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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Semi-Empirical Interatomic Potential for Large-Scale Molecular Dynamics Simulation of Metal-Oxide Systems

Classical molecular dynamics (MD) simulation can be applied to systems containing billions of atoms during times up to microseconds. However, utilization of a large-scale MD simulation requires reliable but computationally cheap interatomic potentials. In the case of metallic systems, embedded atom method (EAM) and Finnis-Sinclair (FS) potentials are the reasonable choices, but their development for multicomponent alloys is a challenge. Addition of oxygen atoms makes the problem of developing semi-empirical potentials even more difficult because the long-range Coulomb interaction cannot be neglected, and different atoms have different charges which vary during MD relaxation such that a charge equilibration procedure should be applied every MD step. As results researchers tend to avoid simulating metal-oxide systems. In this talk, a new Finnis-Sinclair (FS) Ni-Co-Cr potential will be presented. Special attention will be paid to reproducing of the element melting temperatures and clustering. Next, a charge transfer ionic potential (CTIP) developed to simulate the NiO properties will be presented. This potential utilizes the Ni FS potential and accounts for the Coulomb interaction in the vicinity of oxygen atoms. Fitting of the CTIP parameters and FS potential functions describing the interaction with oxygen atoms to the available experimental and ab initio data will be discussed. Results of MD simulation of interaction of NiO particles with dislocations in Ni will be shown.

molecular dynamics simulation↗
NASA NTRS2013

An Elevated Reservoir of Air Pollutants over the Mid-Atlantic States During the 2011 DISCOVER-AQ Campaign: Airborne Measurements and Numerical Simulations

During a classic heat wave with record high temperatures and poor air quality from July 18 to 23, 2011, an elevated reservoir of air pollutants was observed over and downwind of Baltimore, MD, with relatively clean conditions near the surface. Aircraft and ozonesonde measurements detected approximately 120 parts per billion by volume ozone at 800 meters altitude, but approximately 80 parts per billion by volume ozone near the surface. High concentrations of other pollutants were also observed around the ozone peak: approximately 300 parts per billion by volume CO at 1200 meters, approximately 2 parts per billion by volume NO2 at 800 meters, approximately 5 parts per billion by volume SO2 at 600 meters, and strong aerosol optical scattering (2 x 10 (sup 4) per meter) at 600 meters. These results suggest that the elevated reservoir is a mixture of automobile exhaust (high concentrations of O3, CO, and NO2) and power plant emissions (high SO2 and aerosols). Back trajectory calculations show a local stagnation event before the formation of this elevated reservoir. Forward trajectories suggest an influence on downwind air quality, supported by surface ozone observations on the next day over the downwind PA, NJ and NY area. Meteorological observations from aircraft and ozonesondes show a dramatic veering of wind direction from south to north within the lowest 5000 meters, implying that the development of the elevated reservoir was caused in part by the Chesapeake Bay breeze. Based on in situ observations, Community Air Quality Multi-scale Model (CMAQ) forecast simulations with 12 kilometers resolution overestimated surface ozone concentrations and failed to predict this elevated reservoir; however, CMAQ research simulations with 4 kilometers and 1.33 kilometers resolution more successfully reproduced this event. These results show that high resolution is essential for resolving coastal effects and predicting air quality for cities near major bodies of water such as Baltimore on the Chesapeake Bay and downwind areas in the Northeast.

ozone↗
NASA NTRSDate not supplied

Surrogate Optimization for Quantum Circuits

Variational quantum Eigensolvers are touted as a near-term algorithm capable of impacting many applications. However, the potential has yet to be realized with few claims of quantum advantage and high resource estimates mainly due to the need for optimization in the presence of noise. Finding algorithms and methods to improve the convergence is essential to accelerate the capabilities of near-term hardware for VQE or more broad applications of hybrid methods in which optimization is required. To this goal we look to use modern approaches recently developed in circuit simulations and stochastic classical optimization that can be combined in a surrogate optimization approach to classical circuits. Using an approximate state vector simulator, we efficiently calculate an approximate Hessian, fed as an input for a detailed quantum circuit simulator. We demonstrate the capabilities of such an approach with and without sampling noise. We also show that this method outperforms Powell in the presence of quantum circuit shot noise by a factor of 2-4

quantum computing↗
DOE OSTI2025

Classical Benchmarks for Variational Quantum Eigensolver Simulations of the Hubbard Model

