. This leads to a polar state with small polar clusters and strong length and direction fluctuations in unit-cell polar vectors, thus manifesting improved high-field polarizability, steadily reduced hysteresis, and high breakdown strength macroscopically. The favorable polar structure features also result in a unique field-increased η, excellent stability, and superior discharge capacity. Our work demonstrates that the hidden local chemical order exerts a significant impact on the polarization characteristic of relaxors, and can be exploited for accessing superior energy storage performance.

25 ENERGY STORAGE↗
DOE OSTI2023

A hybrid Monte Carlo study of bond-stretching electron–phonon interactions and charge order in BaBiO3

Abstract The relationship between electron–phonon ( e -ph) interactions and charge-density-wave (CDW) order in the bismuthate family of high-temperature superconductors remains unresolved. We address this question using nonperturbative hybrid Monte Carlo calculations for the parent compound BaBiO 3 . Our model includes the Bi 6 s and O 2 p σ orbitals and coupling to the Bi-O bond-stretching branch of optical phonons via modulations of the Bi-O hopping integral. We simulate three-dimensional clusters of up to 4000 orbitals, with input model parameters taken from ab initio electronic structure calculations and a phonon energy ℏΩ 0 = 60 meV. Our results demonstrate that the coupling to the bond-stretching modes is sufficient to reproduce the CDW transition in this system, despite a relatively small dimensionless coupling. We also find that the transition deviates from the weak-coupling Peierls’ picture. This work demonstrates that off-diagonal e -ph interactions in orbital space are vital in establishing the bismuthate phase diagram.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Bioproducts from high-protein algal biomass: An economic and environmental sustainability review and risk analysis

This report has High-protein algal biomass as an important bio-commodity that has the potential to provide a new source of sustainable protein products. Herein is a critical review that identifies 1) the most relevant sustainability findings related to the processing of proteinaceous algal biomass to higher value protein products and 2) the potential pathways to improve life cycle assessment (LCA) and techno-economic analysis (TEA) metrics, including life-cycle carbon dioxide equivalent (CO 2 eq), life cycle energy, and minimum selling price (MSP) of these products. The critical review of the literature revealed a large variation in model input parameters relating to these metrics. Therefore, a Monte Carlo analysis was conducted to assess the risk associated with these input variations. To understand the uncertainties that propagate into high-protein algae to products’ systems, we reviewed more than 20 state-of-the-art unit operations for algal biomass processing., including cell disruption, protein solubilization, protein precipitation and purification, and protein concentration. We evaluated displacement of proteinaceous products by algal-bioproducts, including ruminant feed, aquaculture feed, protein tablets, and biopolymers and biopolyesters, with prices in the market ranging from 1.9 to 120 $\$$ kg -1 protein. This review realized that the MSP of ruminant and non-ruminant feed ranges from 0.65±0.56 to 2.9±1.1 $\$$ kg -1 protein, and bioplastics’ MSP ranges from 0.97 to 7.0 $\$$ kg -1 protein. Regarding LCA metrics, there is limited research on life cycle energy in proteinaceous biomass concentration and bioproduct systems, reported at 32.7 MJ kg protein -1 , for animal feed displacement. Animal feed emissions in the literature report negative fluxes, representing environmental benefits, as low as -3.7 kgCO 2 eq kg -1 protein and positive fluxes, i.e., global warming potential, as high as 12.8 kgCO 2 eq kg -1 protein. There is limited research on bioplastics life cycle emissions reported at 0.6 kgCO 2 eq kg -1 protein. In general, the studies to date of algae-derived protein bioproducts showed similar life cycle emissions to soybean meals, nylon, polymers, and polystyrenes. Our risk analysis realized that more than 50% of scenarios can result in negative-net life cycle CO 2 eq emissions. This review and risk analysis assess and demonstrate the scenarios that improve economic and environmental sustainability metrics in high-protein algal bioproducts systems.

09 BIOMASS FUELS↗
DOE OSTI2022

Quantifying electron temperature distributions from time-integrated x-ray emission spectra

K-shell x-ray emission spectroscopy is a standard tool used to diagnose the plasma conditions created in high-energy-density physics experiments. In the simplest approach, the emissivity-weighted average temperature of the plasma can be extracted by fitting an emission spectrum to a single temperature condition. It is known, however, that a range of plasma conditions can contribute to the measured spectra due to a combination of the evolution of the sample and spatial gradients. In this work, we define a parameterized model of the temperature distribution and use Markov Chain Monte Carlo sampling of the input parameters, yielding uncertainties in the fit parameters to assess the uniqueness of the inferred temperature distribution. Here we present the analysis of time-integrated S and Fe x-ray spectroscopic data from the Orion laser facility and demonstrate that while fitting each spectral region to a single temperature yields two different temperatures, both spectra can be fit simultaneously with a single temperature distribution. We find that fitting both spectral regions together requires a maximum temperature of $1310^{+90}_{-70}$ eV with significant contributions from temperatures down to 200 eV.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Impact of High-Reactivity Advanced Test Reactor Experiments on Photon Heating in Nearby Experiment Locations

