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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

BISON microstructure-based pulverization criterion in high burnup structure

To improve the economics of commercial nuclear power production, utilities are seeking to increase the allowable burnup limit of UO$_2$ fuel. One of the main factors that contributes to the current burnup limit of 62 GWd/MTU in commercial light water reactors (LWRs) is the risk of fine fragmentation or pulverization during a loss of coolant accident (LOCA). Pulverization primarily occurs at high burnups, especially when the high burnup structure (HBS) has formed. To allow the industry to pursue increased burnup and develop mitigation strategies, it is essential to have improved capability to predict the onset of pulverization. However, the mechanism of pulverization is not well understood, and the existing predictive capabilities implemented in the BISON fuel performance code are empirical in nature. In this report, mesoscale simulations are used to improve understanding of the formation mechanism of the HBS and how it responds during a LOCA transient, and inform development of a BISON pulverization criterion. A phase-field model was used to simulate the evolution of bubble pressure as a result of HBS formation. The simulations showed that gas atoms diffuse from grain interiors to the new grain boundaries created during HBS formation, and diffuse rapidly along these grain boundaries to reach existing bubbles. This causes an increase in bubble pressure in existing bubbles, leading to bubble growth during steady-state operation. To simulate the response of HBS bubbles to a LOCA transient, a newly developed phase-field model was used; in agreement with preliminary results from FY20, bubble size did not change significantly during the duration of the transient. A phase-field fracture model was used to study fragmentation patterns in the HBS, including using input from the phase-field model as initial conditions. Phase-field fracture simulations were used to determine a pulverization criterion for BISON. A function for the critical pressure for pulverization to occur was fit to data from the phase-field fracture simulations, and this function was implemented as a material property in BISON. For comparison, an analytical criterion for pulverization was developed and implemented within the same material property.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Unravelling the dynamics of the maturation protein in MS2 bacteriophage via molecular simulations

The MS2 bacteriophage capsid serves as a model system for studying viral structure and function. Mature MS2 virus consists of 178 capsid proteins and a single maturation protein (MP), which is essential for host receptor binding and infection initiation. Despite its critical role, the dynamic behavior of the capsid with the MP remains poorly understood. To address this, we conducted 0.5 µs all-atom molecular dynamics (MD) simulations of the MS2 capsid with and without the MP, revealing key insights into its structural dynamics. Our simulations showed that MP exhibits high flexibility, particularly in the “tip” and “side-loop” regions, which undergo significant motions that likely enhance its ability to engage with the F-pilus receptor. Detailed analysis of MP conformational states revealed that loop rearrangements around H357 enable transient switching between “semi-closed” and “open” conformations, suggesting a conformational selection mechanism for pilus binding. Additionally, ion interaction analyses revealed distinct sodium and chloride binding patterns, where sodium ions were mostly found at the outer capsid shell, while chloride ions interacted with the basic residues on the RNA-facing side. We also found that the presence of the MP enhances salt-bridge interactions, contributing to increased capsid stability, yet it does not significantly alter the pore sizes of pentameric and hexameric units. Together, these findings provide new insights into the functional role of the MP, highlighting its contribution to capsid stability and host receptor engagement. This study offers a foundation for understanding capsid dynamics relevant to viral infectivity and may guide future rational strategies aimed at disrupting host-virus interactions.

Capsid stability↗
DOE OSTI2022

Triangular lattice quantum dimer model with variable dimer density

Abstract Quantum dimer models are known to host topological quantum spin liquid phases, and it has recently become possible to simulate such models with Rydberg atoms trapped in arrays of optical tweezers. Here, we present large-scale quantum Monte Carlo simulation results on an extension of the triangular lattice quantum dimer model with terms in the Hamiltonian annihilating and creating single dimers. We find distinct odd and even $${{\mathbb{Z}}}_{2}$$ Z 2 spin liquids, along with several phases with no topological order: a staggered crystal, a nematic phase, and a trivial symmetric phase with no obvious broken symmetry. We also present dynamic spectra of the phases, and note implications for experiments on Rydberg atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2018

Solar Wind Implantation Into the Lunar Regolith: Monte Carlo Simulations of H Retention in a Surface With Defects and the H2 Exosphere

