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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

All-atom molecular dynamics simulations of weak polyionic brushes: influence of charge density on the properties of polyelectrolyte chains, brush-supported counterions, and water molecules

All atom molecular dynamics (MD) simulations of planar Na+-counterion-neutralized polyacrylic acid (PAA) brushes are performed for varying degrees of ionization (and thereby varying charge density) and varying grafting density. Variation in the PE charge density (or degree of ionization) and grafting density leads to massive changes of the properties of the PE molecules (quantified by the changes in the height and the mobility of the PE brushes) as well as the local arrangement and distribution of the brush-supported counterions and water molecules within the brushes. The effect on the counterions is manifested by the corresponding variation of the counterion mobility, counterion concentration, extent of counterion binding to the charged site of the PE brushes, water-in-salt-like structure formation, and counterion-water–oxygen radial distribution function within the PE brushes. On the other hand, the effect on water molecules is manifested by the corresponding variation of water–oxygen–water–oxygen RDF, local water density, water–water and water–PE functional group hydrogen bond networks, static dielectric constant of water molecules, orientational tetrahedral order parameter, and water mobility. Enforcing such varying degree of ionization of weak polyelectrolytes is possible by changing the pH of the surrounding medium. Thus, our results provide insights into the changes in microstructure (at the atomistic level) of weak polyionic brushes at varying pH. Finally, we anticipate that this knowledge will prove to be vital for the efficient design of several nano-scale systems employing PE brushes such as nanomechanical gates, current rectifiers, etc.

42 ENGINEERING↗
DOE OSTI2015

A wrench in the works of human acetylcholinesterase: Soman induced conformational changes revealed by molecular dynamics simulations

Irreversible inactivation of human acetylcholinesterase (hAChE) by organophosphorous pesticides (OPs) and chemical weapon agents (CWA) has severe morbidity and mortality consequences. We present data from quantum mechanics/molecular mechanics (QM/MM) and 80 classical molecular dynamics (MD) simulations of the apo and soman-adducted forms of hAChE to investigate the effects on the dynamics and protein structure when the catalytic Serine 203 is phosphonylated. We find that the soman phosphonylation of the active site Ser203 follows a water assisted addition-elimination mechanism with the elimination of the fluoride ion being the highest energy barrier at 6.5 kcal/mole. We observe soman-dependent changes in backbone and sidechain motions compared to the apo form of the protein. These alterations restrict the soman-adducted hAChE to a structural state that is primed for the soman adduct to be cleaved and removed from the active site. The altered motions and resulting structures provide alternative pathways into and out of the hAChE active site. In the soman-adducted protein both side and back door pathways are viable for soman adduct access. Correlation analysis of the apo and soman adducted MD trajectories shows that the correlation of gorge entrance and back door motion is disrupted when hAChE is adducted. This supports the hypothesis that substrate and product can use two different pathways as entry and exit sites in the apo form of the protein. These alternative pathways have important implications for the rational design of medical countermeasures.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Application of First-Principles-Based Artificial Neural Network Potentials to Multiscale-Shock Dynamics Simulations on Solid Materials

The use of artificial neural network (ANN) potentials trained with first-principles calculations has emerged as a promising approach for molecular dynamics (MD) simulations encompassing large space and time scales while retaining first-principles accuracy. To date, however, the application of ANN-MD has been limited to near-equilibrium processes. Here we combine first-principles-trained ANN-MD with multiscale shock theory (MSST) to successfully describe far-from-equilibrium shock phenomena. Overall, our ANN-MSST-MD approach describes shock-wave propagation in solids with first-principles accuracy but a 5000 times shorter computing time. Accordingly, ANN-MD-MSST was able to resolve fine, long-time elastic deformation at low shock speed, which was impossible with first-principles MD because of the high computational cost. This work thus lays a foundation of ANN-MD simulation to study a wide range of far-from-equilibrium processes.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Using collective variables to drive molecular dynamics simulations

A software framework is introduced that facilitates the application of biasing algorithms to collective variables of the type commonly employed to drive massively parallel molecular dynamics (MD) simulations. The modular framework that is presented enables one to combine existing collective variables into new ones, and combine any chosen collective variable with available biasing methods. The latter include the classic time-dependent biases referred to as steered MD and targeted MD, the temperature-accelerated MD algorithm, as well as the adaptive free-energy biases called metadynamics and adaptive biasing force. The present modular software is extensible, and portable between commonly used MD simulation engines.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Time Step Considerations when Simulating Dynamic Behavior of High Performance Homes

