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At least 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Path-space variational inference for non-equilibrium coarse-grained systems

In this paper we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular simulations. The latter are ubiquitous in physicochemical and biological applications, where they are typically associated with coupling mechanisms, multi-physics and/or boundary conditions. In general the non-equilibrium steady states are not known explicitly as they do not necessarily have a Gibbs structure. The presented approach can compare microscopic behavior of molecular systems to parametric and non-parametric coarse-grained models using the relative entropy between distributions on the path space and setting up a corresponding path-space variational inference problem. The methods can become entirely data-driven when the microscopic dynamics are replaced with corresponding correlated data in the form of time series. Furthermore, we present connections and generalizations of force matching methods in coarse-graining with path-space information methods. We demonstrate the enhanced transferability of information-based parameterizations to different observables, at a specific thermodynamic point, due to information inequalities. We discuss methodological connections between information-based coarse-graining of molecular systems and variational inference methods primarily developed in the machine learning community. However, we note that the work presented here addresses variational inference for correlated time series due to the focus on dynamics. The applicability of the proposed methods is demonstrated on high-dimensional stochastic processes given by overdamped and driven Langevin dynamics of interacting particles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Coordination and Hydrolysis of Plutonium Ions in Aqueous Solution using Car-Parrinello Molecular Dynamics Free Energy Simulations

Car-Parrinello molecular dynamics (CPMD) simulations have been used to examine the hydration structures, coordination energetics and the first hydrolysis constants of Pu3+, Pu4+, PuO2+ and PuO22+ ions in aqueous solution at 300 K. The coordination numbers and structural properties of the first shell of these ions are in good agreement with available experimental estimates. The hexavalent PuO22+ species is coordinated to 5 aquo ligands while the pentavalent PuO2+ complex is coordinated to 4 aquo ligands. The Pu3+ and Pu4+ ions are both coordinated to 8 water molecules. The first hydrolysis constants obtained for Pu3+ and PuO22+ are 6.65 and 5.70 respectively, all within 0.3 pH units of the experimental values (6.90 and 5.50 respectively). The hydrolysis constant of Pu4+, 0.17, disagrees with the value of -0.60 in the most recent update of the Nuclear Energy Agency Thermochemical Database (NEA-TDB) but supports recent experimental findings. The hydrolysis constant of PuO2+, 9.51, supports the experimental results of Bennett et al. (Radiochim. Act. 1992, 56, 15). A correlation between the pKa of the first hydrolysis reaction and the effective charge of the plutonium center was found.

Actinide↗
DOE OSTI2023

Simulation study of the effects of polymer network dynamics and mesh confinement on the diffusion and structural relaxation of penetrants

The diffusion of small molecular penetrants through polymeric materials represents an important fundamental problem, relevant to the design of materials for applications such as coatings and membranes. Polymer networks hold promise in these applications because dramatic differences in molecular diffusion can result from subtle changes in the network structure. In this paper, we use molecular simulation to understand the role that cross-linked network polymers have in governing the molecular motion of penetrants. By considering the local, activated alpha relaxation time of the penetrant and its long-time diffusive dynamics, we can determine the relative importance of activated glassy dynamics on penetrants at the segmental scale vs entropic mesh confinement on penetrant diffusion. We vary several parameters, such as the cross-linking density, temperature, and penetrant size, to show that cross-links primarily affect molecular diffusion through the modification of the matrix glass transition, with local penetrant hopping at least partially coupled to the segmental relaxation of the polymer network. This coupling is very sensitive to the local activated segmental dynamics of the surrounding matrix, and we also show that penetrant transport is affected by dynamic heterogeneity at low temperatures. To contrast, only at high temperatures and for large penetrants or when the dynamic heterogeneity effect is weak, does the effect of mesh confinement become significant, even though penetrant diffusion more broadly empirically follows similar trends as established models of mesh confinement-based transport.