The solar wind implants protons into the top 20–30 nm of lunar regolith grains, and the implanted hydrogen will diffuse out of the regolith but also interact with oxygen in the regolith oxides. We apply a statistical approach to estimate the diffusion of hydrogen in the regolith hindered by forming temporary bonds with regolith oxygen atoms. A Monte Carlo simulation was used to track the temporal evolution of bound OH surface content and the H2 exosphere. The model results are consistent with the interpretation of the Chandrayaan‐1 M3 observations of infrared absorption spectra by surface hydroxyls as discussed in Li and Milliken (2017, https://doi.org/10.1126/sciadv.1701471). The model reproduced the latitudinal concentration of OH by using a Gaussian energy distribution of f(U(sub 0) = 0.5 eV, U(sub W) = 0.078–0.1 eV) to characterize the activation energy barrier to the diffusion of hydrogen in space weathered regolith. In addition, the model results of the exospheric content of H2 are consistent with observations by the Lyman Alpha Mapping Project on the Lunar Reconnaissance Orbiter. Therefore, we provide support for hydroxyl formation by chemically trapped solar wind protons.

Tucker, O. J.↗
NASA NTRS2018

Solar Wind Implantation Into the Lunar Regolith: Monte Carlo Simulations of H Retention in a Surface With Defects and the H2 Exosphere

The solar wind implants protons into the top 20–30 nm of lunar regolith grains, and the implanted hydrogen will diffuse out of the regolith but also interact with oxygen in the regolith oxides. We apply a statistical approach to estimate the diffusion of hydrogen in the regolith hindered by forming temporary bonds with regolith oxygen atoms. A Monte Carlo simulation was used to track the temporal evolution of bound OH surface content and the H2 exosphere. The model results are consistent with the interpretation of the Chandrayaan-1 M3 observations of infrared absorption spectra by surface hydroxyls as discussed in Li and Milliken (2017). Themodel reproduced the latitudinal concentration of OH by using a Gaussian energy distribution of f(U(o) = 0.5eV, U(w) = 0.078 – 0.1 eV) to characterize the activation energy barrier to the diffusion of hydrogen in space weathered regolith. In addition, the model results of the exospheric content of H2 are consistent with observations by the Lyman Alpha Mapping Project on the Lunar Reconnaissance Orbiter. Therefore, we provide support for hydroxyl formation by chemically trapped solar wind protons.

O. J. Tucker↗
NASA NTRS2018

Solar Wind Implantation Into the Lunar Regolith: Monte Carlo Simulations of H Retention in a Surface With Defects and the H2 Exosphere

The solar wind implants protons into the top 20–30 nm of lunar regolith grains, and the implanted hydrogen will diffuse out of the regolith but also interact with oxygen in the regolith oxides. We apply a statistical approach to estimate the diffusion of hydrogen in the regolith hindered by forming temporary bonds with regolith oxygen atoms. A Monte Carlo simulation was used to track the temporal evolution of bound OH surface content and the H2 exosphere. The model results are consistent with the interpretation of the Chandrayaan‐1 M3 observations of infrared absorption spectra by surface hydroxyls as discussed in Li and Milliken (2017, https://doi.org/10.1126/sciadv.1701471). The model reproduced the latitudinal concentration of OH by using a Gaussian energy distribution of f(U0 = 0.5 eV, UW = 0.078–0.1 eV) to characterize the activation energy barrier to the diffusion of hydrogen in space weathered regolith. In addition, the model results of the exospheric content of H2 are consistent with observations by the Lyman Alpha Mapping Project on the Lunar Reconnaissance Orbiter. Therefore, we provide support for hydroxyl formation by chemically trapped solar wind protons.