Building energy simulations, especially those concerning pre-cooling strategies and cooling/heating peak demand management, require careful analysis and detailed understanding of building characteristics. Accurate modeling of the building thermal response and material properties for thermally massive walls or advanced materials like phase change materials (PCMs) are critically important.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Low-mass molecular dynamics simulation: A simple and generic technique to enhance configurational sampling

Highlights: • Reducing atomic masses by 10-fold vastly improves sampling in MD simulations. • CLN025 folded in 4 of 10 × 0.5-μs MD simulations when masses were reduced by 10-fold. • CLN025 folded as early as 96.2 ns in 1 of the 4 simulations that captured folding. • CLN025 did not fold in 10 × 0.5-μs MD simulations when standard masses were used. • Low-mass MD simulation is a simple and generic sampling enhancement technique. - Abstract: CLN025 is one of the smallest fast-folding proteins. Until now it has not been reported that CLN025 can autonomously fold to its native conformation in a classical, all-atom, and isothermal–isobaric molecular dynamics (MD) simulation. This article reports the autonomous and repeated folding of CLN025 from a fully extended backbone conformation to its native conformation in explicit solvent in multiple 500-ns MD simulations at 277 K and 1 atm with the first folding event occurring as early as 66.1 ns. These simulations were accomplished by using AMBER forcefield derivatives with atomic masses reduced by 10-fold on Apple Mac Pros. By contrast, no folding event was observed when the simulations were repeated using the original AMBER forcefields of FF12SB and FF14SB. The results demonstrate that low-mass MD simulation is a simple and generic technique to enhance configurational sampling. This technique may propel autonomous folding of a wide range of miniature proteins in classical, all-atom, and isothermal–isobaric MD simulations performed on commodity computers—an important step forward in quantitative biology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Structure, Dynamics, and Hydrogen Transport in Amorphous Polymers: An Analysis of the Interplay between Free Volume Element Distribution and Local Segmental Dynamics from Molecular Dynamics Simulations

Polymers are attractive membrane materials owing to their mechanical robustness and relatively inexpensive fabrication. An important indicator of membrane performance are free volume elements (FVE): microporous void spaces created by the inefficient packing of bulky groups along the polymer chain. FVEs tend to degrade over time, as polymer chains reorganize irreversibly. While it is widely accepted that polymer flexibility has an impact on membrane transport properties, the molecular nature of this impact is still not well understood. By the establishment of a correlation between local chain dynamics and the distribution of free volume elements (FVEs), penetrant transport can be regulated more efficiently in amorphous polymer membranes. In this work, we implement all-atom molecular dynamics (MD) simulations to explore the relationship between chain dynamics and free volume in three polymers with different levels of backbone flexibility: polymethylpentene (PMP), polystyrene (PS), and HAB-6FDA thermally rearranged polymer (TRP). We construct these polymers at different temperatures and examine how temperature impacts the FVE distribution and segmental mobility. Our analysis shows that chain segments near FVEs have higher mobility compared with the atoms in the bulk; the extent of this difference increases with chain flexibility. Increasing the chain flexibility by increasing the temperature results in a broader FVE distribution. Rigid polymers such as TRP show the most robust FVE distribution and are not significantly affected by the temperature change. To capture penetrant diffusion through the polymer matrix, hydrogen is inserted and the diffusion is measured at different temperatures; hydrogen mobility is influenced by the FVE structure and overall mobility of polymer chains. Lastly, at low temperatures, hydrogen mobility is influenced by void distribution, while at high temperatures, polymer dynamics dictate hydrogen transport.

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

Deep potential molecular dynamics simulations of ion-enhanced etching of silicon by atomic chlorine

