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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Molecular Dynamics Simulations of Austenite-Martensite Interfaces in NiTi Shape Memory Alloys

The unique properties of shape memory alloys (SMAs) arise from a reversible martensitic transformation. The nucleation and migration of austenite-martensite interfaces are the key to understanding the SMA properties. Molecular dynamics (MD) simulations can provide important atomic-scale information about these aspects of the transformation, but their time scales prevent the interface formation under near-equilibrium conditions relevant to experiment. We present a new MD methodology which allows for the natural formation of energetically preferred austenite-martensite interfaces under near-equilibrium conditions. Our simulation demonstrates that the interfaces in NiTi are semi-coherent, composed of a series of terrace planes and structural disconnections, and they migrate rapidly through single crystals with only a small thermodynamic driving force. In bi-crystals and polycrystals, the migration of these same interfaces is significantly impeded by grain boundaries and stored elastic energy. This behavior can result in SMA hysteresis via several mechanisms associated with nucleation and non-elastic strain accommodation.

Gabriel Plummer↗
DOE OSTI2020

Orientation and Conformation of Proteins at the Air–Water Interface Determined from Integrative Molecular Dynamics Simulations and Sum Frequency Generation Spectroscopy

Understanding the assembly of proteins at the air-water interface (AWI) informs the formation of protein films, emulsion properties, and protein aggregation. Determination of protein conformation and orientation at an interface is difficult to resolve with a single experimental or simulation technique alone. To date, the interfacial structure of even one of the most widely studied proteins, lysozyme, at the AWI remains unresolved. Here in this study, molecular dynamics (MD) simulations are used to determine if the protein adopts a side-on, head-on, or axial orientation at the AWI with two different forcefields, GROMOS-53a6 + SPC/E and a99SB-disp + TIP4P-D. Vibrational sum frequency generation (SFG) spectroscopy experiments and spectral SFG calculations validate consistency between the structure determined from MD and experiments. Overall, we show with strong agreement that lysozyme adopts an axial conformation at pH 7. Further, we provide molecular-level insight as to how pH influences the binding domains of lysozyme resulting in side-on adsorption near the isoelectric point of the lysozyme.

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

Iron surface corrosion in supercritical CO2 at atomic scale investigated by molecular dynamics simulations

Understanding the corrosion behavior of steels in supercritical carbon dioxide (S-CO2) is essential for ensuring the safe application of S-CO2 as a heat-transfer fluid in high-temperature energy systems, including advanced nuclear reactors. In this work, molecular dynamics (MD) simulations using ReaxFF potential are performed to explore the atomic-scale corrosion mechanisms of body-centered cubic iron (BCC-Fe) in S-CO2. The results show that CO2 molecules in S-CO2 decompose at the Fe surface, generating free C and O atoms that form Fe-C and Fe-O bonds and subsequently produce oxides and carbides. Concurrently, Fe atoms dissolve from the surface and diffuse into the S-CO2 region, resulting in interdiffusion of Fe, C and O atoms at the interface. The corrosion-layer thickness calculations show that high pressure and temperature induced by S-CO2 have stronger effects than surface orientation on the corrosion process. In addition, surface Fe atoms undergo substantial displacement under S-CO2 exposure, further accelerating corrosion. When a radiation-induced void is introduced near the Fe surface, the corrosion is enhanced. The void-matrix interface expands the reaction surface area and simultaneously induces corrosion reactions inside the bulk, resulting in a deeper penetration of C and O and thicker corrosion layers. All these results indicate that high-temperature, high-pressure and radiation-induced voids can seriously affect the corrosion of Fe in S-CO2, and must be considered to better use S-CO2 in nuclear facilities.

Li, Wenhua↗
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↗