O J Tucker↗
DOE OSTI2023

Voltage-Dependent First-Principles Simulation of Insertion of Chloride Ions into Al/Al 2 O 3 Interfaces Using the Quantum Continuum Approximation

Experiments have shown that pitting corrosion can develop in aluminum surfaces at potentials > − 0.5 V relative to the standard hydrogen electrode (SHE). Until recently, the onset of pitting corrosion in aluminum has not been rigorously explored at an atomistic scale because of the difficulty of incorporating a voltage into density functional theory (DFT) calculations. We introduce the Quantum Continuum Approximation (QCA) which self-consistently couples explicit DFT calculations of the metal-insulator and insulator-solution interfaces to continuum Poisson-Boltzmann electrostatic distributions describing the bulk of the insulating region. By decreasing the number of atoms necessary to explicitly simulate with DFT by an order of magnitude, QCA makes the first-principles prediction of the voltage of realistic electrochemical interfaces feasible. After developing this technique, we apply QCA to predict the formation energy of chloride atoms inserting into oxygen vacancies in Al(111)/α-Al 2 O 3 (0001) interfaces as a function of applied voltage. We predict that chloride insertion is only favorable in systems with a grain boundary in the Al 2 O 3 for voltages > − 0.2 V (SHE). Here our results roughly agree with the experimentally demonstrated onset of corrosion, demonstrating QCA's utility in modeling realistic electrochemical systems at reasonable computational cost.

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

Molecular dynamics simulations of energy accommodation between gases and polymers for ultra-low thermal conductivity insulation

Determining the energy accommodation between gases and solids is essential to developing porous thermal insulation materials with ultra-low effective thermal conductivity that reduce energy use, greenhouse gas emissions, and fossil fuel consumption. The energy accommodation coefficients of most gases, however, have been rarely studied, especially with respect to solids that have relatively high thermal resistivity, e.g., polymers. Here, by using all-atom nonequilibrium molecular dynamics simulations, we reveal the accommodation coefficients of He, Ar, N 2 , and O 2 with polymers, mainly polystyrene. We find that their values are around 0.51, 0.72, 0.79, and 0.90, respectively, suggesting a critical reexamination of the commonly used theoretical maximum value of 1. We have also conducted experiments and validated the value for air, which is about 0.81. Such a change in accommodation coefficients can lead to a reduction of about 70%, 50%, 35%, and 20% in the thermal conductivity of He, Ar, N 2 , and O 2 gases in nano pores (below 100 nm) or at low pressures (below 1 millibar). With these new accommodation coefficients, we find that in a 10 nm pore with ambient pressure at 300 K, the gas thermal conductivity of He, Ar, N 2 , and O 2 in porous polystyrene can be as low as 9.7 × 10 –4 , 3.4 × 10 –4 , 7.3 × 10 –4 , and 8.5 × 10 –4 W·m –1 ·K –1 , respectively, which are two to three orders of magnitude lower than their bulk values, promising higher thermal resistivity of insulation materials. This work reveals the fundamental energy exchange between gases and polymers, providing important guidance for designing high-performance thermal insulation materials for various applications.

36 MATERIALS SCIENCE↗
NASA NTRS1974

Reflection of a thick planar shock wave from a coplanar surface

The reflection of a thick shock wave from an adsorbing surface has been studied for argon and neon test gases using the direct simulation Monte Carlo method and laboratory shock-tube experiments. In the simulation, collisions between gas atoms were calculated with a point-center repulsive intermolecular potential, and collisions between gas atoms and the surface were described by a simple two-parameter model which includes the effects of adsorption and thermal accommodation. Experimental data included normal stress and temperature time histories on the surface of a shock-tube and wall. These data and published data of density variations near the end wall were compared with simulation results to assess the influence of adsorption and accommodation on the flowfield and the surface and also to infer optimum values for the surface-interaction model parameters. Good quantitative agreement between simulation and laboratory data was found with this simple surface-interaction model.

Deiwert, G. S.↗
NASA NTRS2005

Simulated Space Environment Effects on Tether Materials with Protective Coatings

Atomic oxygen (AO) erodes most organic materials. and ultraviolet radiation embrittles polymers. A previous study indicated untreated polymers such as ultra-high molecular weight polyethylene (UHMWPE) are severely degraded when exposed to AO. This test series was performed to determine the effect of AO and UV on the mechanical integrity of tether materials that were treated with AO-protective coatings. Three coating systems were evaluated for their ability to protect the underlying material from AO erosion. The first coating system is the Photosil surface modification process which incorporates silicon-containing functional groups into the top micron of an organic material. The Photosil process has had favorable results with polyurethane- and epoxy-based thermal control coatings . The second coating system is metallization, in this case nickel. The third coating system is silsesquioxane. The Marshall Space Flight Center Atomic Oxygen Beam Facility (AOBF) was used to simulate low Earth orbit AO of 5 eV energy. In addition, some tether samples were exposed to ultraviolet radiation then evaluated for any changes in mechanical strength. Tether missions, such as a momentum-exchange/electrodynamic reboost (MXER) tether, may benefit from this research.

