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Results for “molecular dynamic (MD) simulation”

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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Local conformations and heterogeneities in structures and dynamics of isotactic polypropylene adsorbed onto carbon fiber

Carbon fiber (CF) reinforced polymers (CFRPs) have experienced widespread use in various industries. One of the most important parameters that controls the macroscopic property of CFRPs is the interface between a polymer matrix and CF. There is growing evidence to suggest the formation of a bound polymer layer (BPL), i.e., polymer chains that physically adsorb on a filler surface. However, this interface is always in contact with the thicker part of a polymer matrix, rendering its understanding a difficult task. Therein, we use CF-reinforced isotactic polypropylene (iPP) as a rational CFRP. To characterize the BPL on the CF surface, we extracted it from the CFRP using solvent-rinsing with p-xylene. The physical and thermal properties of the BPL were characterized by differential scanning calorimetry and thermogravimetric analysis, while its microscopic structures and dynamics were probed by small-angle neutron scattering and quasi-elastic neutron scattering (QENS) techniques. Subsequently, we employed atomistic molecular dynamics (MD) simulations to complement the QENS results above the bulk melting temperature and reveal details that were experimentally inaccessible. In this work, we observed that the degree of crystallinity of the BPL was quite lower than the bulk, while the melting temperature of the BPL remained the same as the bulks. Within the given length and time scales probed by QENS and MD, we also observed that most of the bound chains were mobile, with the formation of a high-density region (less than 1 nm in thickness) near the CF surface. The segmental dynamics of the bound chains probed by both QENS and MD were also much faster than those of the free chains, possibly due to the presence of a free surface region at the topmost surface of the BPL. Furthermore, the MD results demonstrated that the backbone chains and side groups lie nearly flat on the CF surface, which is the driving force for the flattening process of the iPP BPL to overcome the conformational entropy loss in the total free energy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Protein–Ligand Binding Free-Energy Calculations with ARROW–A Purely First-Principles Parameterized Polarizable Force Field

Protein–ligand binding free-energy calculations using molecular dynamics (MD) simulations have emerged as a powerful tool for in silico drug design. Here, we present results obtained with the ARROW force field (FF)–a multipolar polarizable and physics-based model with all parameters fitted entirely to high-level ab initio quantum mechanical (QM) calculations. ARROW has already proven its ability to determine solvation free energy of arbitrary neutral compounds with unprecedented accuracy. The ARROW FF parameterization is now extended to include coverage of all amino acids including charged groups, allowing molecular simulations of a series of protein–ligand systems and prediction of their relative binding free energies. We ensure adequate sampling by applying a novel technique that is based on coupling the Hamiltonian Replica exchange (HREX) with a conformation reservoir generated via potential softening and nonequilibrium MD. ARROW provides predictions with near chemical accuracy (mean absolute error of ~0.5 kcal/mol) for two of the three protein systems studied here (MCL1 and Thrombin). The third protein system (CDK2) reveals the difficulty in accurately describing dimer interaction energies involving polar and charged species. Overall, for all of the three protein systems studied here, ARROW FF predicts relative binding free energies of ligands with a similar accuracy level as leading nonpolarizable force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Atomistic Insights into the Reactive Diffusion of CO 2 in Guanidine-Based Facilitated Transport Membranes

The pressing need to address climate change has led to significant advancements in carbon dioxide (CO 2 ) capture technologies. Notably, facilitated transport membranes (FTMs) are distinguished by their exceptional selectivity and permeance, attributed to their reversible chemical reactions with CO 2 . This study, for the first time, sheds light on the reactive diffusion mechanism of CO 2 in FTMs, utilizing 1,1,3,3-tetramethylguanidine (TMG) as a mobile carrier. Specifically, state-ofthe- art molecular dynamics (MD) simulations, augmented by a reparameterized reactive force field (ReaxFF) capable of describing atomistic interactions and reaction pathways, are conducted to investigate the transport of CO 2 in TMG. The analysis of mean squared displacement (MSD) and diffusion coefficients reveals a clear hierarchy in the mobility of reaction components. Our findings highlight a unique hopping diffusion mechanism between bicarbonate ions and TMG molecules, increasing the diffusivity of reacted CO 2 by 1.4 times. The hopping events observed not only enhance our understanding of molecular mobility but also offer a means to boost the performance of FTMs in CO 2 capture applications. Overall, this research lays the groundwork for the future design of FTMs with optimal carrier properties.

