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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Soil Organic Matter (SOM): Molecular Simulations

Molecular simulation is a powerful tool used to gain an atomistic, molecular, and nanoscale level understanding of the structure, dynamics, and interactions from adsorption on minerals and assembly in aggregates of soil organic matter (SOM). Given the importance of SOM fate and persistence in soils and the current knowledge gaps, applications of atomistic scale simulations to study the complex compounds in SOM and their interactions in self-assembled aggregates composed of different organic matter compounds and with mineral surfaces of different types common in soils are few and far between. Here, we describe various molecular simulation methods that are currently in use in various areas and applicable to SOM research, followed by a brief survey of specific applications to SOM research and an illustration with our own recent efforts in this area. We conclude with an outlook and the challenges for future research in this area.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2016

The structure of liquid water up to 360 MPa from x-ray diffraction measurements using a high Q-range and from molecular simulation

X-ray diffraction measurements of liquid water are reported at pressures up to 360 MPa corresponding to a density of 0.0373 molecules per Å{sup 3}. The measurements were conducted at a spatial resolution corresponding to Q{sub max} = 16 Å{sup −1}. The method of data analysis and measurement in this study follows the earlier benchmark results reported for water under ambient conditions having a density of 0.0333 molecules per Å{sup 3} and Q{sub max} = 20 Å{sup −1} [J. Chem. Phys. 138, 074506 (2013)] and at 70 °C having a density of 0.0327 molecules per Å{sup 3} and Q{sub max} = 20 Å{sup −1} [J. Chem. Phys. 141, 214507 (2014)]. The structure of water is very different at these three different T and P state points and thus they provide the basis for evaluating the fidelity of molecular simulation. Measurements show that at 360 MPa, the 4 waters residing in the region between 2.3 and 3 Å are nearly unchanged: the peak position, shape, and coordination number are nearly identical to their values under ambient conditions. However, in the region above 3 Å, large structural changes occur with the collapse of the well-defined 2nd shell and shifting of higher shells to shorter distances. The measured structure is compared to simulated structure using intermolecular potentials described by both first-principles methods (revPBE-D3) and classical potentials (TIP4P/2005, MB-pol, and mW). The DFT-based, revPBE-D3, method and the many-body empirical potential model, MB-pol, provide the best overall representation of the ambient, high-temperature, and high-pressure data. The revPBE-D3, MB-pol, and the TIP4P/2005 models capture the densification mechanism, whereby the non-bonded 5th nearest neighbor molecule, which partially encroaches the 1st shell at ambient pressure, is pushed further into the local tetrahedral arrangement at higher pressures by the more distant molecules filling the void space in the network between the 1st and 2nd shells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

A coarse-graining approach for molecular simulation that retains the dynamics of the all-atom reference system by implementing hydrodynamic interactions

We report on a new approach for deriving coarse-grained intermolecular forces that retains the frictional contribution that is often discarded by conventional coarse-graining methods. The approach is tested for water and an aqueous glucose solution, and the results from the new implementation for coarse-grained molecular dynamics simulation show remarkable agreement with the dynamics obtained from reference all-atom simulations. The agreement between the structural properties observed in the coarse-grained and all-atom simulations is also preserved. We discuss how this approach may be applied broadly to any existing coarse-graining method where the coarse-grained models are rigorously derived from all-atom reference systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Extending molecular simulation time scales: Parallel in time integrations for high-level quantum chemistry and complex force representations

Parallel in time simulation algorithms are presented and applied to conventional molecular dynamics (MD) and ab initio molecular dynamics (AIMD) models of realistic complexity. Assuming that a forward time integrator, f (e.g., Verlet algorithm), is available to propagate the system from time t{sub i} (trajectory positions and velocities x{sub i} = (r{sub i}, v{sub i})) to time t{sub i+1} (x{sub i+1}) by x{sub i+1} = f{sub i}(x{sub i}), the dynamics problem spanning an interval from t{sub 0}…t{sub M} can be transformed into a root finding problem, F(X) = [x{sub i} − f(x{sub (i−1})]{sub i} {sub =1,M} = 0, for the trajectory variables. The root finding problem is solved using a variety of root finding techniques, including quasi-Newton and preconditioned quasi-Newton schemes that are all unconditionally convergent. The algorithms are parallelized by assigning a processor to each time-step entry in the columns of F(X). The relation of this approach to other recently proposed parallel in time methods is discussed, and the effectiveness of various approaches to solving the root finding problem is tested. We demonstrate that more efficient dynamical models based on simplified interactions or coarsening time-steps provide preconditioners for the root finding problem. However, for MD and AIMD simulations, such preconditioners are not required to obtain reasonable convergence and their cost must be considered in the performance of the algorithm. The parallel in time algorithms developed are tested by applying them to MD and AIMD simulations of size and complexity similar to those encountered in present day applications. These include a 1000 Si atom MD simulation using Stillinger-Weber potentials, and a HCl + 4H{sub 2}O AIMD simulation at the MP2 level. The maximum speedup ((serial execution time)/(parallel execution time) ) obtained by parallelizing the Stillinger-Weber MD simulation was nearly 3.0. For the AIMD MP2 simulations, the algorithms achieved speedups of up to 14.3. The parallel in time algorithms can be implemented in a distributed computing environment using very slow transmission control protocol/Internet protocol networks. Scripts written in Python that make calls to a precompiled quantum chemistry package (NWChem) are demonstrated to provide an actual speedup of 8.2 for a 2.5 ps AIMD simulation of HCl + 4H{sub 2}O at the MP2/6-31G* level. Implemented in this way these algorithms can be used for long time high-level AIMD simulations at a modest cost using machines connected by very slow networks such as WiFi, or in different time zones connected by the Internet. The algorithms can also be used with programs that are already parallel. Using these algorithms, we are able to reduce the cost of a MP2/6-311++G(2d,2p) simulation that had reached its maximum possible speedup in the parallelization of the electronic structure calculation from 32 s/time step to 6.9 s/time step.

