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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Shock compression of crystalline TeO 2 to the high-pressure fluid regime: Insights from ab initio molecular dynamics simulations

The shock response of fully-dense and porous crystalline tellurium dioxide (TeO 2 ⁠) to the high-pressure and high-temperature fluid regime was investigated within the framework of density functional theory with Mermin’s generalization to finite temperatures. The principal and porous shock Hugoniot curves were predicted from canonical ab initio molecular dynamics (AIMD) simulations, with the phase space sampled along isotherms up to 80 000 K, for densities ranging from ρ = 3 to 17 g/cm 3 . The polymorphs investigated are α-TeO 2 paratellurite (⁠P4 1 2 1 2), TeO 2 cotunnite (⁠Pnma⁠), and TeO 2 post-cotunnite (⁠P2 1 /m⁠). Based on the discontinuity found in the calculated U s – u p slope of TeO 2 post-cotunnite at a shock velocity of U s ≃ 8.35km/s and a particle velocity of u p ≃ 3.64 km/s, the shock melting temperature and pressure are predicted to be ≃ 6500 K and ≃ 170 GPa. Results from the AIMD simulations are in line with the static compression data of TeO 2 paratellurite and cotunnite, and with the recent shock Hugoniot data for single-crystal α- TeO 2 for pressures up to 85 GPa, obtained using the inclined-mirror method and the velocity interferometer system for any reflector combined with powder gun and two-stage light-gas gun.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Ab initio study of the structure and properties of amorphous silicon hydride from accelerated molecular dynamics simulations

This paper presents a large-scale ab initio simulation study of amorphous silicon hydride (a-Si 1-x H x ) with an emphasis on the structure and properties of the material across a range of hydrogen concentration by combining accelerated molecular dynamics (MD) simulations with first-principles density-functional calculations. The accelerated MD scheme relied on classical metadynamics, which enabled the development of 2500+ high-quality structural models of a-Si 1-x H x , with system sizes ranging from 150 to 6000 atoms and hydrogen concentrations vary from 6 to 20 at. %. The resulting amorphous networks were found to be completely free from any coordination defects and that they all exhibited a pristine band-gap in their electronic spectrum. The microstructural properties of hydrogen distributions were examined with an emphasis on the presence of isolated and clustered environments of hydrogen atoms. The results were compared with experimental data obtained from X-ray diffraction, infrared spectroscopy and nuclear magnetic resonance studies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ab initio study of the structure and properties of amorphous silicon hydride from accelerated molecular dynamics simulations

This paper presents a large-scale ab initio simulation study of amorphous silicon hydride (a-Si 1-x H x ) with an emphasis on the structure and properties of the material across a range of hydrogen concentration by combining accelerated molecular dynamics (MD) simulations with first-principles density-functional calculations. The accelerated MD scheme relied on classical metadynamics, which enabled the development of 2600+ high-quality structural models of a-Si 1-x H x , with system sizes ranging from 150 to 6,000 atoms and hydrogen concentrations vary from 6 to 20 at. %. The resulting amorphous networks were found to be completely free from any coordination defects and that they all exhibited a pristine band-gap in their electronic spectrum. The microstructural properties of hydrogen distributions were examined with great emphasis on the presence of isolated and clustered environments of hydrogen atoms. The results were compared with a suite of experimental data obtained from x-ray diffraction, infrared spectroscopy, spectroscopic ellipsometry and nuclear magnetic resonance studies.

36 MATERIALS SCIENCE↗
NASA NTRS2016

Evaluation of Methods for Molecular Dynamics Simulation of Ionic Liquid Electric Double Layers

We investigate how systematically increasing the accuracy of various molecular dynamics modeling techniques influences the structure and capacitance of ionic liquid electric double layers (EDLs). The techniques probed concern long-range electrostatic interactions, electrode charging (constant charge versus constant potential conditions), and electrolyte polarizability. Our simulations are performed on a quasi-two-dimensional, or slab-like, model capacitor, which is composed of a polarizable ionic liquid electrolyte, [EMIM][BF4], interfaced between two graphite electrodes. To ensure an accurate representation of EDL differential capacitance, we derive new fluctuation formulas that resolve the differential capacitance as a function of electrode charge or electrode potential. The magnitude of differential capacitance shows sensitivity to different long-range electrostatic summation techniques, while the shape of differential capacitance is affected by charging technique and the polarizability of the electrolyte. For long-range summation techniques, errors in magnitude can be mitigated by employing two-dimensional or corrected three dimensional electrostatic summations, which lead to electric fields that conform to those of a classical electrostatic parallel plate capacitor. With respect to charging, the changes in shape are a result of ions in the Stern layer (i.e. ions at the electrode surface) having a higher electrostatic affinity to constant potential electrodes than to constant charge electrodes. For electrolyte polarizability, shape changes originate from induced dipoles that soften the interaction of Stern layer ions with the electrode. The softening is traced to ion correlations vertical to the electrode surface that induce dipoles that oppose double layer formation. In general, our analysis indicates an accuracy dependent differential capacitance profile that transitions from the characteristic camel shape with coarser representations to a more diffuse profile with finer representations.