Simulating the Hubbard model is of great interest to a wide range of applications within condensed matter physics, however its solution on classical computers remains challenging in dimensions larger than one. The relative simplicity of this model, embodied by the sparseness of the Hamiltonian matrix, allows for its efficient implementation on quantum computers, and for its approximate solution using variational algorithms such as the variational quantum eigensolver. While these algorithms have been shown to reproduce the qualitative features of the Hubbard model, their quantitative accuracy in terms of producing true ground state energies and other properties, and the dependence of this accuracy on the system size and interaction strength, the choice of variational ansatz, and the degree of spatial inhomogeneity in the model, remains unknown. Here we present a rigorous classical benchmarking study, demonstrating the potential impact of these factors on the accuracy of the variational solution of the Hubbard model on quantum hardware, for systems with up to 32 qubits. We find that even when using the most accurate wavefunction ansätze for the Hubbard model, the error in its ground state energy and wavefunction plateaus for larger lattices, while stronger electronic correlations magnify this issue. Concurrently, spatially inhomogeneous parameters and the presence of off-site Coulomb interactions only have a small effect on the accuracy of the computed ground state energies. Our study highlights the capabilities and limitations of current approaches for solving the Hubbard model on quantum hardware, and we discuss potential future avenues of research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Emulation of quantum correlations by classical dynamics in a spin-$\frac{1}{2}$ Heisenberg chain

We simulate the dynamical spin structure factor (DSSF) 𝒮⁡(𝑞,𝜔) of the spin-1/2 Heisenberg antiferromagnetic chain using classical simulations. By employing Landau-Lifshitz Dynamics, we emulate quantum correlations through temperature-dependent corrections, including rescaling of magnetic dipoles and renormalization of exchange interactions. Here, our results closely match Quantum Monte-Carlo calculations for 𝑘 B⁢ 𝑇/𝐽≳1, extending the applicability of classical dynamics to the challenging case of gapless excitations. At higher temperatures, our simulations comply with general predictions for uncorrelated paramagnetic fluctuations in the infinite temperature limit. Entanglement witnesses derived from the quantum-equivalent DSSF act as sensitive diagnostics for the quantum-to-classical crossover. Their reliability stems from their dependence on spectral features alone, enabling classical dynamics to emulate quantum thresholds without genuine entanglement. This framework also reproduces transverse spin correlations in finite magnetic fields, in agreement with quantum simulations. Together, our results establish quantum-corrected classical dynamics as a scalable and predictive tool for interpreting scattering experiments and exploring quantum correlations in strongly correlated spin systems.

Inelastic neutron scattering↗
NASA NTRS2002

Computational Nanomechanics of Carbon Nanotubes and Composites

Nanomechanics of individual carbon and boron-nitride nanotubes and their application as reinforcing fibers in polymer composites has been reviewed with interplay of theoretical modeling, computer simulations and experimental observations. The emphasis in this work is on elucidating the multi-length scales of the problems involved, and of different simulation techniques that are needed to address specific characteristics of individual nanotubes and nanotube polymer-matrix interfaces. Classical molecular dynamics simulations are shown to be sufficient to describe the generic behavior such as strength and stiffness modulus but are inadequate to describe elastic limit and nature of plastic buckling at large strength. Quantum molecular dynamics simulations are shown to bring out explicit atomic nature dependent behavior of these nanoscale materials objects that are not accessible either via continuum mechanics based descriptions or through classical molecular dynamics based simulations. As examples, we discus local plastic collapse of carbon nanotubes under axial compression and anisotropic plastic buckling of boron-nitride nanotubes. Dependence of the yield strain on the strain rate is addressed through temperature dependent simulations, a transition-state-theory based model of the strain as a function of strain rate and simulation temperature is presented, and in all cases extensive comparisons are made with experimental observations. Mechanical properties of nanotube-polymer composite materials are simulated with diverse nanotube-polymer interface structures (with van der Waals interaction). The atomistic mechanisms of the interface toughening for optimal load transfer through recycling, high-thermal expansion and diffusion coefficient composite formation above glass transition temperature, and enhancement of Young's modulus on addition of nanotubes to polymer are discussed and compared with experimental observations.