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

Energetics and the Role of Defects in Fe(II)-Catalyzed Goethite Recrystallization from Molecular Simulations

Goethite is one of the most stable and common iron (III) minerals at the Earth’s near surface. However, recent isotope- tracer studies suggest that goethite continuously recrystallizes in the presence of aqueous Fe(II) ions. Such studies often indicate the presence of two regimes of atom exchange kinetics, a rapid stage assigned to reactive defect sites initially available at particle surfaces, followed by slower continuous exchange. An autocatalytic solid-state electron conduction model coupling Fe(II) oxidative adsorption to its reductive release at spatially distinct sites has been proposed, but the thermodynamic driving force has yet to be pinpointed. Here, using a novel hybrid/reactive molecular simulation method, for goethite (110) surfaces at circumneutral pH, we rigorously tested whether surface free energy minimization, including examining the role of structural defects, is sufficient to overcome the activation energy for interfacial electron transfer and conduction. The simulations quantitatively show that: (i). on smooth stable surfaces the available thermal energy at dynamic equilibrium is sufficient to sustain the slow continuous regime of atom exchange kinetics via short intra-surface electron conduction pathways of 1-2 nm (3-5 Fe site hops); (ii). in this slower regime, the model converges to atom exchange kinetics of 10 -5 Fe s -1 cm -2 , a rate recently deduced from stochastic modeling of experimental data and linked to the reductive dissolution rate of goethite; (iii). the driving force for initially rough defective goethite surfaces to smoothen can accelerate atom exchange to an extent quantitatively consistent with that observed in the initial rapid stage, in this case accessing conduction pathways of up to 8 nm. The findings suggest that the interaction of Fe(II) with initially defective goethite surfaces can drive, by the conduction model, atom exchange that is capable of recrystallizing the interiors of nanoscale particles, and that, closer to equilibrium on smooth surfaces, slower atom exchange continues in perpetuity but likely involving only the outermost atomic layers.

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

Predicting Reaction Products and Automating Reactive Trajectory Characterization in Molecular Simulations with Support Vector Machines

A machine learning-based methodology for the prediction of chemical reaction products, along with automated elucidation of mechanistic details via phase space analysis of reactive trajectories, is introduced using low-dimensional heuristic models and then applied to ab initio computer simulations of the photodissociation of acetaldehyde, an important chemical system in atmospheric chemistry. Our method is centered around training Support Vector Machines (SVMs) to identify optimal separatrices that delineate the regions of phase space that lead to different chemical reaction products. In contrast to the more common “black box” type machine learning methodologies for analyzing chemical simulation data, this SVM-based methodology allows for mechanistic insight to be gleaned from further analysis of the positioning of the phase space points used to train the SVM with respect to the separatrices. For example, a pair of phase space points that are in close proximity to each other but on opposite sides of a separatrix may be situated on opposite sides of a transition state, while phase space points occurring early in a simulation that are distant from a separatrix are likely to belong to trajectories that are highly biased toward the product state associated with the basin of attraction to which they belong. In addition to inferring mechanistic details about multiple-pathway chemical reactions, our method can also be used to increase reactive trajectory sampling efficiency in molecular simulations via rejection sampling, with trajectories leading to undesired product states being identified and terminated early in the simulation rather than being carried to completion.

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

Molecular Simulations Probing the Adsorption and Diffusion of Ammonia, Nitrogen, Hydrogen, and Their Mixtures in Bulk MFI Zeolite and MFI Nanosheets at High Temperature and Pressure