Finckenor, Miria M.↗
DOE OSTI2021

Shape Stability of Truncated Octahedral fcc Metal Nanocrystals

Metallic nanocrystals (NCs) can be synthesized with tailored nonequilibrium shapes to enhance desired properties, e.g., octahedral fcc metal NCs optimize catalytic activity associated with {111} facets. However, maintenance of optimized properties requires stability against thermal reshaping. Thus, we analyze the reshaping of truncated fcc metal octahedra mediated by surface diffusion using a stochastic atomistic-level model with energetic input parameters for Pd. Furthermore, the model describes NC thermodynamics by an effective nearest-neighbor interaction and includes a realistic treatment of diffusive hopping for undercoordinated surface atoms. Kinetic Monte Carlo simulation reveals that the effective barrier, E eff , for the initial stage of reshaping is strongly tied to the degree of truncation of the vertices in the synthesized initial octahedral shapes. This feature is elucidated via exact analytic determination of the energy variation along the optimal reshaping pathway at low-temperature (T), which involves transfer of atoms from truncated {100} vertex facets to form new layers on {111} side facets. Deviations from predictions of the low-T analysis due to entropic effects are more prominent for higher T and larger NC sizes.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Flow visualization of a rocket injector spray using gelled propellant simulants

A study was conducted at NASA-Lewis to compare the atomization characteristics of gelled and nongelled propellant simulants. A gelled propellant simulant composed of water, sodium hydroxide, and an acrylic acid polymer resin (as the gelling agent) was used to simulate the viscosity of an aluminum/PR-1 metallized fuel gel. Water was used as a comparison fluid to isolate the rheological effects of the water-gel and to simulate nongelled RP-1. The water-gel was injected through the central orifice of a triplet injector element and the central post of a coaxial injector element. Nitrogen gas flowed through the outer orifices of the triplet injector element and through the annulus of the coaxial injector element and atomized the gelled and nongelled liquids. Photographs of the water-gel spray patterns at different operating conditions were compared with images obtained using water and nitrogen. A laser light was used for illumination of the sprays. The results of the testing showed that the water sprays produced a finer and more uniform atomization than the water-gel sprays. Rheological analysis of the water-gel showed poor atomization caused by high viscosity of water-gel delaying the transition to turbulence.

Green, James M.↗
NASA NTRS1991

Flow visualization of a rocket injector spray using gelled propellant simulants

A study was conducted at NASA-Lewis to compare the atomization characteristics of gelled and nongelled propellant simulants. A gelled propellant simulant composed of water, sodium hydroxide, and an acrylic acid polymer resin (as the gelling agent) was used to simulate the viscosity of an aluminum/PR-1 metallized fuel gel. Water was used as a comparison fluid to isolate the rheological effects of the water-gel and to simulate nongelled RP-1. The water-gel was injected through the central orifice of a triplet injector element and the central post of a coaxial injector element. Nitrogen gas flowed through the outer orifices of the triplet injector element and through the annulus of the coaxial injector element and atomized the gelled and nongelled liquids. Photographs of the water-gel spray patterns at different operating conditions were compared with images obtained using water and nitrogen. A laser light was used for illumination of the sprays. The results of the testing showed that the water sprays produced a finer and more uniform atomization than the water-gel sprays. Rheological analysis of the water-gel showed poor atomization caused by high viscosity of water-gel delaying the transition to turbulence.