Srivastava, Deepak↗
DOE OSTI2026

Data for The impact of aerosol mixing state on immersion freezing: Insights from classical nucleation theory and particle-resolved simulations

This dataset contains the values directly shown in the figures of the article "The impact of aerosol mixing state on immersion freezing: Insights from classical nucleation theory and particle-resolved simulations". This article is in preparation for submission to the journal Atmospheric Chemistry and Physics. The dataset consists of 12 NetCDF files processed from the raw output of the PartMC model. It does not include the theoretical values of frozen fraction, which can be computed using the equations provided in the paper. *New in V2: adding data for a newly included figure (INP_spectrum.nc), removing files that are no longer used in the revised manuscript figures (e.g., UNC_A_ratio=0.9_Dp=0.1.nc, UNC_A_ratio=0.9_Dp=10.0.nc, UNC_A_ratio=0.1_Dp=0.1.nc, and UNC_A_ratio=0.1_Dp=10.0.nc), and updating README.pdf accordingly.

Aerosol mixing state↗
NASA NTRS1991

A comparison of classical mechanics models and finite element simulation of elastically tailored wing boxes

Structural tailoring concepts were developed to create wings with elastically produced camber for the purpose of increasing lift during takeoff conditions. Simple models based upon enhancements to the thin walled composite beam theory of Rehfield were developed to investigate prospects for elastic tailoring of the chordwise deformation of wing structures. The purpose here is to provide a comparison of the theoretical results with a finite element model for the bending method of producing camber. Finite element correlation studies were completed for two cases: a bonded unstiffened structural box, and a bolted unstiffened structural box. Results from these studies show an error of less than one percent for the bonded case and less than six percent for the bolted case in predicting camber curvature for the structural box. Examination of the results shows that the theory is very accurate for the cases studied and will provide an excellent basis for conducting further tailoring studies.

Rehfield, Lawrence W.↗
NASA NTRS2014

Development of Dynamic Sub-Grid Models for Variational Multiscale Methods

A dynamic Variational Multiscale Method (Hughes et al. 1998) is developed by leveraging the Germano procedure from classical Large-eddy Simulations (LES). The similarity between the classical and variational approaches is analyzed in the context of incompressible flow. This analysis leads to a consistent modeling approach for both incompressible and compressible flows, the latter being demonstrated in a priori testing for low-speed attached and separated boundary layers. Similar to the classical LES procedure from which it is derived, the variational dynamic procedure does not guarantee a positive semi-definite coefficient in the general case. However, reproducing the behavior of the classical LES dynamic approach is seen as a necessary first step to develop a VMM that automatically adjusts to the local resolution and flow physics.

Variational multiscale↗
NASA NTRS2021

Quantum Computing to Accelerate High Fidelity Computational Materials Modeling

In this CIF we worked to develop quantum algorithms for material science simulations based on new ideas recently proposed on plane wave basis sets. Many body simulations are not generally performed in plane wave basis sets on classical hardware, but with newly proposed quantum algorithms, it is possible this will be a highly efficient basis set to run quantum simulations on quantum hardware. Using state of the art classical simulations we ran small test simulations to estimate the resources that will be needed to run such plane wave algorithms on quantum hardware. We demonstrate our approach for a series of atoms and molecular systems.