Haskins, Justin B.↗
DOE OSTI2022

Predicting initial dissolution rates using structural features from molecular dynamics simulations

Predicting chemical durability of glass materials is important for various applications from daily life such as drink glass and kitchen ware to advanced technologies such as nuclear waste disposal and biomedicine. In this work, we explored prediction of initial dissolution rate through structural features from molecular dynamics (MD) simulations for a wide range of glass compositions (total 28) including borosilicate and aluminosilicate glasses, ZrO 2 -containing and V 2 O 5 -containing boroaluminosilicate glasses. The initial dissolution rates (r 0 ) measured experimentally at 90 °C with varying solution conditions were correlated with structural features (e.g., polyhedral linkages and non-bridging oxygen species) obtained from MD simulations, either from this study or from literature. Since hydrolysis of the glass network through breaking of the network former linkages (e.g., Si-O-Si, Si-O-Al, etc.) is a critical step of network glass dissolution, the statistics of these linkages obtained from MD were correlated to r0 through linear regression, where the coefficient of determination (R 2 ) and root mean square error are found to be 0.949 and 0.681, respectively. This model was compared and discussed with existing models developed by various approaches including machine learning, the kinetic rate equation, topological constraint theory, and other descriptors from MD simulations. The discussion provides insights on future model improvements to predict glass dissolution. In addition, the impact of V 2 O 5 on the glass dissolution was examined in detail, implicating that the impact is not the same across all glass compositions and test conditions.

36 MATERIALS SCIENCE↗
NASA NTRS2019

Molecular Dynamics Simulations of Silicon Carbide, Boron Nitride and Silicon for Ceramic Matrix Composite Applications

A comprehensive computational molecular dynamics study is presented for crystalline α-SiC (6H, 4H, and 2H SiC), β-SiC (3C SiC), layered boron nitride, amorphous boron nitride and silicon, the constituent materials for high-temperature SiC/SiC compositions. Large-scale Atomic/Molecular Parallel Simulator software package was used. The Tersoff Potential force field was utilized to evaluate their mechanical characteristics of most of the materials, and the Reax force field was used to model silicon when the Tersoff Potential did not provide accurate results. Their mechanical behaviors were evaluated at a strain rate of 10(exp 7)/s and the results agree with the experimental data in the literature. The results are foundational for linking constituent behavior to composite performance, particularly when test data is unavailable or suspect.

Aluko, Olanrewaju↗
DOE OSTI2021

Investigations of water/oxide interfaces by molecular dynamics simulations

Water/oxide interfaces are ubiquitous on earth and show significant influence on many chemical processes. For example, understanding water and solute adsorption as well as catalytic water splitting can help build better fuel cells and solar cells to overcome our looming energy crisis; the interaction between biomolecules and water/oxide interfaces is one hypothesis to explain the origin of life. However, knowledge in this area is still limited due to the difficulty of studying water/solid interfaces. As a result, research using increasingly sophisticated experimental techniques and computational simulations has been carried out in recent years. Although it is difficult for experimental techniques to provide detailed microscopic structural information, molecular dynamics (MD) simulations have satisfactory performance. In this report, we discuss classical and ab initio MD simulations of water/oxide interfaces. Generally, we are interested in the following questions: How do solid surfaces perturb interfacial water structure? How do interfacial water molecules and adsorbed solutes affect solid surfaces and how do interfacial environments affect solvent and solute behavior? Finally, we discuss progress in the application of neural network potential based MD simulations, which offer a promising future because this approach has already enabled ab initio level accuracy for very large systems and long trajectories.

