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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multiscale Molecular Dynamics Simulations: Accelerating Conformational Sampling of Biomolecular Systems by Iterating All-Atom and Coarse-Grained Simulations

We developed the atomistic-coarse-grained multiscale MD simulation method in the OpenMM simulation package by iterating between the all-atom (AA) and coarse-grained (CG) MD simulations to enhance the sampling of biomolecular conformations. As the free energy surfaces are flattened during CG MD simulations, we can accelerate the transitions between different low-energy conformations. The AA-CG-AA cycles are repeated, facilitating the accelerated sampling of biomolecular conformations at a CG level, while the finer atomistic interactions are refined with AA simulators.

Do, Hung Nguyen↗
DOE OSTI2021

Berni Julian Alder, theoretical physicist and inventor of molecular dynamics, 1925–2020

Berni Julian Alder, one of the leading figures in the invention of molecular dynamics simulations used for a wide array of problems in physics and chemistry, died on September 7th, 2020. His career, spanning more than 65 years, transformed statistical mechanics, many body physics, the study of chemistry and the microscopic dynamics of fluids, by making atomistic computational simulation (in parallel with traditional theory and experiment) a new pathway to unexpected discoveries. Among his many honors, the CECAM prize, recognizing exceptional contributions to the simulation of the microscopic properties of matter is named for him. He was awarded the National Medal of Science by President Obama in 2008.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Grazing Incidence Wide-Angle X-ray Scattering of Water Adsorption in Polyamide Barrier Layers of Reverse Osmosis Membranes

To understand the relationship between the intermolecular structure of aromatic polyamide (PA) scaffold and the water molecules in the barrier layers of reverse osmosis (RO) membranes, a grazing incidence wide-angle X-ray scattering (GIWAXS) study was carried out on freestanding PA thin films at varying relative humidity (RH) conditions. The scattering results were analyzed by an interference scattering model, containing a phase factor between a PA chain and an adsorbed water molecule. This model yielded good fits to the GIWAXS profiles where the water adsorption was found to vary linearly with RH. Atomistic molecular dynamics (MD) simulations were also performed to complement the experimental study. Furthermore, the simulations revealed that a rapid condensation layer initially formed on the PA film surface, followed by the slow water molecule diffusion inside the PA membrane. Sparse adsorbed water, isolated in subnanopores of the PA film adjacent to the polar atoms, even in very low quantities, modifies the X-ray scattering. Atomistic simulations at the microscopic scale provide partial support for several X-ray scattering findings.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A new self-adaptive reconstruction method to identify defects through Wigner–Seitz approach

A new self-adaptive reconstruction method based on local atomic structure at any given molecular dynamics (MD) step has been developed in this article. The method can be used in Wigner–Seitz defect analysis approach to correctly and efficiently explore the information of both point defects and complex defect clusters (e.g. dislocation loops and voids) formed after a displacement cascade where the cascade interacts with grain boundaries and/or dislocations. The algorithm and validation are provided in detail. Results for identification of radiation defects during and after cascades interacting with a dislocation network show that the new method can well recognize all simple and complex defects and defect clusters. Thus, this new method provides a totally new way to explore the density and size of radiation defects at atomic scale after complex MD evolution processes, providing correct information to understand and predict radiation damage in materials through atomic simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Sorption-induced polymer rearrangement: approaches from molecular modeling

With the growing need for chemical separation and chemical storage solutions, polymeric adsorbents have emerged as a promising class of candidate materials because of their potentially tunable sorption properties, membrane structure and relatively cost consciousness. Moreover, the developing field of polymeric membrane materials has shown particular success at integrating both experimental and computational studies. However, these material systems are known to suffer from varying degrees of induced membrane structural rearrangement upon adsorbate uptake, and thus many polymeric membrane performance metrics are often considered to degrade with an increasing number of ‘guest’ species. In this mini–review, we highlight methodology tradeoffs and provide insights into atomistic molecular simulations used to study adsorption with flexible frameworks, which have the potential to predict separation, storage or catalytic capabilities a priori to experimental efforts. Specifically, molecular simulation methods that have been applied to provide predictions of polymeric membrane properties that have included consideration for sorbate–induced polymer chain rearrangement, swelling and/or plasticization are reviewed. Here, the examples and methodologies described provide demonstrations of the applicability of simulations as an approach to understand adsorption–based phenomena at an atomistic/molecular level, and as a tool to carry out screening studies aimed at efficiently providing analysis for a diversity of polymeric adsorbent–adsorbate systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Membrane interactions of the globular domain and the hypervariable region of KRAS4b define its unique diffusion behavior