Norman Tubman↗
DOE OSTI2026

Coupled Lindblad Pseudomode Theory for Simulating Open Quantum Systems

Coupled Lindblad pseudomode theory is a promising approach for simulating non-Markovian quantum dynamics on both classical and quantum platforms, with dynamics that can be realized as a quantum channel. We provide theoretical evidence that the number of coupled pseudomodes only needs to scale as polylog⁡(𝑇/𝜖) in the simulation time 𝑇 and precision 𝜖. Inspired by the realization problem in control theory, we also develop a robust numerical algorithm for constructing the coupled modes that avoid the nonconvex optimization required by existing approaches. We demonstrate the effectiveness of our method by computing population dynamics and absorption spectra for the spin-boson model. Furthermore, this Letter provides a significant theoretical and computational improvement to the coupled Lindblad framework, which impacts a broad range of applications from classical simulations of quantum impurity problems to quantum simulations on near-term quantum platforms.

Anderson impurity model↗
DOE OSTI2025

Thermodynamics of Liquid Uranium from Atomistic and Ab Initio Modeling

We present thermodynamic properties for liquid uranium obtained from classical molecular dynamics (MD) simulations and the first-principles theory. The coexisting phases method incorporated within MD modeling defines the melting temperature of uranium in good agreement with the experiment. The calculated melting enthalpy is in agreement with the experimental range. Classical MD simulations show that ionic contribution to the total specific heat of uranium does not depend on temperature. The density of states at the Fermi level, which is a crucial parameter in the determination of the electronic contribution to the total specific heat of liquid uranium, is calculated by ab initio all electron density functional theory (DFT) formalism applied to the atomic configurations generated by classical MD. The calculated specific heat of liquid uranium is compared with the previously calculated specific heat of solid γ-uranium at high temperatures. The liquid uranium cannot be supercooled below T sc ≈ 800 K or approximately about 645 K below the calculated melting point, although, the self-diffusion coefficient approaches zero at T D ≈ 700 K. Uranium metal can be supercooled about 1.5 times more than it can be overheated. The features of the temperature hysteresis are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Data and Code for Atomic Scale Etching of Diamond: Insights from Molecular Dynamics Simulations

This work investigates the effects of argon ions, hydrogen atoms, and hydrogen ions on the diamond (100) surface using classical molecular dynamics simulations. The purpose of this investigation was to asses plasma processing techniques for applications in quantum device manufacturing. The simulations suggest that combining argon ion smoothing with selective, near threshold energy H removal of amorphous C could be an effective strategy for diamond surface engineering, leading to more reliable and sensitive diamond color center devices. Results were found to differ significantly with interatomic potential, and an analysis of these differences was also carried out. Included in this repository are LAMMPS source files, input scripts, and plotting scripts required to reproduce the data. Also included are the output data required to make all the plots included in the associated publication.

Brenner↗
DOE OSTI2025

Developing the Science Basis for Understanding Polymer Encapsulant Degradation Mechanisms: DuraMAT 2.0 Final Project Report

Polymeric encapsulants are essential materials in photovoltaic modules, protecting sensitive electronics from the environment while providing mechanical integrity to the multilayered assembly. However, these polymeric materials are susceptible to degradation processes driven by the ingress of environmental species, ultraviolet radiation, thermal stresses, and mechanical loading. In this study, we employ a combined atomistic simulation and accelerated aging experimental approach to study the molecular-scale mechanisms of encapsulant degradation. Classical molecular dynamics simulations quantify the diffusion of environmental and degradation species through the polymer matrix, producing composition-specific diffusion coefficients. Reactive simulations characterize activation energy barriers and reaction rate constants for key chemical pathways. In parallel, thermal-desorption analyses coupled with mass spectrometry monitor the emergence and concentration profiles of degradation products under controlled stressor conditions. By integrating simulation and experiment, we establish quantitative correlations between polymer composition, species diffusivity, and chemical reactivity. We anticipate that these relations and quantitative values could serve as high-fidelity inputs to reaction-diffusion models, enabling physics-informed lifetime predictions and guiding the design of more durable encapsulant materials for solar energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Quantum-classical embedding via ghost Gutzwiller approximation for enhanced simulations of correlated electron systems