The continued development of plasma-assisted processing techniques requires a fundamental understanding of plasma-surface interactions. Molecular dynamics (MD) simulations have been employed to complement experimental studies and better understand the properties of such systems. Recently, machine learning (ML) methods have enabled the development of ab initio-based interatomic potentials, which can be generalized to complex combinations of multiple atom types. In this work, we use ML potentials developed using the Deep Potential Molecular Dynamics (DeepMD) framework to provide a model of ion-enhanced etching of Si by Cl atoms. We demonstrate the importance of proper selection of the training data set to the accuracy of the DeepMD model and compare our results to MD results using empirical potentials, as well as to experimental measurements. Exposure of undoped Si at 300 K to thermal Cl atoms yields a steady-state Cl coverage of 1.25 monolayers, which is slightly lower than the value obtained in previous experimental studies. Predictions of Si etch yields by simultaneous Cl atom and Ar + ion impacts as a function of ion energy, neutral to ion flux ratio, and angle of incidence of the ions are in reasonably good agreement with classical MD results and experimental measurements. Finally, etch yields and SiCl x mixed layer thicknesses during simultaneous bombardment of the Si(100) surface by Cl atoms and Cl + ions are in good agreement with experimental data. In conclusion, the present work is a necessary condition for the extension of the DeepMD procedure to more complex systems of interest in plasma-surface interactions.

Artificial neural networks↗
DOE OSTI2015

Effect of Tapering on Morphology and Interfacial Behavior of Diblock Copolymers from Molecular Dynamics Simulations

Tapered diblock copolymers are AB diblock copolymers modified by adding a gradient region between the blocks in which composition varies smoothly from one species to the other. This gives additional control parameters, the length of the taper and its direction, to control the microphase separation behavior. Using tapers can also increase the accessibility of the bicontinuous gyroid phase, potentially of interest in transport applications. Recently, the phase diagram of these systems was predicted using self-consistent field theory (SCFT). Here, we perform coarse-grained molecular dynamics (MD) simulations to investigate both the structural and dynamic properties of tapered diblock copolymers. The MD results are consistent with the SCFT phase diagram, and the density profiles are also similar as a function of taper length and direction. We additionally compute mean-squared displacements and end-to-end relaxation times of lamellar systems and observe individual polymer conformations. Increasing taper length effectively lowers segregation strength and leads to a smaller domain spacing; the changes in dynamics are also discussed. The short (30%) inverse taper has a significantly shorter domain spacing than the diblock and qualitatively different polymer conformations (chains can fold back and forth across the interface).

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

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom

Energy-efficient ventilation control plays an important role in reducing building energy consumption while ensuring occupant health and comfort. While Computational Fluid Dynamics (CFD) simulations provide detailed and physically accurate representations of indoor airflow, their high computational cost limits their use in real-time building control. In this work, we present a neural operator learning framework that combines the physical accuracy of CFD with the computational efficiency of machine learning to enable building ventilation control with the high-fidelity fluid dynamics models. Our method jointly optimizes the airflow supply rates and vent angles to reduce energy use and adhere to air quality constraints. We train an ensemble of neural operator transformer models to learn the mapping from building control actions to airflow fields using high-resolution CFD data. This learned neural operator is then embedded in an optimization-based control framework for building ventilation control. Experimental results show that our approach achieves significant energy savings compared to maximum airflow rate control, rule-based control, as well as data-driven control methods using spatially averaged CO 2 prediction and deep learning–based reduced-order models, while consistently maintaining safe indoor air quality. These results highlight the practicality and scalability of our method in maintaining energy efficiency and indoor air quality in real-world buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties

Polymer electrolytes are promising candidates for the next generation lithium-ion battery technology. Large scale screening of polymer electrolytes is hindered by the significant cost of molecular dynamics (MD) simulation in amorphous systems: the amorphous structure of polymers requires multiple, repeated sampling to reduce noise and the slow relaxation requires long simulation time for convergence. Here, we accelerate the screening with a multi-task graph neural network that learns from a large amount of noisy, unconverged, short MD data and a small number of converged, long MD data. We achieve accurate predictions of 4 different converged properties and screen a space of 6247 polymers that is orders of magnitude larger than previous computational studies. Further, we extract several design principles for polymer electrolytes and provide an open dataset for the community. Our approach could be applicable to a broad class of material discovery problems that involve the simulation of complex, amorphous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

CuCl Complexation in the Vapor Phase: Insights from Ab Initio Molecular Dynamics Simulations