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

Uncovering the role of nanoscale precipitates on martensitic transformation and superelasticity

Here we characterize the role of coherent nanoscale B2 Ni 50 Al 50 precipitates on the temperature- and stress-induced martensitic phase transformation in nanocrystalline Ni 63 Al 37 shape memory alloys using multi-million-atoms molecular dynamics (MD) simulations. We studied two types of precipitates: one with single crystal precipitates (SXP) and a second where grain boundaries cut through precipitates (PXP). Simulations reveal that the presence of B2 precipitates stabilizes the cyclic flag-shaped stress-strain response, characteristic of superelasticity, and reduces remnant strain. In contrast, single-phase nanocrystalline Ni 63 Al 37 exhibits degradation of the reverse transformation during cyclic loading and, eventually, incomplete reversible transformation within a few cycles. This is consistent with previous experimental findings of ultra-low fatigue in Ni-Ti-Cu alloys with Ti 2 Cu precipitates. The simulations reveal that the presence of precipitates significantly improves the reversibility of the transformation by acting as elastic zones that partially shield the martensitic transformation and drive the reverse transformation. A detailed analysis of the MD trajectories reveals that the martensitic transformation of the matrix induces ultra-large elastic deformation in some of the B2 precipitates (approximately 12%) to the point of resulting in a martensite-like atomic structure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electrochemically Mediated Au–C(sp 2 ) Anchors for Molecular Electronics

Terminal anchor groups play a key role in the stability and electronic properties of molecular junctions. Single molecule junctions typically consist of two preinstalled terminal anchors linking organic molecules to metal electrodes. Here, in this work, we show that p -terphenyl derivatives containing only a single terminal anchor show conductance features similar to junctions with two preinstalled terminal anchors. A set of p -terphenyl derivatives with one terminal anchor was prepared using automated chemical synthesis and characterized using single molecule electronics experiments, molecular dynamics (MD) simulations, bulk electrochemistry and spectroscopy, and nonequilibrium Green’s function-density functional theory (NEGF-DFT) calculations. Our results show that 4-amino- p -terphenyl (PPP) and related analogs exhibit a well-defined high conductance state that is diminished or absent in other p-terphenyl derivatives lacking a preinstalled amine terminal anchor or fluorine or methyl substitutions at the terminal para position. However, a low conductance state is observed in all amino- p -terphenyl derivatives with one preinstalled anchor due to molecular junctions formed by noncovalent dimeric π–π stacking interactions. The observed high conductance state diminishes upon the addition of reducing agents and is restored upon the addition of an oxidizing agent. Our results suggest that the high conductance state arises due to Au–C(sp 2 ) bond formation facilitated by a single electron oxidation event at the electrode surface. A series of control experiments with different anchor groups shows that primary amines play a key role in forming Au–C bonds for molecular junctions. Overall, these results suggest that Au–C bond formation gives rise to high conductance pathways in organic molecules containing only one preinstalled terminal anchor. Insights from this work can be leveraged in the design of molecular electronic devices, particularly in understanding the mechanisms of molecular binding and junction formation.

charge transport↗
DOE OSTI2025

Efficient machine learning interatomic potentials robust for liquid and multiple solid polymorphs of NaF and KF

Achieving atomic-level understanding of crystallization of molten salts is of importance to a wide range of technological applications. Recent work [Fan et al., Proc. Natl. Acad. Sci. USA 122, e2425702122 (2025)] revealed that crystal nucleation in molten LiF salt is a multistage process according to the molecular-dynamics (MD) simulations based on an atomic cluster expansion (ACE) machine-learning interatomic potential (MLIP). In order to understand the influence of increasing cation size on nucleation pathways and nucleation rates of molten fluoride salts, here we develop two new ACE MLIPs for NaF and KF. The two ACE MLIPs feature DFT-SCAN-level accuracy for liquid and multiple solid polymorphs over a wide temperature (0–2000 K) and pressure (0–100 GPa) range, and also reproduce well a number of experimental data for solid and liquid equilibrium properties. The efficiency of the two ACE MLIPs enable million-atom-scale or microsecond-scale MD simulations. The two general-purpose ACE MLIPs are expected to be useful for atomistic simulations for different purposes, in addition to studying crystallization of molten NaF and KF salts.