The RAS proteins are GTP-dependent switches that regulate signaling pathways and are frequently mutated in cancer. RAS proteins concentrate in the plasma membrane via lipid-tethers and hypervariable region side-chain interactions in distinct nano-domains. However, little is known about RAS membrane dynamics and the details of RAS activation of downstream signaling. Here, we characterize RAS in live human and mouse cells using single-molecule-tracking methods and estimate RAS mobility parameters. KRAS4b exhibits confined mobility with three diffusive states distinct from the other RAS isoforms (KRAS4a, NRAS, and HRAS); and although most of the amino acid differences between RAS isoforms lie within the hypervariable region, the additional confinement of KRAS4b is largely determined by the protein’s globular domain. To understand the altered mobility of an oncogenic KRAS4b, we used complementary experimental and molecular dynamics simulation approaches to reveal a detailed mechanism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Predicting thermophysical properties of molten salts in the MgCl 2 -NaCl-KCl-LiCl system with a shell-model potential

Ternary eutectic salts composed of MgCl 2 , NaCl, and KCl, referred to as MNK salts, have recently emerged as promising candidates as high-temperature heat transfer fluids and thermal energy storage media. Here we performed classical molecular dynamics (MD) simulations to predict the densities, specific heat capacities, viscosities, and ionic self-diffusivities for MNK salts over a wide temperature range. The impact of LiCl additive on their thermophysical properties was also investigated. To capture the electronic polarization of Cl anions by neighboring cations, we developed a novel shell-model potential using the force-matching method and a dataset of ab initio calculated interatomic forces. Our extensive MD simulations predict structure and properties for pure salts and binary/ternary salt mixtures in the MgCl 2 -NaCl-KCl-LiCl system in overall good agreement with available experimental and theoretical data, which corroborates the accuracy and reliability of our developed potential.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Grain boundary solute segregation across the 5D space of crystallographic character

Solute segregation in materials with grain boundaries (GBs) has emerged as a popular method to thermodynamically stabilize nanocrystalline structures. However, the impact of varied GB crystallographic character on solute segregation has never been thoroughly examined. Here, this work examines Co solute segregation in a dataset of 7272 Al bicrystal GBs that span the 5D space of GB crystallographic character. Considerable attention is paid to verification of the calculations in the diverse and large set of GBs. In addition, the results of this work are favorably validated against similar bicrystal and polycrystal simulations. As with other work, we show that Co atoms exhibit strong segregation to sites in Al GBs and that segregation correlates strongly with GB energy and GB excess volume. Segregation varies smoothly in the 5D crystallographic space but has a complex landscape without an obvious functional form.

36 MATERIALS SCIENCE↗
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↗
DOE OSTI2025

Breaking the mold: Overcoming the time constraints of molecular dynamics on general-purpose hardware

The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved with computing power along the three principal dimensions of accuracy, atom count (spatial scale), and duration (temporal scale). Since the mid-2000s, computer platforms have, however, failed to provide strong scaling for MD, as scale-out central processing unit (CPU) and graphics processing unit (GPU) platforms that provide substantial increases to spatial scale do not lead to proportional increases in temporal scale. Important scientific problems therefore remained inaccessible to direct simulation, prompting the development of increasingly sophisticated algorithms that present significant complexity, accuracy, and efficiency challenges. While bespoke MD-only hardware solutions have provided a path to longer timescales for specific physical systems, their impact on the broader community has been mitigated by their limited adaptability to new methods and potentials. In this work, we show that a novel computing architecture, the Cerebras wafer scale engine, completely alters the scaling path by delivering unprecedentedly high simulation rates up to 1.144 M steps/s for 200 000 atoms whose interactions are described by an embedded atom method potential. This enables direct simulations of the evolution of materials using general-purpose programmable hardware over millisecond timescales, dramatically increasing the space of direct MD simulations that can be carried out. In this paper, we provide an overview of advances in MD over the last 60 years and present our recent result in the context of historical MD performance trends.

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

Unveiling the effect of Ni on the formation and structure of Earth’s inner core

Ni is the second most abundant element in the Earth’s core. Yet, its effects on the inner core’s structure and formation process are usually disregarded because of its electronic and size similarity with Fe. Using ab initio molecular dynamics simulations, we find that the bcc phase can spontaneously crystallize in liquid Ni at temperatures above Fe’s melting point at inner core pressures. The melting temperature of Ni is shown to be 700 to 800 K higher than that of Fe at 323 to 360 GPa. hcp, bcc, and liquid phase relations differ for Fe and Ni. Ni can be a bcc stabilizer for Fe at high temperatures and inner core pressures. A small amount of Ni can accelerate Fe’s crystallization at core pressures. These results suggest that Ni may substantially impact the structure and formation process of the solid inner core.