Simulating correlated materials on present-day quantum hardware remains challenging due to limited quantum resources. Quantum embedding methods offer a promising route by reducing computational complexity through the mapping of bulk systems onto effective impurity models, allowing more feasible simulations on pre- and early-fault-tolerant quantum devices. Here, this work develops a quantum-classical embedding framework based on the ghost Gutzwiller approximation to enable quantum-enhanced simulations of ground-state properties and spectral functions of correlated electron systems. Circuit complexity is analyzed using an adaptive variational quantum algorithm on a statevector simulator, applied to the infinite-dimensional Hubbard model with increasing ghost mode numbers from 3 to 5, resulting in circuit depths growing from 16 to 104. Noise effects are examined using a realistic error model, revealing significant impact on the spectral weight of the Hubbard bands. To mitigate these effects, the Iceberg quantum error detection code is employed, achieving up to 40% error reduction in simulations. Finally, the accuracy of the density matrix estimation and the derived spectral function is benchmarked on IBM and Quantinuum quantum hardware, featuring distinct qubit-connectivity and employing multiple levels of error mitigation techniques.

Chen, I-Chi [Ames Laboratory (AMES), Ames, IA (Uni↗
DOE OSTI2025

Structure, dynamics, and electrochemistry of choline chloride/ethylene glycol eutectic solvents at an electrode surface explored by molecular dynamics simulations

Choline chloride and ethylene glycol mixtures with 1:2, 1:4, and 1:6 molar ratios on the surfaces of graphite and gold electrodes were studied using classical molecular dynamics simulations. Both neutral and charged electrodes were considered. The liquid composition, solvation structure, molecular orientation, and dynamics at the electrode surface are significantly different from those of the bulk liquid. These properties strongly depend on the electrode material and charge density, whereas they are less sensitive to the overall solvent composition. The effect of the electrode on the composition, structure, and orientation of the liquid fades beyond ∼10 Å from the surface of the electrode. This distance corresponds to about two layers of the structured solvent, despite the fact that the layered structure extends to at least five layers or about 25 Å. However, the electrode influences solvent dynamics over a longer distance. The electrochemical properties of the eutectic solvent at both electrode surfaces were also studied. The simulations captured the experimental differential capacitance shapes for both electrode systems, although the magnitudes and exact shapes differ. The simulations further revealed that the solvent in the first solvation layer can both overscreen and underscreen the electrode charges depending on the electrode material and electrode potential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

The impact of aerosol mixing state on immersion freezing: insights from classical nucleation theory and particle-resolved simulations

Immersion freezing, initiated by ice-nucleating particles (INPs) in supercooled aqueous droplets, plays an important role in the formation of ice crystals within clouds. The efficiency of immersion freezing depends strongly on INP composition and, crucially, on the mixing state – how chemical species are distributed across the particle population. Here, we quantify the impact of aerosol mixing state on immersion freezing using a combined theoretical and particle-resolved modeling approach. We derive analytical expressions for the frozen fraction of internally and externally mixed INP populations based on classical nucleation theory, showing that the frozen fraction is sensitive to whether ice-active species are present in all particles or only in a subset of the population. We introduce a multi-species immersion freezing scheme into the particle-resolved model PartMC, using the water activity-based immersion freezing model (ABIFM) to compute freezing probabilities for mixed-composition particles. To improve computational efficiency, we implement a Binned Tau-Leaping algorithm and demonstrate an order-of-magnitude speedup with minimal accuracy loss. Simulations reproduce the analytical trends in limiting cases and extend the analysis to more general aerosol populations, where mixing state continues to exert a substantial control on frozen fraction. Sensitivity analyses across particle size, species type, and cooling condition reveal that the mixing state effect is most pronounced when small amounts of highly efficient INPs are mixed with less efficient materials. These findings underscore the need to represent aerosol mixing state explicitly in models of heterogeneous ice nucleation to reduce uncertainty in cloud-phase partitioning.

54 ENVIRONMENTAL SCIENCES↗