We investigated the hydration of the CuCl 0 complex in HCl-bearing water vapor at 350°C and a vapor-like fluid density between 0.02 and 0.09 g/cm 3 using ab initio molecular dynamics (MD) simulations. The simulations reveal that one water molecule is strongly bonded to Cu(I) (first coordination shell), forming a linear [H 2 O-Cu-Cl] 0 moiety. The second hydration shell is highly dynamic in nature, and individual configurations have short life-spans in such low-density vapors, resulting in large fluctuations in instantaneous hydration numbers over a timescale of picoseconds. The average hydration number in the second shell ( m ) increased from ~0.5 to ~3.5 and the calculated number of hydrogen bonds per water molecule increased from 0.09 to 0.25 when fluid density (which is correlated to water activity) increased from 0.02 to 0.09 g/cm 3 ( f H 2 O 1.72 to 2.05). These changes of hydration number are qualitatively consistent with previous solubility studies under similar conditions, although the absolute hydration numbers from MD were much lower than the values inferred by correlating experimental Cu fugacity with water fugacity. This could be due to the uncertainties in the MD simulations and uncertainty in the estimation of the fugacity coefficients for these highly nonideal “vapors” in the experiments. Finally, our study provides the first theoretical confirmation that beyond-first-shell hydrated metal complexes play an important role in metal transport in low-density hydrothermal fluids, even if it is highly disordered and dynamic in nature.

58 GEOSCIENCES↗
DOE OSTI2014

Molecular dynamics simulation of diffusion coefficients and structural properties of some alkylbenzenes in supercritical carbon dioxide at infinite dilution

The binary infinite dilute diffusion coefficients, D{sub 12}{sup ∞}, of some alkylbenzenes (Ph-C{sub n}, from Ph-H to Ph-C{sub 12}) from 313 K to 333 K at 15 MPa in supercritical carbon dioxide (scCO{sub 2}) have been studied by molecular dynamics (MD) simulation. The MD values agree well with the experimental ones, which indicate MD simulation technique is a powerful way to predict and obtain diffusion coefficients of solutes in supercritical fluids. Besides, the local structures of Ph-C{sub n}/CO{sub 2} fluids are further investigated by calculating radial distribution functions and coordination numbers. It qualitatively convinces that the first solvation shell of Ph-C{sub n} in scCO{sub 2} is significantly influenced by the structure of Ph-C{sub n} solute. Meanwhile, the mean end-to-end distance, the mean radius of gyration and dihedral angle distribution are calculated to gain an insight into the structural properties of Ph-C{sub n} in scCO{sub 2}. The abnormal trends of radial distribution functions and coordination numbers can be reasonably explained in term of molecular flexibility. Moreover, the computed results of dihedral angle clarify that flexibility of long-chain Ph-C{sub n} is the result of internal rotation of C-C single bond (σ{sub c-c}) in alkyl chain. It is interesting that compared with n-alkane, because of the existence of benzene ring, the flexibility of alkyl chain in Ph-C{sub n} with same carbon atom number is significantly reduced, as a result, the carbon chain dependence of diffusion behaviors for long-chain n-alkane (n ≥ 5) and long-chain Ph-C{sub n} (n ≥ 4) in scCO{sub 2} are different.

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

Si–Cl 2 –Ar + Atomic Layer Etching Window: A Fundamental Study Using Molecular Dynamics Simulations and a Reduced Order Model

Silicon (Si) atomic layer etching (ALE) by alternating exposure to chlorine gas (Cl 2 ) and argon ions (Ar + ) is studied by using molecular dynamics (MD) simulations and a reduced order model (ROM). Here, the purpose of this study is to elucidate the properties of the ALE window, a range of ion energies where the amount of Si etched over a series of cycles is nonzero and nearly independent of ion energy. Experimental studies of the Si–Cl 2 –Ar + ALE system report contradictory results related to the ALE window’s ion energy range. Both MD simulations and the ROM show that there is an ALE window present from approximately 15 to 20 eV for normal incidence argon ions. The Si–Cl 2 –Ar + system, therefore, exhibits a narrow ALE window. The amount of Si etched per cycle is less than one atomic layer because of the higher etch yield of Cl atoms relative to atomic Si and silicon chlorides. A modified version of the ROM with an artificially increased Si physical sputtering threshold energy expands the ALE window, illustrating the importance of the difference in chemical and physical sputtering threshold energies in the ALE window energy range. The ROM is also used to examine the dependence of the EPC on the Ar + ion fluence.

energy↗
DOE OSTI2018

Structure–Property of Lithium–Sulfur Nanoparticles via Molecular Dynamics Simulation

Lithium-sulfur (Li-S) batteries offer higher energy densities than most reported lithium-ion batteries. However, our understanding of Li-S battery is still largely unknown at the level of the nanoscale. Here, the structural properties of Li-S materials were investigated via molecular dynamics (MD) simulations using the ReaxFF force field. everal Li-S nanoparticles with different Li:S composition ratios (2:1 and 2:8) and various structures are studied. Our MD simulations show that, among the four structures we constructed for Li 2 S 8 nanoparticles, the core-shell structure is the most thermodynamically stable one during the charging (delithiation) process. In contrast to bulk crystal Li 2 S, we find the presence of mixed lithium sulfide and polysulfide species are common features for these Li-S (Li 2 S, Li 2 S 8 ) nanoparticles. The complex distribution of these sulfide and polysulfide speciation are dictated by both stoichiometry and local atomic structures in the nanoparticle. Finally, these findings will provide insight into further development of functionalized lithium-sulfur cathodes.