Chemistry↗
DOE OSTI2022

Ab initio molecular dynamics (AIMD) simulations of NaCl, UCl 3 molten salts

Ab initio molecular dynamics (AIMD) simulations are used to calculate select thermophysical and thermodynamic properties of NaCl, UCl and NaCl-UCl 3 molten salts. Following established approaches, the AIMD simulations include a model for Van der Waals interactions. The Langreth & Lundqvist (vDW-DF2), DFT-D3, and density-dependent energy correction (DFT-dDsC) dispersion models are first tested for molten NaCl in order to assess their accuracy for density and heat capacity predictions across a range of temperatures. Based on the NaCl results, the vdW-DF2 and DFT-dDsC methods are extended to the UCl 3 system and compared to available experimental data. Next, mixtures of NaCl-UCl 3 are investigated and analyzed with respect to the deviation from ideal solution behavior. For the DFT-dDsC simulations, density deviates by up to 2% from an ideal mixture, with the maximum occurring close to the eutectic composition. The mixing energy also deviates from an ideal solution and exhibits a minimum of about -0.074 to eV per formula unit, again close to the eutectic composition. Finally, the compressibility and species diffusivity of the pure and mixed salt systems are calculated. The diffusivities are slightly reduced in the mixed compared to the pure systems and the compressibilities loosely follow a linear correlation as a function of the UCl 3 composition. The trends observed for mixing properties are rationalized by correlating them to the coordination chemistry, which emphasizes the importance of maintaining the extended network formed by U and Cl ions as the NaCl concentration increases. The concentration at which breakdown of the extended network occurs, roughly coincides with the minimum of both the mixing energy and the deviation from ideal solution behavior for density.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Investigating the Accuracy of Water Models through the Van Hove Correlation Function

In this study, we present molecular-simulation-based calculations of the Van Hove correlation function (VHF) of water using multiple modeling approaches: classical molecular dynamics with simple three-site nonpolarizable models, with a polarizable model, and with a reactive force field; density functional tight-binding molecular dynamics; and ab initio molecular dynamics. Due to the many orders of magnitude difference in the computational cost of these approaches, we investigate how small and short the simulations can be while still yielding sufficiently accurate and interpretable results for the VHF. We investigate the accuracy of the different models by comparing them to recently published inelastic X-ray scattering measurements of the VHF. We find that all of the models exhibit qualitative agreement with the experiments, and in some models and for some properties, the agreement is quantitative. This work lays the foundation for future simulation approaches to calculating the VHF for aqueous solutions in bulk and under nanoconfinement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Machine learning the electric field response of condensed phase systems using perturbed neural network potentials

Abstract The interaction of condensed phase systems with external electric fields is of major importance in a myriad of processes in nature and technology, ranging from the field-directed motion of cells (galvanotaxis), to geochemistry and the formation of ice phases on planets, to field-directed chemical catalysis and energy storage and conversion systems including supercapacitors, batteries and solar cells. Molecular simulation in the presence of electric fields would give important atomistic insight into these processes but applications of the most accurate methods such as ab-initio molecular dynamics (AIMD) are limited in scope by their computational expense. Here we introduce Perturbed Neural Network Potential Molecular Dynamics (PNNP MD) to push back the accessible time and length scales of such simulations. We demonstrate that important dielectric properties of liquid water including the field-induced relaxation dynamics, the dielectric constant and the field-dependent IR spectrum can be machine learned up to surprisingly high field strengths of about 0.2 V Å −1 without loss in accuracy when compared to ab-initio molecular dynamics. This is remarkable because, in contrast to most previous approaches, the two neural networks on which PNNP MD is based are exclusively trained on molecular configurations sampled from zero-field MD simulations, demonstrating that the networks not only interpolate but also reliably extrapolate the field response. PNNP MD is based on rigorous theory yet it is simple, general, modular, and systematically improvable allowing us to obtain atomistic insight into the interaction of a wide range of condensed phase systems with external electric fields.

Science & Technology - Other Topics↗
DOE OSTI2018

How Useful Are Common Simulants of Chemical Warfare Agents at Predicting Adsorption Behavior?

We report that nanoporous materials such as metal–organic frameworks (MOFs) have attractive properties for selective capture of chemical warfare agents (CWAs). For obvious reasons, most research on adsorption of CWAs is performed with simulant molecules rather than real agents. This paper examines how effectively common CWA simulants mimic the adsorption properties of sarin and soman. To this end, we perform molecular simulations in the dilute adsorption limit for four simulants [dimethyl methylphosphonate (DMMP), diethyl chlorophosphate (DCP), diisopropyl fluorophosphate, and dimethyl p-nitrophenyl phosphate (DMNP)] and sarin and soman in a set of 2969 MOFs with experimentally known crystal structures. To establish the robustness of the conclusions with respect to the force field used in these simulations, each system was examined with two independent force fields, a “generic” force field and a density functional theory (DFT)-derived force field we established based on extensive dispersion-corrected DFT calculations of adsorption in the well-known MOF UiO-66. Our results show that when judging the performance of adsorbents using the heat of adsorption, DCP and DMMP are the best simulants for the adsorption of sarin, while DMNP is the best simulant for soman. The adsorption properties of DCP or DMMP show a strong correlation with sarin over a range of MOFs, but the correlation between DMNP and soman is considerably weaker. Finally, comparisons of results with both force fields indicate that our main conclusions are robust with respect to the force field used to define adsorbate–MOF interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Emergent facilitation and glassy dynamics in supercooled liquids