Crystal melting↗
DOE OSTI2022

The role of deviatoric stress and dislocations on the α to ω phase transformation in Ti

Under extreme conditions, α-Ti becomes unstable and transforms either into β-Ti at high temperature or into ω-Ti at high pressure. In what concerns the α to ω phase transformation (PT), there has been a wide range of experimentally reported transition pressures from approximately 2 to 15 GPa at room temperature. Deviatoric stresses and internal defects are often assumed to be the root cause of this variation. Here, in this study, these postulates are revisited using both continuum mechanics and molecular dynamics (MD) simulations. First, a simple continuum model, assuming linear elasticity and isotropic plasticity, is developed to describe the effects of applied stress and dislocations on the stability of an ω nucleus in an infinite α domain. Second, a new MD simulation method is developed to generate an ω nucleus in the α domain utilizing the displacement field identified from the topological analysis. Results from MD simulations show that despite the fact that phase diagrams typically delineate the limits between two phases in terms of only P and T, deviatoric stress promotes the α to ω phase transformation by reducing the critical radius above which an ω nucleus is stable. Furthermore, the required deviatoric stress to nucleate and stabilize a nanoscale ω nucleus is likely emanating from the internal stress of defects such as dislocations. The MD-informed micromechanics models are used to identify favorable configurations where dislocations help favor the α to ω transformation. These configurations show that the interaction with a basal or prismatic dislocation reduces the critical radius of a ω nucleus by about 10 or 16 %, respectively. In addition, prismatic edge dislocations are found to promote the growth of ω nucleus when interacting with the ($\bar{1}$$\bar{1}$20) α //(0001) ω interface. Importantly, a simple model of the arrival of dislocation at an ω nucleus suggests that PT does not necessarily require a pile-up to be present but could alternatively be mediated by a constant rapid flow of dislocations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Molecular dynamics and experimental study on the adhesion mechanism of polyvinyl alcohol (PVA) fiber in alkali-activated slag/fly ash

This paper aims to study the adhesion mechanism of polyvinyl alcohol (PVA) fiber within alkali-activated slag/fly ash (AASF) matrix using molecular dynamics (MD) simulation in combination with systematic experimental characterization. The adhesion of PVA to C-(N-)A-S-H gel with different Ca/(Si+Al) and Al/Si ratios was modeled using MD simulation, with the related adsorption enthalpy calculated and the adhesion mechanism explored. The experimentally attained chemical bonding energy of PVA fiber in AASF coincides well with the simulation results. In both cases, the adhesion enhances primarily with increasing Ca/(Si+Al) ratio of C-(N-)A-S-H gel. Additionally, MD simulation indicates preferential element distributions of Ca around PVA molecule, which was confirmed experimentally by the detection of the Ca-rich C-(N-)A-S-H gel in the interfacial transition zone (ITZ). }This study provides further insights into the adhesion mechanism of PVA fiber to C-(N-)A-S-H gel formed in AASF, which is particularly valuable for the future development of PVA-based high-performance alkali-activated composites.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2

SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD–ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Unsupervised learning of representative local atomic arrangements in molecular dynamics data

Molecular dynamics (MD) simulations present a data-mining challenge, given that they can generate a considerable amount of data but often rely on limited or biased human interpretation to examine their information content. By not asking the right questions of MD data we may miss critical information hidden within it. Here we combine dimensionality reduction (UMAP) and unsupervised hierarchical clustering (HDBSCAN) to quantitatively characterize prevalent coordination environments of chemical species within MD data. By focusing on local coordination, we significantly reduce the amount of data to be analyzed by extracting all distinct molecular formulas within a given coordination sphere. We then efficiently combine UMAP and HDBSCAN with alignment or shape-matching algorithms to partition these formulas into structural isomer families indicating their relative populations. The method was employed to reveal details of cation coordination in electrolytes based on molecular liquids.

