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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Molecular dynamics simulation studies of 1,3-dimethyl imidazolium nitrate ionic liquid with water

The fundamental understanding of intermolecular interactions of ionic liquids (ILs) with water is essential in predicting IL–water thermodynamic properties. In this study, intermolecular or noncovalent interactions were studied for 1,3-dimethyl imidazolium [DMIM]+ cation and nitrate [NO 3 ] – anion with water, employing quantum mechanics and molecular dynamics simulations. Molecular dynamics simulations were performed using a revised multipolar polarizable force field. The effect of water on ionic liquids was evaluated in terms of thermodynamic and dynamic properties. Thermodynamic properties included liquid densities ρ, excess molar volumes ΔV E , and liquid structures g(r)⁠. Dynamic properties included self-diffusion coefficients D of mixture constituents as a function of water concentration. The density of ionic liquid–water mixtures monotonically decrease with increasing concentration of water. A negative excess volume was obtained for low and high water concentrations, demonstrating strong intermolecular interactions of water with ionic liquid components. Liquid structures of ionic liquid–water mixtures revealed a tendency for anions to interact with cations at shorter intermolecular distances when the water concentration is increased. Diffusion rates were found to increase for all mixture components with increase in the fraction of water. A significant change in the diffusion rate was found at ~0.3 weight fraction of water. However, the water self-diffusion coefficient was dominant at all concentrations. Furthermore, the ratio of water/anion and anion/cation self-diffusion coefficients was found to decrease linearly with increasing concentration of water molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Interfacial Reactivity and Speciation Emerging from Na-Montmorillonite Interactions with Water and Formic Acid at 200 °C: Insights from Reactive Molecular Dynamics Simulations, Infrared Spectroscopy, and X-ray Scattering Measurements

Reactive organic fluid - mineral interactions at elevated temperatures contribute to the evolution of planetary matter. One of the less studied but important transformations in this regard involves the reactions of formic acid with naturally occurring clays such as sodium montmorillonite. To advance a mechanistic understanding of these interactions, we use ReaxFF reactive molecular dynamics simulations in conjunction with infrared (IR) spectroscopy and X-ray scattering experiments to investigate the speciation behavior of water-formic acid mixtures on sodium montmorillonite interfaces at 473 K and 1 atm. Using a newly developed reactive forcefield, we show that the experimental IR spectra of unreacted and reacted mixture can be accurately reproduced by ReaxFF/MD. We further benchmark the simulation predictions of sodium carbonate and bicarbonate formation in the clay interlayers using Small and Wide-Angle X-ray Scattering measurements. Subsequently, leveraging the benchmarked forcefield, we interrogate the pathway of speciation reactions with emphasis on carbonate, formate, and hydroxide groups elucidating the energetics, transition states, intermediates, and preferred products. Further, we also delineate the differences in reactivities and catalytic effects of clay edges, facets, and interlayers owing to their local chemical environments, which have far reaching consequences in their speciation behavior. The experimental and simulation approaches described in this study and the transferable forcefields can be applied translationally to advance the science of clay-fluid interactions for several applications including subsurface fluid storage and recovery and clay-pollutant dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Accelerators for Classical Molecular Dynamics Simulations of Biomolecules

Atomistic Molecular Dynamics (MD) simulations provide researchers the ability to model biomolecular structures such as proteins and their interactions with drug-like small molecules with greater spatiotemporal resolution than is otherwise possible using experimental methods. MD simulations are notoriously expensive computational endeavors that have traditionally required massive investment in specialized hardware to access biologically relevant spatiotemporal scales. Our goal is to summarize the fundamental algorithms that are employed in the literature to then highlight the challenges that have affected accelerator implementations in practice. We consider three broad categories of accelerators: Graphics Processing Units (GPUs), Field-Programmable Gate Arrays (FPGAs), and Application Specific Integrated Circuits (ASICs). These categories are comparatively studied to facilitate discussion of their relative trade-offs and to gain context for the current state of the art. We conclude by providing insights into the potential of emerging hardware platforms and algorithms for MD.