In supercooled liquids, dynamical facilitation refers to a phenomenon where microscopic motion begets further motion nearby, resulting in spatially heterogeneous dynamics. This is central to the glassy relaxation dynamics of such liquids, which show super-Arrhenius growth of relaxation timescales with decreasing temperature. Despite the importance of dynamical facilitation, there is no theoretical understanding of how facilitation emerges and impacts relaxation dynamics. Here, we present a theory that explains the microscopic origins of dynamical facilitation. We show that dynamics proceeds by localized bond-exchange events, also known as excitations, resulting in the accumulation of elastic stresses with which new excitations can interact. At low temperatures, these elastic interactions dominate and facilitate the creation of new excitations near prior excitations. Using the theory of linear elasticity and Markov processes, we simulate a model, which reproduces multiple aspects of glassy dynamics observed in experiments and molecular simulations, including the stretched exponential decay of relaxation functions, the super-Arrhenius behavior of relaxation timescales as well as their two-dimensional finite-size effects. The model also predicts the subdiffusive behavior of the mean squared displacement (MSD) on short, intermediate timescales. Furthermore, we derive the phonon contributions to diffusion and relaxation, which when combined with the excitation contributions produce the two-step relaxation processes, and the ballistic–subdiffusive–diffusive crossover MSD behaviors commonly found in supercooled liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Nuclear Quantum Effects in Water and Aqueous Systems: Experiment, Theory, and Current Challenges

Nuclear quantum effects influence the structure and dynamics of hydrogen bonded systems, such as water, which impacts their observed properties with widely varying magnitudes. This review highlights the recent significant developments in the experiment, theory and simulation of nuclear quantum effects in water. Novel experimental techniques, such as deep inelastic neutron scattering, now provide a detailed view of the role of nuclear quantum effects in water’s properties. These have been combined with theoretical developments such as the introduction of the competing quantum effects principle that allows the subtle interplay of water’s quantum effects and their manifestation in experimental observables to be explained. We discuss how this principle has recently been used to explain the apparent dichotomy in water’s isotope effects, which can range from very large to almost nonexistent depending on the property and conditions. We then review the latest major developments in simulation algorithms and theory that have enabled the efficient inclusion of nuclear quantum effects in molecular simulations, permitting their combination with on-the-fly evaluation of the potential energy surface using electronic structure theory. Finally, we identify current challenges and future opportunities in the area.

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

Toward Addressing the Challenge to Predict the Heat Capacities of RDX and HMX Energetic Materials

Availability of heat capacity as function of pressure and temperature is an essential prerequisite for development of a computational multiscale strategy capable to address the evolution of microstructure and energy release in advanced high energy density materials. In the case of 1,3,5-trinitro-1,3,5-triazinane (RDX) and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX) systems as two of the most studied energetic materials, there are substantial gaps in experimental data, with available heat capacities values distributed only in a region close to standard ambient conditions. In this study we demonstrate how these major experimental limitations can be addressed in the case of the RDX and HMX systems based on the combined use of classical and quantum mechanical calculations. We show that by considering ideal gas properties evaluated using quantum mechanical methods, and residual properties obtained from molecular simulations using fully flexible atomistic force field models, excellent agreement can be obtained for the predicted heat capacities to the most recent experimental values. An important advantage of the current computational methodology is that it allows evaluation of both constant-volume and constant-pressure heat capacities for a broad interval of temperatures and pressures, which encompasses solid and liquid phases conditions. In the case of the solid α and γ phases of RDX and the β phase of HMX, the predicted results follow closely both the available experimental data at standard ambient conditions and the results obtained using density functional theory calculations at high pressures, a regime where experimental data are not available. A perspective to expand the current methodology is also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Critical energy barrier for capillary condensation in mesopores: Hysteresis and reversibility