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

Solvent-induced membrane stress in biofuel production: molecular insights from small-angle scattering and all-atom molecular dynamics simulations

The disruptive effect of organic solvents on microbial membranes represents a significant challenge to the economical production of green fuels and value-added chemicals from lignocellulosic feedstocks. One route to overcoming this challenge is to engineer microbes with membranes capable of resisting organic solvent stresses. In this regard, it is useful to understand the mechanisms by which organic solvents disrupt typical biomembranes. In this study, molecular dynamics (MD) simulation, complemented by small-angle X-ray and neutron scattering (SANS/SAXS), provide a molecular-scale view of the disruption of a microbial model membrane by 1-butanol and tetrahydrofuran (THF), two common water–organic cosolvent mixtures of importance in biofuel production. Solvent interactions at the interface between the head-group and fatty acid tail regions lead to more dramatic membrane changes than interactions solely at the head-groups or tails. Although both organic solvents are found to partition into the membrane, the depth of solvent penetration into the membrane is quite different. Specifically, 1-butanol localizes near the interface between the lipid heads and tails at low concentrations, but partitions into both the head and tail regions at high concentrations. In contrast, THF, overall, partitions less than 1-butanol and prefers the lipid tail regions. Importantly, the presence of 1-butanol near the head/tail interface introduces drastic membrane changes not seen with THF. The organic solvent interactions with the lipids lead to membrane thinning and fluidization, but more so for 1-butanol than for THF. These results suggest that an aim for the future engineering of robust membranes could be to design lipid head groups that reduce the accumulation of organic solvents at the head–tail interface and that rational designs need also be cognizant of the different solvent-specific mechanisms responsible for membrane disruption.

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

Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning

Accurately predicting small molecule partitioning and hydrophobicity is critical in the drug discovery process. There are many heterogeneous chemical environments within a cell and entire human body. For example, drugs must be able to cross the hydrophobic cellular membrane to reach their intracellular targets, and hydrophobicity is an important driving force for drug–protein binding. Atomistic molecular dynamics (MD) simulations are routinely used to calculate free energies of small molecules binding to proteins, crossing lipid membranes, and solvation but are computationally expensive. Machine learning (ML) and empirical methods are also used throughout drug discovery but rely on experimental data, limiting the domain of applicability. We present atomistic MD simulations calculating 15,000 small molecule free energies of transfer from water to cyclohexane. This large data set is used to train ML models that predict the free energies of transfer. We show that a spatial graph neural network model achieves the highest accuracy, followed closely by a 3D-convolutional neural network, and shallow learning based on the chemical fingerprint is significantly less accurate. A mean absolute error of ~4 kJ/mol compared to the MD calculations was achieved for our best ML model. We also show that including data from the MD simulation improves the predictions, tests the transferability of each model to a diverse set of molecules, and show multitask learning improves the predictions. This work provides insight into the hydrophobicity of small molecules and ML cheminformatics modeling, and our data set will be useful for designing and testing future ML cheminformatics methods.

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

All-Atom Molecular Dynamics Simulations of Cationic Polyelectrolyte Brushes in the Presence of Halide Counterions

Understanding the response of the charged polyelectrolyte (PE) brushes and brush-supported water and ions to the changes in the nature of screening counterions is significant in developing strategies for utilizing PE brushes in various applications. In this paper, we employ all-atom molecular dynamics (MD) simulations for studying the behavior of cationic [poly(2-(methacryloyloxy)ethyl) trimethylammonium] (PMETA) brushes and brush-supported water and ions in the presence of different halide (X: I – , Br – , Cl – , and F – ) screening counterions. We find that despite the F– ion having the largest charge density, the extent of binding of the counterions on the PMETAX brushes varies as I – > Br – > Cl – > F – , leading to PMETAX brush height being least with I– counterions and greatest with F – counterions. This trend in the binding of the halide ions matches the previous experimental result and can be explained by identifying the chaotropic nature of the I – and Br – ions that promote a disruption of water structure and a more favorable binding of the ions to the polymer chains. Such a binding trend also ensures that the order of the water molecules around the PMETAX chains or the counterions as well as the number of water–water hydrogen bonds inside the brush layer increases in the following order of the counterion-specific PMETAX brushes: F – > Cl – > Br – > I – . Furthermore, halide-ion-PMETAX-chain binding takes place via both interchain and intrachain bridging: intrachain bridging dominates for the case of counterions that show enhanced binding (I – and Br – ), while interchain bridging is more favored for the case of counterions that show weakened binding (F – and Cl – ). Also, a greater degree of intrachain bridging leads to greater compressibility and flexibility of the brush layer. Lastly, we show that the mobility of the halide ions follows a nonmonotonic trend with the charge density: the mobility decreases as I – < Br – < Cl – (as their binding to the PMETAX chains varies as I – > Br – > Cl – ), but the mobility of F – ions is in between that of I – and Br – ions. We argue that the strongly attached hydration layer and the ensuing friction inside the brush layer lead to such a reduced mobility of the F – ions.