The Advanced Test Reactor’s (ATR’s) distinctive ability to provide a wide range of irradiation conditions is attractive for programs pursuing fuel qualification experiments. These potentially high-fuel-load experiments are a relatively new development and produce unexplored effects on nearby experiments. Here, this paper explores how photon heating of such an experiment may affect other nearby experiment programs, ultimately serving to better inform decisions regarding experiment design and risks to programmatic goals. The MC21 (Monte Carlo for the 21st Century) code is used to model and study how gamma heat generation rates and axial effects impact different ATR positions. The results reveal that the proximity of a given experiment’s position to the high-fuel-load one can significantly alter that experiment’s expected axial profile.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Multimuons in cosmic-ray events as seen in ALICE at the LHC

ALICE is a large experiment at the CERN Large Hadron Collider. Located 52 meters underground, its detectors are suitable to measure muons produced by cosmic-ray interactions in the atmosphere. In this paper, the studies of the cosmic muons registered by ALICE during Run 2 (2015–2018) are described. The analysis is limited to multimuon events defined as events with more than four detected muons (N μ > 4) and in the zenith angle range 0° < θ < 50°. The results are compared with Monte Carlo simulations using three of the main hadronic interaction models describing the air shower development in the atmosphere: QGSJET-II-04, EPOS-LHC, and SIBYLL 2.3d. The interval of the primary cosmic-ray energy involved in the measured muon multiplicity distribution is about 4 × 10 15 < E prim < 6 × 10 16 eV. In this interval none of the three models is able to describe precisely the trend of the composition of cosmic rays as the energy increases. However, QGSJET-II-04 is found to be the only model capable of reproducing reasonably well the muon multiplicity distribution, assuming a heavy composition of the primary cosmic rays over the whole energy range, while SIBYLL 2.3d and EPOS-LHC underpredict the number of muons in a large interval of multiplicity by more than 20% and 30%, respectively. The rate of high muon multiplicity events (N μ > 100) obtained with QGSJET-II-04 and SIBYLL 2.3d is compatible with the data, while EPOS-LHC produces a significantly lower rate (55% of the measured rate). For both QGSJET-II-04 and SIBYLL 2.3d, the rate is close to the data when the composition is assumed to be dominated by heavy elements, an outcome compatible with the average energy E prim ∼ 10 17 eV of these events. This result places significant constraints on more exotic production mechanisms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Dual View of the Z 2 -Gauged XY Model in 3D

The 𝑍 2 -gauged XY model is of long-standing interest both in the context of nematic order, and the study of fractionalization and superconductivity. This Letter presents heuristic arguments that no deconfinement of the XY field occurs in this model and presents results of a large-scale Monte Carlo simulations on a cubic lattice that are consistent with this conclusion. Furthermore, the correlation radius determining the confinement is found to be growing rapidly as a function of the parameters in the phase featuring the nematic order. Thus, mesoscopic properties of the system can mimic deconfinement with high accuracy in some part of the phase diagram.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Planck constraints and gravitational wave forecasts for primordial black hole dark matter seeded by multifield inflation

Here, we perform a Markov Chain Monte Carlo analysis of a simple yet generic multifield inflation model characterized by two scalar fields coupled to each other and nonminimally coupled to gravity, fit to Planck 2018 cosmic microwave background (CMB) data. In particular, model parameters are constrained by data on the amplitude of the primordial power spectrum of scalar curvature perturbations on CMB scales A s , the spectral index n s , and the ratio of power in tensor to scalar modes r, with a prior that the primordial power spectrum should also lead to primordial black hole (PBH) production sufficient to account for the observed dark matter abundance. We find that n s in particular controls the constraints on our model. Whereas previous studies of PBH formation from an ultraslow-roll phase of inflation have highlighted the need for at least one model parameter to be highly fine-tuned, we identify a degeneracy direction in parameter space such that shifts by ~10% of one parameter can be compensated by comparable shifts in other parameters while preserving a close fit between model predictions and observations. Furthermore, we find this allowed parameter region produces observable gravitational wave signals in the frequency ranges to which upcoming experiments are projected to be sensitive, including Advanced LIGO and Virgo, the Einstein Telescope, Cosmic Explorer, DECIGO, and LISA.

79 ASTRONOMY AND ASTROPHYSICS↗