Capillary condensation in the regime of developing hysteresis occurs at a vapor pressure, P{sub cond}, that is less than that of the vapor-like spinodal. This is because the energy barrier for the vapor-liquid transition from a metastable state at P{sub cond} becomes equal to the energy fluctuation of the system; however, a detailed mechanism of the spontaneous transition has not been acquired even through extensive experimental and simulation studies. We therefore construct accurate atomistic silica mesopore models for MCM-41 and perform molecular simulations (gauge cell Monte Carlo and grand canonical Monte Carlo) for argon adsorption on the models at subcritical temperatures. A careful comparison between the simulation and experiment reveals that the energy barrier for the capillary condensation has a critical dimensionless value, W{sub c}{sup *} = 0.175, which corresponds to the thermal fluctuation of the system and depends neither on the mesopore size nor on the temperature. We show that the critical energy barrier W{sub c}{sup *} controls the capillary condensation pressure P{sub cond} and also determines a boundary between the reversible condensation/evaporation regime and the developing hysteresis regime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Renewable lubricants with tailored molecular architecture

We present a strategy to synthesize three types of renewable lubricant base oils with up to 90% yield using 2-alkylfurans, derived from nonfood biomass, and aldehydes, produced from natural oils or biomass through three chemistries: hydroxyalkylation/alkylation (HAA), HAA followed by hydrogenation, and HAA followed by hydrodeoxygenation. These molecules consist of (i) furan rings, (ii) saturated furan rings, and (iii) deoxygenated branched alkanes. The structures of these molecules can be tailored in terms of carbon number, branching length, distance between branches, and functional groups. The site-specific, energy-efficient C–C coupling chemistry in oxygenated biomass compounds, unmatched in current refineries, provides tailored structure and tunable properties. Molecular simulation demonstrates the ability to predict properties in agreement with experiments, proving the potential for molecular design.

09 BIOMASS FUELS↗
DOE OSTI2025

STEPs-SOL, a Peptoid Force Field Parameterization to Include Solvent Effects

As peptoids (N-substituted glycines) continue to gain popularity as a class of biomimetic polymers, the importance and demand for accurate force fields in molecular simulations also grow. Building on the vacuum-optimized Systematic and Extensible Force Field for Peptoids (STEPs) force field, here we present STEPs-SOL, a novel peptoid force field parametrization that effectively incorporates solvent effects to enhance the accuracy of peptoid simulations. The development of STEPs-SOL is based on the need for precise electrostatic modeling achieved through solvent-specific partial charge optimization. Here, our systematic approach significantly improves agreement with experimental measurements, reducing the mean absolute error in cis/trans ratio predictions (ΔG c/t ) by an average of 38% across multiple peptoid residues and solvent environments. This improved parametrization addresses computational challenges associated with nonbonded energies while maintaining a workflow that relies on high-level quantum mechanical data rather than depending solely on limited experimental equilibrium properties. By evaluating the effects of conformational bias in restrained electrostatic potential (RESP) charge generation and examining their impact on peptoid conformations in various solvents, we enhance our understanding of peptoid structural dynamics while providing a more accurate modeling framework.

force field↗
DOE OSTI2013

Analysis of Molecular Clusters in Simulations of Lithium-Ion Battery Electrolytes

Graph theoretic tools were used to identify and classify clusters of ions and solvent molecules in molecular dynamics simulations of lithium-ion battery electrolytes. Electrolytes composed of various concentrations of LiPF6 dissolved in ethylene carbonate (EC), dimethylene carbonate (DMC), or a 1:1 EC/DMC mixture were simulated at multiple temperatures using classical molecular dynamics. Contrary to Nernst–Einstein theory but consistent with experiment, pure DMC systems had the greatest diffusivity but the lowest conductivity. This disagreement with Nernst–Einstein theory is explained by the observed clustering behavior, which found that systems with pure EC as a solvent formed ion clusters with nonzero charge, whereas systems with pure DMC as a solvent formed primarily neutral clusters.

25 ENERGY STORAGE↗
DOE OSTI2024

KCl-UCl 3 molten salts investigated by Ab Initio Molecular Dynamics (AIMD) simulations: A comparative study with three dispersion models

Ab Initio Molecular Dynamics (AIMD) simulations are performed on molten KCl-UCl 3 salt mixtures to determine energies, heat capacities, and densities. The density-dependent energy correction (DFT-dDsC), Grimme et al.’s DFT-D3, and Langreth & Lundqvist (vdW-cx) models are used for dispersion forces and combined with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation potential with a Hubbard U param eter for the 5$f$ electrons of uranium. After validating predictions for the end-member systems to literature data, KCl-UCl 3 mixtures are studied at select temperatures. Densities and energies both deviate from ideal solution behavior, with the maximum deviation occurring around 36% UCl 3 for mixing energies and slightly lower (29% UCl 3 ) for densities. Compared to the NaCl-UCl 3 system, which was previously investigated using the same simulation methodologies, the KCl-UCl 3 density and mixing energy deviations from ideal solution behavior are larger by almost a factor of two. No deviation from ideal solution behavior for heat capacity was observed. The AIMD predictions for mixing energies and densities agree qualitatively with experimental data, though the spread in data obtained from the various dispersion force models utilized, measurements, and empirical estimates makes strong conclusions difficult. The dependence of thermodynamic and thermophysical properties on composition is correlated with the local chemistry of the solution phase, in particular, the tendency of UCl 3 to form network structures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