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

Atomic scale etching of diamond: insights from molecular dynamics simulations

Diamond is a promising material for multiple applications in quantum information processing and sensing as well as applications in microelectronics. However, diamond devices can be limited by surface defects that compromise charge stability and spin coherence, among others. Improved strategies in plasma etching of diamond could play an important role in minimizing or eliminating these defects. In this work, we explore plasma-assisted atomic scale etching of diamond using argon ions (Ar + ), hydrogen ions (H + ) and hydrogen atoms (H). We employ classical molecular dynamics (MD) simulations and test several interatomic potentials based on the Reactive Empirical Bond Order (REBO) form with comparisons to a variety of published experimental results. We performed MD simulations of low-energy hydrogen ($\leqslant$50 eV) and argon ( $\leqslant$200 eV) ion bombardment of diamond surfaces. Ar + bombardment can be used to locally smooth initially rough diamond surfaces via the formation of an amorphous C layer, the thickness of which increases with argon ion energy. Subsequent exposure with hydrogen ions (or fast neutrals) will selectively etch this amorphous C layer, leaving the underlying diamond layer mostly intact if the H energy is maintained below about 10 eV. The simulations suggest that combining Ar + smoothing with selective, near threshold energy H removal of amorphous C can be an effective strategy for diamond surface engineering, leading to more reliable and sensitive diamond color center devices.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Accelerated Sequence Design of Star Block Copolymers: An Unbiased Exploration Strategy via Fusion of Molecular Dynamics Simulations and Machine Learning

Star block copolymers (s-BCPs) have potential applications as novel surfactants or amphiphiles for emulsification, compatibilization, chemical transformations, and separations. s-BCPs have chain architectures where three or more linear diblock copolymer arms comprised of two chemically distinct linear polymers, e.g., solvophobic and solvophilic chains, are covalently joined at one point. The chemical composition of each of the subunit polymer chains comprising the arms, their molecular weights, and the number of arms can be varied to tailor the surface and interfacial activity of these architecturally unique molecules. Further, this makes identification of the optimal s-BCP design nontrivial as the total number of plausible s-BCP architectures is experimentally or computationally intractable. In this work, we use molecular dynamics (MD) simulations coupled with a reinforcement learning-based Monte Carlo tree search (MCTS) to identify s-BCP designs that minimize the interfacial tension between polar and nonpolar solvents. We first validate the MCTS approach for the design of small- and medium-sized s-BCPs and then use it to efficiently identify sequences of copolymer blocks for large-sized s-BCPs. The structural origins of interfacial tension in these systems are also identified by using the configurations obtained from MD simulations. Chemical insights into the arrangement of copolymer blocks that promote lower interfacial tension were mined using machine learning (ML) techniques. Overall, this work provides an efficient approach to solve design problems via fusion of simulations and ML and provides important groundwork for future experimental investigation of s-BCPs for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Validating continuum theory for Cottrell atmosphere solute drag by molecular dynamics simulations

When a dislocation moves through a field of mobile solute atoms, solutes segregate to the dislocation and form Cottrell atmospheres which exert solute drag forces. Over the last 70 years, continuum theory has been used extensively to estimate these drag forces and their dependence on the dislocation velocity, however few prior works have validated the accuracy of continuum theories. Here, in this work, molecular dynamics (MD) simulations of dislocation motion in face-centered cubic Ni containing interstitial H atoms were performed in order to test the accuracy of continuum theory predictions. Our results demonstrate that continuum theory provides an accurate estimate of the solute drag force for velocities below the critical velocity at which the solute drag force is maximized. Above the critical velocity, continuum theory systematically deviates from MD. Additional analysis reveals that this deviation results from the multi-valued and unstable nature of solute drag under load control, and also from the transition to random solute drag which occurs at high velocities.

Dislocations↗
NASA NTRSDate not supplied

Scalable Variable Charge Molecular Dynamics Simulations of Metal-Oxide Systems

Interfaces between metals and oxides are an important feature in many technologically relevant materials, e.g., oxidation of metal surfaces, oxide-dispersion strengthened (ODS) alloys, dielectric components, and thermal barrier coatings among others. Experimental studies of such interfaces are challenging since the majority are buried within the bulk, making computational modeling an attractive alternative. Molecular dynamics (MD) simulations operate at the length scales relevant to many interface-mediated mechanisms, but the requisite interatomic potentials for metal-oxide systems require computationally expensive variable charge schemes to account for the disparate bonding types, thus often limiting their effectiveness. Here we introduce several improvements to the charge transfer interatomic potential (CTIP) model which enable greater computational efficiency for large scale MD simulations. Then, using a new CTIP parametrization for the Ni-O system, we demonstrate its capabilities to capture critical atomic scale mechanisms associated with metal-oxide interfaces. Long time scale simulations (>10 ns) are used to investigate high temperature oxidation and oxide precipitation from the melt, and large length scale simulations (> 1 million atoms) are used to study the interaction of dislocations with oxide particles. We have implemented the new CTIP model in the widely used, open-source MD code LAMMPS.