Green, James M.↗
DOE OSTI2023

Multiscale Reactive Model for 1,3,5-Triamino-2,4,6-trinitrobenzene Inferred by Reactive MD Simulations and Unsupervised Learning

When high-energy-density materials are subjected to thermal or mechanical insults at extreme conditions (shock loading), a coupled response between the thermo-mechanical and chemical behaviors is systematically induced. Herein we develop a reaction model for the fast chemistry of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) at the mesoscopic scale, where the chemical behavior is determined by underlying microscopic reactive simulations. The slow carbon cluster formation is not discussed in the present work. All-atom reactive molecular dynamics (MD) simulations are performed with the ReaxFF potential, and a reduced-order chemical kinetics model for TATB is fitted to isothermal and adiabatic simulations of single crystal chemical decomposition. Unsupervised machine learning techniques based on non-negative matrix factorization are applied to MD trajectories to model the decomposition kinetics of TATB in terms of a four-component model. The associated heats of reaction are fit to the temperature evolution from adiabatic decomposition trajectories. Using a chemical species analysis, we show that non-negative matrix factorization captures the main chemical decomposition steps of TATB and provides an accurate estimation of their evolution with temperature. The final analytical formulation, coupled to a diffusion term, is incorporated into a continuum formalism, and simulation results are compared one-to-one against MD simulations of 1D reaction propagation along different crystallographic directions and with different initial temperatures. A good agreement is found for both the temporal and spatial evolution of the temperature field.

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

Continuous operation of a coherent 3,000-qubit system

Neutral atoms are a promising platform for quantum science, enabling advances in areas ranging from quantum simulations and computation to metrology, atomic clocks and quantum networking. Although atom losses typically limit these systems to a pulsed mode, continuous operation could substantially enhance cycle rates, remove bottlenecks in metrology and enable deep-circuit quantum evolution through quantum error correction. Here we demonstrate an experimental architecture for high-rate reloading and continuous operation of a large-scale atom-array system while realizing coherent storage and manipulation of quantum information. Our approach utilizes a series of two optical lattice conveyor belts to transport atom reservoirs into the science region, where atoms are repeatedly extracted into optical tweezers without affecting the coherence of qubits stored nearby. Using a reloading rate of 300,000 atoms in tweezers per second, we create over 30,000 initialized qubits per second, which we leverage to assemble and maintain an array of over 3,000 atoms for more than 2 hours. Furthermore, we demonstrate persistent refilling of the array with atomic qubits in either a spin-polarized or a coherent superposition state while preserving the quantum state of stored qubits. Our results pave the way for the realization of large-scale continuously operated atomic clocks, sensors and fault-tolerant quantum computers.

atomic and molecular physics↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Structure, Dynamics, and Hydrogen Transport in Amorphous Polymers: An Analysis of the Interplay between Free Volume Element Distribution and Local Segmental Dynamics from Molecular Dynamics Simulations

Polymers are attractive membrane materials owing to their mechanical robustness and relatively inexpensive fabrication. An important indicator of membrane performance are free volume elements (FVE): microporous void spaces created by the inefficient packing of bulky groups along the polymer chain. FVEs tend to degrade over time, as polymer chains reorganize irreversibly. While it is widely accepted that polymer flexibility has an impact on membrane transport properties, the molecular nature of this impact is still not well understood. By the establishment of a correlation between local chain dynamics and the distribution of free volume elements (FVEs), penetrant transport can be regulated more efficiently in amorphous polymer membranes. In this work, we implement all-atom molecular dynamics (MD) simulations to explore the relationship between chain dynamics and free volume in three polymers with different levels of backbone flexibility: polymethylpentene (PMP), polystyrene (PS), and HAB-6FDA thermally rearranged polymer (TRP). We construct these polymers at different temperatures and examine how temperature impacts the FVE distribution and segmental mobility. Our analysis shows that chain segments near FVEs have higher mobility compared with the atoms in the bulk; the extent of this difference increases with chain flexibility. Increasing the chain flexibility by increasing the temperature results in a broader FVE distribution. Rigid polymers such as TRP show the most robust FVE distribution and are not significantly affected by the temperature change. To capture penetrant diffusion through the polymer matrix, hydrogen is inserted and the diffusion is measured at different temperatures; hydrogen mobility is influenced by the FVE structure and overall mobility of polymer chains. Lastly, at low temperatures, hydrogen mobility is influenced by void distribution, while at high temperatures, polymer dynamics dictate hydrogen transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