MPMC and MCMD: Free High-Performance Simulation Software for Atomistic Systems

Advancements in parallel computing and hardware have allowed computational exploration of chemical systems of interest with unprecendented accuracy and efficiency. The typical development of molecular simulation software is initially inspired by a particular scientific inquiry. The softwares presented herein, MPMC (Massively Parallel Monte Carlo) and MCMD (Monte Carlo/Molecular Dynamics) were born out of a pursuit to simulate condensed phase physical and chemical interactions in porous materials. MPMC first began in 2005 and has been used for dozens of published results in the literature but has not yet been introduced in a standalone paper. MCMD is a more recent expansion and re-write with some published work, focused on adding molecular dynamics algorithms for transport and other time-dependent properties of chemical systems. Each software functions as a standalone with some unique and other overlapping features. Here, a driving aim of this work is to consider periodic, long-range polarization effects in classical simulation, and both codes are optimized to perform such calculations. Sample results will be presented which highlight methodically that inclusion of explicit polarization produces simulation results with predictive power which in general are in greater agreement with experiment than non-polarizable analogous simulations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2000

Modeling Molecules

The molecule modeling method known as Multibody Order (N) Dynamics, or MBO(N)D, was developed by Moldyn, Inc. at Goddard Space Flight Center through funding provided by the SBIR program. The software can model the dynamics of molecules through technology which stimulates low-frequency molecular motions and properties, such as movements among a molecule's constituent parts. With MBO(N)D, a molecule is substructured into a set of interconnected rigid and flexible bodies. These bodies replace the computation burden of mapping individual atoms. Moldyn's technology cuts computation time while increasing accuracy. The MBO(N)D technology is available as Insight II 97.0 from Molecular Simulations, Inc. Currently the technology is used to account for forces on spacecraft parts and to perform molecular analyses for pharmaceutical purposes. It permits the solution of molecular dynamics problems on a moderate workstation, as opposed to on a supercomputer.

Source record↗
DOE OSTI2016

Designer interface peptide grafts target estrogen receptor alpha dimerization

The nuclear transcription factor estrogen receptor alpha (ERα), triggered by its cognate ligand estrogen, regulates a variety of cellular signaling events. ERα is expressed in 70% of breast cancers and is a widely validated target for anti-breast cancer drug discovery. Administration of anti-estrogen to block estrogen receptor activation is still a viable anti-breast cancer treatment option but anti-estrogen resistance has been a significant bottle-neck. Dimerization of estrogen receptor is required for ER activation. Blocking ERα dimerization is therefore a complementary and alternative strategy to combat anti-estrogen resistance. Dimer interface peptide “I-box” derived from ER residues 503–518 specifically blocks ER dimerization. Recently using a comprehensive molecular simulation we studied the interaction dynamics of ERα LBDs in a homo-dimer. Based on this study, we identified three interface recognition peptide motifs LDKITDT (ERα residues 479–485), LQQQHQRLAQ (residues 497–506), and LSHIRHMSNK (residues 511–520) and reported the suitability of using LQQQHQRLAQ (ER 497–506) as a template to design inhibitors of ERα dimerization. Stability and self-aggregation of peptide based therapeutics poses a significant bottle-neck to proceed further. In this study utilizing peptide grafted to preserve their pharmacophoric recognition motif and assessed their stability and potential to block ERα mediated activity in silico and in vitro. The Grafted peptides blocked ERα mediated cell proliferation and viability of breast cancer cells but did not alter their apoptotic fate. We believe the structural clues identified in this study can be used to identify novel peptidometics and small molecules that specifically target ER dimer interface generating a new breed of anti-cancer agents. - Highlights: • Designer peptide grafts retain core molecular recognition motif during MD simulations. • Designer peptide grafts with Poly-ALA helix form stable complexes with estrogen receptor in silico. • Inhibitor peptides significantly decrease estrogen induced cell proliferation of ER positive breast cancer cells in vitro.

60 APPLIED LIFE SCIENCES↗