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

Crystallization of the P 3 Sn 4 Phase upon Cooling P 2 Sn 5 Liquid by Molecular Dynamics Simulation Using a Machine Learning Interatomic Potential

We performed molecular dynamics simulations to study the crystallization of the P3Sn4 phase from P 2 Sn 5 liquid using a machine learning (ML) interatomic potential with desirable efficiency and accuracy. Our results capture the liquid properties of P 2 Sn 5 at 1300 K, which is well above the melting temperature. The phase separation and crystallization are observed when P 2 Sn 5 liquid is cooled down below 832 and 505 K, respectively. The simulation results are in good agreement with the experimentally observed phase transformation behaviors and provide useful insights into the complex nucleation and crystallization process at the details of atomistic scale. Our work also demonstrated that ML interatomic potentials based on neural network deep learning are robust and capable of accurately describing the energetics and kinetics of complex materials through molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Method of information entropy for convergence assessment of molecular dynamics simulations

The lack of a reliable method to evaluate the convergence of molecular dynamics simulations has contributed to discrepancies in different areas of molecular dynamics. Here, the method of information entropy is introduced to molecular dynamics for stationarity assessment. The Shannon information entropy formalism is used to monitor the convergence of the atom motion to a steady state in a continuous spatial domain and is also used to assess the stationarity of calculated multidimensional fields such as the temperature field in a discrete spatial domain. It is demonstrated in this work that monitoring the information entropy of the atom position matrix provides a clear indicator of reaching steady state in radiation damage simulations, non-equilibrium molecular dynamics thermal conductivity computations, and simulations of Poiseuille and Couette flow in nanochannels. A main advantage of the present technique is that it is non-local and relies on fundamental quantities available in all molecular dynamics simulations. Unlike monitoring average temperature, the technique is applicable to simulations that conserve total energy such as reverse non-equilibrium molecular dynamics thermal conductivity computations and to simulations where energy dissipates through a boundary as in radiation damage simulations. The method is applied to simulations of iron using the Tersoff/ZBL splined potential, silicon using the Stillinger–Weber potential, and to Lennard–Jones fluid. Its applicability to both solids and fluids shows that the technique has potential for generalization to other areas in molecular dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

The selective heating effect of microwave irradiation on a binary mixture of water and polyethylene oxide: a molecular dynamics simulation approach

In this study, we investigate the molecular mechanisms of a microwave-driven selective heating process by performing molecular dynamics simulations for three different systems including pure water, pure polyethylene oxide (PEO), and water-PEO mixed systems in the presence of a microwave with two different intensities of electric field such as 0.001 V/Å -1 and 0.01 V/Å -1 at a frequency of 100 GHz. First, from performing molecular dynamics simulations of CO and CO 2 in the presence of the microwave, it is confirmed that the molecular dipole moment is responsible for the rotational motion induced by the oscillating electric field. Second, by analyzing the MD simulations of the pure water system, we discover that the dipole moment of water exhibits a time lag with respect to the microwave. During the heating process, however, the temperature, kinetic, and potential energies increase synchronously with the oscillating electric field of the microwave, showing that the heating of the water system is caused by the molecular reaction of water to the microwave. Comparing the water-PEO mixed system to the pure water and pure PEO systems, the water-PEO mixed system has a higher heating rate than the pure PEO system but a lower heating rate than the pure water system. Therefore, we conclude that heating the water-PEO mixed system is driven by water molecules selectively activated by microwave irradiation. Furthermore, we also calculate the diffusion coefficients of water molecules and PEO chains by describing their mean square displacements, demonstrating that the diffusion coefficients are increased in the presence of microwaves for both water and PEO in pure and mixed systems. Lastly, during the microwave heating process, the structures of the water-PEO mixed system are altered as a function of the intensity of electric field, which is mainly driven by the response of water molecules.

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

Cavity molecular dynamics simulations of vibrational polariton-enhanced molecular nonlinear absorption

We report recent experiments have observed that the chemical and photophysical properties of molecules can be modified inside an optical Fabry– Pérot microcavity under collective vibrational strong coupling (VSC) conditions, and such modification is currently not well understood by theory. In an effort to understand the origin of such cavity-induced phenomena, some recent studies have focused on the effect of the cavity environment on the nonlinear optical response of the molecular subsystem. Here, we use a recently proposed protocol for classical cavity molecular dynamics simulations to numerically investigate the linear and the nonlinear response of liquid carbon dioxide under such VSC conditions following an optical pulse excitation. We find that applying a strong pulse of excitation to the lower hybrid light–matter state, i.e., the lower polariton (LP), can lead to an overall molecular nonlinear absorption that is enhanced by up to two orders of magnitude relative to the excitation outside the cavity. This polariton-enhanced multiphoton absorption also causes an ultrashort LP lifetime (0.2 ps) under strong illumination. Unlike usual polariton relaxation processes—whereby polaritonic energy transfers directly to the manifold of singly excited vibrational dark states—under the present mechanism, the LP transfers energy directly to the manifold of higher vibrationally excited dark states; these highly excited dark states subsequently relax to the manifold of singly excited states with a lifetime of tens of ps. Because the present mechanism is generic in nature, we expect these numerical predictions to be experimentally observed in different molecular systems and in cavities with different volumes.