Recent advances in the synthesis of MFI zeolite nanosheets have led to highly selective membranes that are promising candidates for small-scale ammonia separation from ammonia/nitrogen/hydrogen mixtures in distributed green ammonia production plants. Using force-field-based molecular simulations, we evaluate the performance of bulk all-silica MFI zeolite and a 3 nm thick all-silica MFI nanosheet for ammonia/nitrogen/hydrogen separations at moderate temperature and pressure conditions (T = 373 K, p = 5 bar) as well as conditions relevant for a membrane-based reactor–separator process (T = 523 or 623 K, p = 80 bar). Isobaric–isothermal Gibbs ensemble Monte Carlo (GEMC) simulations were carried out to understand the selective adsorption behavior for these mixtures. Molecular dynamics simulations in the canonical ensemble were performed to examine the transport behavior of ammonia in a mixture with nitrogen or hydrogen at loadings obtained from the GEMC simulations. Our results show that both bulk MFI and the nanosheet with explicit surface silanols are highly selective toward ammonia adsorption, but the adsorption selectivity decreases by factors of 4 and 10 for ammonia/nitrogen and ammonia/hydrogen mixtures as the temperature is increased from 373 to 623 K. Conversely, the diffusion selectivities toward ammonia are more favorable at process-relevant temperatures and for the MFI nanosheet. Here, at T = 523 K and p = 80 bar, our simulations predict overall separation factors of 3.8 ± 0.2 and 4.5 ± 0.3 for ammonia/nitrogen and ammonia/hydrogen mixtures, respectively, in the bulk MFI zeolite, and separation factors of 8.6 ± 0.4 and 12.5 ± 0.8, respectively, for the MFI nanosheet.

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

Molecular Simulation Models of Carbon Dioxide Intercalation in Hydrated Sodium Montmorillonite

Carbon capture and storage (CCS) technologies provide effective options for reducing carbon dioxide (CO 2 ) emissions and mitigating global climate change. Geologic CO 2 storage involves the injection of supercritical CO 2 into deep geologic formations overlain by sealing formations and geologic traps that prevent the CO 2 from escaping. The ability of seals to retain injected CO 2 depends on their permeability and geomechanical property evolution. Caprocks are often comprised of shale or mudstone enriched with swelling clay minerals that can expand or contract upon interaction with CO 2 . Intercalation of CO 2 into interlayer of swelling clay causes evolution of the geomechanical stress and can promote fracture formation. The interlayer of expanded clay provides ample space for additional permanent CO 2 storage and its subsequent transformation into carbonates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Molecular simulation of thermodynamic and transport properties for the H{sub 2}O+NaCl system

Molecular dynamics and Monte Carlo simulations have been carried out to obtain thermodynamic and transport properties of the binary mixture H{sub 2}O+NaCl at temperatures from T = 298 to 473 K. In particular, vapor pressures, liquid densities, viscosities, and vapor-liquid interfacial tensions have been obtained as functions of pressure and salt concentration. Several previously proposed fixed-point-charge models that include either Lennard-Jones (LJ) 12-6 or exponential-6 (Exp6) functional forms to describe non-Coulombic interactions were studied. In particular, for water we used the SPC and SPC/E (LJ) models in their rigid forms, a semiflexible version of the SPC/E (LJ) model, and the Errington-Panagiotopoulos Exp6 model; for NaCl, we used the Smith-Dang and Joung-Cheatham (LJ) parameterizations as well as the Tosi-Fumi (Exp6) model. While none of the model combinations are able to reproduce simultaneously all target properties, vapor pressures are well represented using the SPC plus Joung-Cheathem model combination, and all LJ models do well for the liquid density, with the semiflexible SPC/E plus Joung-Cheatham combination being the most accurate. For viscosities, the combination of rigid SPC/E plus Smith-Dang is the best alternative. For interfacial tensions, the combination of the semiflexible SPC/E plus Smith-Dang or Joung-Cheatham gives the best results. Inclusion of water flexibility improves the mixture densities and interfacial tensions, at the cost of larger deviations for the vapor pressures and viscosities. The Exp6 water plus Tosi-Fumi salt model combination was found to perform poorly for most of the properties of interest, in particular being unable to describe the experimental trend for the vapor pressure as a function of salt concentration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Molecular simulation of structure and diffusion at smectite-water interfaces: Using expanded clay interlayers as model nanopores

In geologic settings relevant to a number of extraction and potential sequestration processes, nanopores bounded by clay mineral surfaces play a critical role in the transport of aqueous species. Solution structure and dynamics at clay–water interfaces are quite different from their bulk values, and the spatial extent of this disruption remains a topic of current interest. We have used molecular dynamics simulations to investigate the structure and diffusion of aqueous solutions in clay nanopores approximately 6 nm thick, comparing the effect of clay composition with model Na-hectorite and Na-montmorillonite surfaces. In addition to structural properties at the interface, water and ion diffusion coefficients were calculated within each aqueous layer at the interface, as well as in the central bulk-like region of the nanopore. The results show similar solution structure and diffusion properties at each surface, with subtle differences in sodium adsorption complexes and water structure in the first adsorbed layer due to different arrangements of layer hydroxyl groups in the two clay models. Interestingly, the extent of surface disruption on bulk-like solution structure and diffusion extends to only a few water layers. Additionally, a comparison of sodium ion residence times confirms similar behavior of inner-sphere and outer-sphere surface complexes at each clay surface, but ~1% of sodium ions adsorb in ditrigonal cavities on the hectorite surface. Thus, the presence of these anhydrous ions is consistent with highly immobile anhydrous ions seen in previous nuclear magnetic resonance spectroscopic measurements of hectorite pastes.

36 MATERIALS SCIENCE↗