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

Chain Redistribution Stabilizes Coexistence Phases in Block Copolymer Blends

The nanoscale morphologies of block copolymer (BCP) thin films are determined by chain architecture. Experimental studies of thin film blends of different BCP chain types have demonstrated that blending can stabilize new motifs, such as coexistence phases. Here, we deploy coarsegrained molecular dynamics (MD) simulations in order to better understand the self-assembly behavior of BCP blend thin films. Here, we consider blends of lamella- and cylinder-forming BCP chains, studying their morphological makeup, the chain distribution within the morphology, and the underlying polymer chain conformations. Our simulations show that there are local concentration deviations at the scale of the morphological objects that dictate the local structure, and that BCP chains redistribute within the morphology so as to stabilize the structure. Underlying these effects are measurable distortions in the BCP chain conformations. The conformational freedom afforded by BCP blending stabilizes defects and allows coexistence phases to appear, while also leading to kinetic trapping effects. These results highlight the power of blending in designing the morphology that forms.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Morphology and Dynamics in Hydroxide-Conducting Polysulfones

In alkaline zinc–manganese dioxide batteries, there is a need for selective polymeric separators that have good hydroxide ion conductivity but that prevent the transport of zincate (Zn(OH) 4 ) 2- . Here we investigate the nanoscale structure and hydroxide transport in two cationic polysulfones that are promising for these separators. We present the synthesis and characterization for a tetraethylammonium-functionalized polysulfone (TEA-PSU) and compare it to our previous work on an N-butylimidazolium-functionalized polysulfone (NBI-PSU). We perform atomistic molecular dynamics (MD) simulations of both polymers at experimentally relevant water contents. The MD simulations show that both polymers develop well phase separated nanoscale water domains that percolate through the polymer. Calculation of the total scattering intensity from the MD simulations reveal weak or nonexistent ionomer peaks at low wave vectors. The lack of an ionomer peak is due to a loss of contrast in the scattering. The small water domains in both polymers, with median diameters on the order of 0.5–0.7 nm, lead to hydroxide and water diffusion constants that are 1–2 orders of magnitude smaller than their values in bulk water. This confinement lowers the conductivity but also may explain the strong exclusion of zincate from the PSU membranes seen experimentally.

25 ENERGY STORAGE↗
DOE OSTI2025

Mechanisms and stability of Li dynamics in amorphous Li-Ti-P-S-based mixed ionic–electronic conductors: A machine learning molecular dynamics study

Mixed ionic–electronic conductors (MIECs) exhibit both high ionic and electronic conductivity to improve the battery performance. In this work, we investigate the mechanism and stability of transport channels in our recently developed MIEC material, amorphous Ti-doped lithium phosphorus sulfide (LPS), using molecular dynamics (MD) simulations with a 99% accurate machine-learning force field (MLFF) trained on ab initio MD data. The achieved MLFF helps efficient large-scale MD simulations on LPS with three Ti concentrations (10%, 20%, and 30%) and six temperatures (25°C to 225°C) to calculate ionic conductivity, activation energy, Li-ion transport mechanism, and configurational entropy. Results show that ionic conductivities and activation energies are consistent with our recent experimental values. Moreover, Li-ion transport occurs via free-volume diffusion facilitated by the formation of disordered Li-S polyhedra. The enhanced stability of transport channels at 10% and 20% Ti doping, compared to 0% and 30%, is observed by analyzing the vibrational and configurational entropy of these disordered Li-S polyhedra. Overall, this study highlights the utility of MLFF-based large-scale MD simulations in explaining the transport mechanism and the stability of Li-ion in Ti-doped LPS electrolyte with significant computational efficiency.

And configuration entropy↗
DOE OSTI2022

Lytic polysaccharide monooxygenase increases cellobiohydrolases activity by promoting decrystallization of cellulose surface

Efficient depolymerization of crystalline cellulose requires cooperation between multiple cellulolytic enzymes. Through biochemical approaches, molecular dynamics (MD) simulation, and single-molecule observations using high-speed atomic force microscopy (HS-AFM), we quantify and track synergistic activity for cellobiohydrolases (CBHs) with a lytic polysaccharide monooxygenase (LPMO) from Phanerochaete chrysosporium. Increasing concentrations of LPMO (AA9D) increased the activity of a glycoside hydrolase family 6 CBH, Cel6A, whereas the activity of a family 7 CBH (Cel7D) was enhanced only at lower concentrations of AA9D. MD simulation suggests that the result of AA9D action to produce chain breaks in crystalline cellulose can oxidatively disturb the crystalline surface by disrupting hydrogen bonds. HS-AFM observations showed that AA9D increased the number of Cel7D molecules moving on the substrate surface and increased the processivity of Cel7D, thereby increasing the depolymerization performance, suggesting that AA9D not only generates chain ends but also amorphizes the crystalline surface, thereby increasing the activity of CBHs.