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

Molecular dynamics simulation of hydrodynamic transport coefficients in plasmas

Molecular dynamics simulations are used to calculate transport coefficients in a two-component plasma interacting through a repulsive Coulomb potential. The thermal conductivity, electrical conductivity, electrothermal coefficient, thermoelectric coefficient, and shear viscosity are computed using the Green–Kubo formalism over a broad range of Coulomb coupling strength, 0.01 ≤ Γ ≤ 140. Emphasis is placed on testing standard results of the Chapman–Enskog solution in the weakly coupled regime (Γ ≪ 1) using these first-principles simulations. As expected, the results show good agreement for Γ ≲ 0.1. However, this agreement is only possible if careful attention is paid to the definitions of linear constitutive relations in each of the theoretical models, a point that is often overlooked. For example, the standard Green–Kubo expression for thermal conductivity is a linear combination of thermal conductivity, electrothermal, and thermoelectric coefficients computed in the Chapman–Enskog formalism. Meaningful results for electrical conductivity are obtained over the full range of coupling strengths explored, but it is shown that potential and virial components of the other transport coefficients diverge in the strongly coupled regime (Γ ≫ 1). In this regime, only the kinetic components of the transport coefficients are meaningful for a classical plasma.

Electrical conductivity↗
DOE OSTI2025

Molecular Dynamics Simulations of a Liquid Metal Wetting Zirconia Suboxides

Molecular dynamics simulations were performed of a liquid metal (Ag) interacting with various zirconia suboxides to calculate the work of adhesion between the liquid metal and the suboxides. These simulations were then used to assess the impact of oxygen content on wetting. The results of this work show a wetting transition as oxygen content is reduced.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Calculating adsorption isotherms using the two-phase thermodynamic method and molecular dynamics simulations

We describe the calculation of adsorption isotherms from molecular dynamics simulations based on the two-phase thermodynamic (2PT) model. The 2PT model developed for bulk fluid phases treats the gas-like components as hard spheres (HSs), which correctly recovers the limiting behaviors of unconfined fluids. We showed that this treatment, however, does not always lead to the correct zero-loading behavior in strongly confining systems. For methane adsorption into zeolite MFI, the HS reference state underestimates entropy by up to 20% at low loadings and leads to an order-of-magnitude increase in the adsorption onset pressure. To fix these issues, we propose the use of ideal adsorbed gas (IAG) as the gas reference model, the properties of which can be computed using the Widom insertion method on an empty adsorbent. We further describe three routes to compute adsorption isotherms from the Helmholtz free energy at different loadings. Comparing against established Monte Carlo (MC) methods, we found that the adsorption isotherms obtained using the IAG reference state agrees to within 40%, which corresponds to deviations of <5% in adsorption free energy. The isotherms calculated using the HS reference state underestimate the adsorption uptake at low to medium loadings in strongly confining systems, but its accuracy improves at higher loadings and as the pore size increases relative to the sorbate diameter. The methods described here provide an alternative approach for computing adsorption isotherms when MC simulations in an open ensemble are undesirable and enable a direct comparison of computed adsorption thermodynamics with experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

MBX V1.2: Accelerating Data-Driven Many-Body Molecular Dynamics Simulations

The MBX software provides an advanced platform for molecular dynamics simulations, leveraging state-of-the-art MB-pol and MB-nrg data-driven many-body potential energy functions. Developed over the past decade, these potential energy functions integrate physics-based and machine-learned many-body terms trained on electronic structure data calculated at the "gold standard" coupled-cluster level of theory. Recent advancements in MBX have focused on optimizing its performance, resulting in the release of MBX v1.2. While the inherently many-body nature of MB-pol and MB-nrg ensures high accuracy, it poses computational challenges. MBX v1.2 addresses these challenges with significant performance improvements, including enhanced parallelism that fully harnesses the power of modern multicore CPUs. In conclusion, these advancements enable simulations on nanosecond time scales for condensed-phase systems, significantly expanding the scope of high-accuracy, predictive simulations of complex molecular systems powered by data-driven many-body potential energy functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Elastic Properties of Plasma-Exposed Tungsten Predicted by Molecular-Dynamics Simulations