Gabriel Plummer↗
DOE OSTI2021

Molecular dynamics simulation of the effect of cooling rate on the structure and properties of lithium disilicate glass

The effects of cooling rate on the structure and properties of lithium disilicate (LS2) glass are investigated using molecular dynamics (MD) computer simulations. The evolution of structural features such as pair distribution function, bond angle distribution, and Li coordination distribution are determined, and correlated with dynamic and static properties to elucidate the effects of cooling rate. The density, elastic moduli, and diffusion coefficient are found to be highly sensitive to cooling rate, whereas the Si pair distribution function and bond angle distribution are weakly affected by the cooling rate. Additionally, the changes of Si-O-Si bond angle and Li coordination number suggest the formation of Li cluster at lower cooling rates. Furthermore, by comparing results from other simulations and reported experiments, we confirm that the increase of cooling rate leads to an increase of conductivity and a decrease of density. Finally, at very high cooling rates, we find that all the atoms in LS2-glass do not relax simultaneously, but do so in two distinct configurations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Probing the Core–Shell Organization of Nanoconfined Methane in Cylindrical Silica Pores Using In Situ Small-Angle Neutron Scattering and Molecular Dynamics Simulations

Determining the structure of nanoconfined fluids is essential for predicting the fate of these fluids in subsurface geologic formations with nanoporous features and for engineering novel nanoporous materials for storing compressed gases. In this study, we probe the structure of nanoconfined methane at pressures in the range of 15–100 bar using in situ small-angle neutron scattering (SANS) measurements and molecular dynamics (MD) simulations. The structure of methane is probed in MCM-41 and SBA-15 with cylindrical pores and diameters of 3.3 and 6.8 nm, respectively. In situ SANS measurements and MD simulations showed that the confined methane molecules are organized in a core–shell structure, with the shell arising from the adsorption of methane molecules on the silica surface. The shell thicknesses of the adsorbed deuterated methane (CD4) molecules in MCM-41 obtained by SANS measurements are 1.4 ± 0.5, 2.1 ± 0.1, 3.2 ± 0.8, 4.0 ± 0.3, and 6.0 ± 0.7 Å at equilibrated pressures of 15.6, 35.6, 55.5, 73.3, and 95.7 bar, respectively. The shell thicknesses of the adsorbed CD4 layer in SBA-15 pores are 2.7 ± 0.5, 4.3 ± 0.7, 6.6 ± 0.7, 10.2 ± 0.3, and 14.6 ± 0.8 Å at equilibrated pressures of 15.5, 32.7, 52.4, 70, and 99.5 bar, respectively. These experimental results are in close agreement with the results predicted from MD simulations. Adsorption of methane molecules on the silica surfaces is primarily driven by van der Waals interactions between the methane molecules and the hydroxyl groups on the silica surface, while electrostatic interactions play a minor role. In conclusion, the experimental and simulation approaches described in this study provide fundamental insights into the organization of confined gases using methane as a specific example in the context of compressed fluid storage in natural and engineered materials for adaptive energy use.

03 NATURAL GAS↗
DOE OSTI2023

$\mathrm{DRAGON}$: A multi-GPU orbital-free density functional theory molecular dynamics simulation package for modeling of warm dense matter

As progress in electronic structure theoretical methods is made, ab initio molecular dynamics (MD) based on orbital-free density functional theory (OF-DFT) is becoming increasingly more successful at substituting the traditional, very accurate but computationally costly Kohn–Sham (KS) approach for simulations of matter at the challenging warm dense matter (WDM) regime. However, despite the significant cost alleviation of eliminating the dependence on the KS orbitals, OF-DFT MD runs require ~10 2 to 10 3 CPU cores running for days, or even weeks, for simulations of systems comprised of 10 2 to 10 3 atoms, depending on thermodynamic conditions. Here we present DRAGON, a multi-GPU OF-DFT MD code for fast and efficient simulations of WDM. With a relatively small allocation of resources (4 to 8 GPU devices) it can provide an order of magnitude speedup for simulations containing $\mathscr{O}$(10 4 ) atoms and target systems composed of $\mathscr{O}$(10 5 ) atoms at conditions within the WDM regime, which is currently outside the capabilities of CPU codes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