09 BIOMASS FUELS↗
DOE OSTI2020

The effects of stress, temperature and facet structure on growth of { 10 1 ¯ 2 } twins in Mg: a molecular dynamics and phase field study

The present study focuses on the roles of structure, stress and temperature on the mobility of facets bounding twin domains and on the overall impact on the growth kinetics of { 10 1 ¯ 2 } twins in Mg. We first use molecular dynamics simulations (MD) to study the relationship between interface structures, stress, temperature and mobility. As facets can exhibit distinct atomic scale structures, we also quantify the effect of stress relaxation mediated by misfit dislocations on the mobility of the basal-prismatic interface. The information gathered for ten different facets is used to calibrate an anisotropic phase field model predicting the effects of temperature and stress on the kinetics and shape of a growing { 10 1 ¯ 2 } 3D twin, by comparison with MD data. The comparative analysis suggests that, as compared to simulations of individual facets, the effective mobility of facets can be significantly different during growth of a 3D twin. This can be attributed to the complex three-dimensional internal stress state of the twin and to coupling in facet motion triggered by facet junctions. As such, by directly fitting both the twin growth kinetics and morphology as predicted by MD for different stresses and temperatures, we can identify a limited set of rate-limiting facets that control twin growth and morphology, and measure their effective mobility.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Method for Obtaining Liquid–Solid Adsorption Rates from Molecular Dynamics Simulations: Applied to Methanol on Pt(111) in H 2 O

Adsorption is an important step in heterogeneous catalysis as it predetermines how many reactant molecules can participate in a surface reaction per unit time. While the rate of adsorption processes is well studied in gas–solid adsorption in both theory and experiment, such rates are still not well studied for liquid–solid adsorption. This is partly because the ever-changing configurations of liquid-phase solvent molecules impede the ability to study a molecule approaching a surface from a liquid phase by either experiment or theory. In this work, we develop a method using molecular dynamics (MD) simulations to study the rate of adsorption in liquid–solid adsorption processes. Specifically, we use MD to model the diffusion of a methanol molecule in aqueous solvent and its adsorption to a Pt(111) surface. We find that by approximating the solute motion as following the same displacement rates as a random walk model, the adsorbed and non-adsorbed states of the methanol molecule near the Pt(111) surface can be discerned and quantified. In particular, this methodology enables extracting a sticking coefficient and a macroscopically relatable adsorption rate. This method can be applied to arbitrary types of reactants and surfaces, as well as different liquid environments, thus providing a general tool for predicting quantitative adsorption rates of liquid–solid adsorption systems.

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

Reactor wall effects in Si–Cl 2 –Ar atomic layer etching

This work complements our previous manuscript [J. Vac. Sci. Technol. A41, 062602 (2023)] where predictions from molecular dynamics (MD) simulations of silicon–chlorine–argon (Si–Cl 2 –Ar) atomic layer etching (ALE) are compared to experiments. When etch product distributions for atomic chlorine (Cl) and silicon chlorides were initially compared to optical emission spectroscopy (OES) signals, it appeared that there was a discrepancy between the MD predictions and experimental results at higher ion fluences. Experiments showed a relatively long period of nearly constant Cl-containing etch products released from the ion-bombarded surface (referred to as the “plateau”) but this effect was not observed in MD simulations. In this report, we demonstrate that the “plateau” observed in the OES signals is most likely due to the desorption of Cl-containing etch products from the walls of the reactor and subsequent adsorption on the Si substrate. Experiments varying the gas residence time in the chamber while keeping incoming gas concentrations and pressure constant support this interpretation. We also conducted experiments with an additional Ar-only flow in the chamber to reduce the concentration of Cl-containing species on the chamber walls. For both sets of flow modification experiments, we observe results consistent with the hypothesis that Cl-containing species desorbing from chamber walls are a significant cause of the observed discrepancy between MD predictions and experimental observations. If the measured OES signals are corrected for this “additional” source of Cl-containing species at the surface, the MD predictions and measured OES signals are in excellent agreement. This further supports the predictive capability of MD simulations to accurately capture the relevant physical and chemical processes in plasma-assisted ALE processes. We provide an order of magnitude estimate of the required density of Cl-containing species that would account for the additional etch products observed. Finally, we discuss the implications of this effect on ALE in plasma nanofabrication.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