We report results of systematic molecular-dynamics computations of the elastic properties of single-crystalline tungsten containing structural defects, voids and overpressurized He nanobubbles, related to plasma exposure of tungsten serving as a plasma- facing component (PFC) in nuclear fusion devices. Our computations reveal that the empty voids are centers of dilatation resulting in development of tensile stress in the tungsten matrix, whereas He-filled voids (nanobubbles) introduce compressive stress in the plasma-exposed tungsten. We find that the dependence of the elastic moduli of plasma-exposed tungsten, namely, the bulk, Young, and shear modulus, on its void fraction follows a universal exponential scaling relation. We also find that the elastic moduli of plasma-exposed tungsten soften substantially as a function of He content in the tungsten matrix, following an exponential scaling relation; this He-induced exponential softening is in addition to the softening caused in the matrix with increasing temperature. A systematic characterization of the dependence of the elastic moduli on the He bubble size reveals that He bubble growth affects significantly both the bulk modulus and the Poisson ratio of plasma-exposed tungsten, while its effect on the Young and shear moduli of the plasma-exposed material is weak. Our findings contribute directly to the development of a structure-properties database that is required for the predictive modeling of the dynamical response of PFCs in nuclear fusion devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effects of Surface Orientation and Termination Plane on Glass‐to‐Crystal Transformation of Lithium Disilicate by Molecular Dynamics Simulations

Glass‐to‐crystal transformation of lithium disilicate is studied using molecular dynamics simulations using an effective partial charge potential. The structural evolution of the interface between glassy and crystalline lithium disilicate is analyzed to simulate crystallization of glass on pre‐existing crystal seeds. Besides previously used atomic number density, the distribution of Q n species (Si tetrahedra with n bridging oxygen) is shown to be an effective parameter for following this transformation quantitatively. The early stages of crystal growth are significantly affected by the orientation and termination of the surface of adjacent crystal, as indicated by calculated atomic density, partial ordering, atomic segregation, and an increase in Q 3 concentration. In particular, under‐coordinated Si within the outer crystal layer is found to be most effective in transforming the amorphous structure toward crystallinity. The increase in Q 3 in the glass close to interface region most clearly shows the initial stage of lithium disilicate crystal growth.

Sun, Wei↗
DOE OSTI2023

Molecular dynamics simulation of Fe-Si alloys using a neural network machine learning potential

Interatomic potential development using machine learning (ML) approaches has attracted a lot of attention in recent years because these potentials can effectively describe the structural and dynamical properties of complex materials at the atomistic level. Here, in this work, we present the development of a neural network (NN) deep ML interatomic potential for Fe-Si alloys, and we demonstrate the effectiveness of the NN-ML potential in predicting the structures and energies of liquid and crystalline phases of Fe-Si alloys in comparison with the results from ab initio molecular dynamics simulations or experimental data. The developed NN-ML potential is also used to perform molecular dynamics simulations to study the structures of Fe-Si alloys with various compositions under rapid solidification conditions. The short-ranged orders in the rapidly solidified Fe-Si alloys are also analyzed by a cluster alignment method.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Near-surface damage and mixing in Si-Cl 2 -Ar atomic layer etching processes: Insights from molecular dynamics simulations

Silicon-chlorine-argon (Si-Cl 2 -Ar) atomic layer etching (ALE) is simulated using classical molecular dynamics (MD). The simulations provide a detailed view into the near-surface region during ALE processing. Bombardment of Ar + ions creates a mixed amorphous region that significantly differs from the picture of ideal ALE. There is also a significant change in the Si etch yield and the etch product distribution as a function of Ar + ion fluence. The Si etch yield is the highest at the beginning of the bombardment step but eventually decays to the physical sputtering yield. Atomic Cl and silicon chlorides are major etch products at the start of an ion bombardment step, but quickly decay. Atomic Si yields remain relatively constant as a function of Ar + ion fluence. As a result, a new schematic of Si-Cl 2 -Ar ALE is presented in order to emphasize the complex behavior observed in MD simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