25 ENERGY STORAGE↗
DOE OSTI2019

Amphiphilic peptide binding on crystalline vs. amorphous silica from molecular dynamics simulations

The leucine-lysine amphiphilic peptide LKα14 has been used to study fundamental driving forces in processes such as peptide-surface binding and biomineralization. Here, we employ molecular dynamics (MD) simulations in tandem with replica exchange metadynamics to probe the binding mechanism and thermodynamics of LKα14 on silica. We also investigate the effect that the nature of the silica surface – crystalline vs. amorphous, has on the binding properties and peptide-surface conformations. We find that water adsorbs differently on both surfaces; it forms a denser interfacial layer on the crystalline surface, compared to the amorphous surface. This causes the peptide to bind more strongly on the amorphous surface than the crystalline surface. Cluster analysis shows that the peptide adopts a helical conformation at both surfaces, with a greater distribution of states on the crystalline surface. Peptide binding is primarily through lysine interactions, in line with prior experimental results.

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

Early stage oxynitridation process of Si(001) surface by NO gas: Reactive molecular dynamics simulation study

Initial stage of oxynitridation process of Si substrate is of crucial importance in fabricating the ultrathin gate dielectric layer of high quality in advanced MOSFET devices. The oxynitridation reaction on a relaxed Si(001) surface is investigated via reactive molecular dynamics (MD) simulation. A total of 1120 events of a single nitric oxide (NO) molecule reaction at temperatures ranging from 300 to 1000 K are statistically analyzed. The observed reaction kinetics are consistent with the previous experimental or calculation results, which show the viability of the reactive MD technique to study the NO dissociation reaction on Si. We suggest the reaction pathway for NO dissociation that is characterized by the inter-dimer bridge of a NO molecule as the intermediate state prior to NO dissociation. Although the energy of the inter-dimer bridge is higher than that of the intra-dimer one, our suggestion is supported by the ab initio nudged elastic band calculations showing that the energy barrier for the inter-dimer bridge formation is much lower. The growth mechanism of an ultrathin Si oxynitride layer is also investigated via consecutive NO reactions simulation. The simulation reveals the mechanism of self-limiting reaction at low temperature and the time evolution of the depth profile of N and O atoms depending on the process temperature, which would guide to optimize the oxynitridation process condition.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Molecular Dynamics Simulations of Uranyl and Uranyl Carbonate Adsorption at Alumino-silicate Surfaces

Adsorption at mineral surfaces is a critical factor controlling the mobility of uranium(VI) in aqueous environments. Therefore, molecular dynamics (MD) simulations were performed to investigate uranyl(VI) adsorption onto two neutral alumino-silicate surfaces, namely the orthoclase (001) surface and the octahedral aluminum sheet of the kaolinite (001) surface. Although uranyl preferentially adsorbed as a bi-dentate innersphere complex on both surfaces, the free energy of adsorption at the orthoclase surface (-15 kcal mol-1) was significantly more favorable than that at the kaolinite surface (-3 kcal mol-1), which was attributed to differences in surface functional groups and to the ability of the orthoclase surface to dissolve a surface potassium ion upon uranyl adsorption. The structures of the adsorbed complexes compared favorably with X-ray absorption spectroscopy results. Simulations of the adsorption of uranyl complexes with up to three carbonate ligands revealed that uranyl complexes coordinated to up to 2 carbonate ions are stable on the orthoclase surface whereas uranyl carbonate surface complexes are unfavored at the kaolinite surface. Combining the MD-derived equilibrium adsorption constants for orthoclase with aqueous equilibrium constants for uranyl carbonate species indicates the presence of adsorbed uranium complexes with one or two carbonates in alkaline conditions, in support of current uranium(VI) surface complexation models.

Environmental Molecular Sciences Laboratory↗