58 GEOSCIENCES↗
DOE OSTI2026

Investigation of the Effect of Framework Flexibility on Adsorption in SIFSIX-3-Cu using a Machine-Learned Force Field

Metal-organic frameworks (MOFs) are a promising class of adsorbents. The performance of MOF sorbents relies on high selectivity and low regeneration energy. This work focuses on the use of machine learned force fields (MLFFs) to model adsorption in a flexible MOF, SIFSIX-3-Cu. A DeePMD-based MLFF was trained to reproduce DFT (PBE+D3) energies, forces, and stresses, using an iterative sampling scheme combining sampling based on molecular dynamics, Monte Carlo, and geometry optimization to capture both attractive and repulsive regions of the potential energy surface. Flexibility of the MOF was explicitly included in this model. Hybrid Monte Carlo/molecular dynamics (MC/MD) simulations using the MLFF predicted adsorption isotherms in good agreement with experimental data for a range of pressures (40 Pa – 104 Pa) in contrast to rigid models, which overpredict CO2 adsorption at low pressures. The improvement was the result of a description of the variability of fluorine-fluorine diagonal distances at adsorption sites. This detailed description of flexibility afforded by the MLFF resulted in more accurate predictions adsorption isotherms when compared to the experimentally measured values. These results underscore the importance of including framework flexibility when modeling adsorption phenomena in MOFs, particularly for low pressure applications and provide a robust procedure for training MLFF models for MOFs.

Atomistic Simulation↗
DOE OSTI2022

Molecular-based analysis of nanoparticle solvation: Classical density functional approach

Proper statistical mechanics understanding of nanoparticle solvation processes requires an accurate description of the molecular structure of the solvent. Achieving this goal with standard molecular dynamics (MD) simulation methods is challenging due to large length scales. An alternative approach to this problem can be formulated using classical density functional theory (cDFT), where a full configurational description of the positions of all the atoms is replaced by collective atomic site densities in the molecule. Using an example of the negatively charged silica-like system in an aqueous polar environment represented by a two-site water model, we demonstrate here that cDFT can reproduce MD data at a fraction of the computational cost. An important implication of this result is the ability to understand how the solvent molecular features may affect the system’s properties at the macroscopic scale. A concrete example highlighted in this work is the analysis of nanoparticle interactions with sizes of up to 100 nm in diameter.

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

Atomistic modeling of metal–nonmetal interphase boundary diffusion

Atomistic computer simulations are applied to investigate the atomic structure, thermal stability, and diffusion processes in Al–Si interphase boundaries as a prototype of metal–ceramic interfaces in composite materials. Some of the most stable orientation relationships between the phases found in this work were previously observed in epitaxy experiments. Here, a non-equilibrium interface can transform to a more stable state by a mechanism that we call interface-induced recrystallization. Diffusion of both Al and Si atoms in stable Al–Si interfaces is surprisingly slow compared with diffusion of both elements in Al grain boundaries but can be accelerated in the presence of interface disconnections. A qualitative explanation of the sluggish interphase boundary diffusion is proposed. Atomic mechanisms of interphase boundary diffusion are similar to those in metallic grain boundaries and are dominated by correlated atomic rearrangements in the form of strings and rings of collectively moving atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Hall–Petch strengthening limit through partially active segregation in nanocrystalline Ag-Cu alloys

The breakdown from grain-size strengthening to softening mechanisms is generally well understood for high-purity nanocrystalline materials when the mean grain size decreases to the nanometer range. In nanocrystalline alloys, however, the stabilization of nanosized grains by grain-boundary solute segregation complicates the above mechanisms. Moreover, current segregation models have little predictive power for determining the optimal solute content that maximizes Hall-Petch strengthening effects. In this article, using large-scale hybrid Monte-Carlo/molecular dynamic simulations, we present a systematic study of the Hall–Petch breakdown in Cu-segregated Ag alloys with grain sizes ranging from 8 nm to 59 nm, where three concentration-dependent regimes of plasticity are described: (1) Classical segregation strengthening behavior at low solute contents, (2) shear band-induced softening at high solute contents, and (3) a previously unknown, but extended plateau of maximum strengths for intermediate solute contents from 4 to 15 at.%, which we term as nanocrystalline Sterling silver. We find that flow strengths in nanocrystalline Sterling alloys naturally exhibit a zero-slope limit at the smallest grain sizes that is well below the ideal Hall–Petch strengthening trend. This phenomenon results from partially active grain-boundary segregation that acts to influence interfacial plasticity in some, but not all, grain boundary regions. Our findings amplify the atomic nature of solute segregation and interaction at grain boundaries and its complex roles on grain boundary-mediated plasticity mechanisms in nanocrystalline alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Melatonin-Induced Modulation of Cholesterol-Enriched Model Neuronal Membranes

Melatonin, a hormone primarily produced by the brain’s pineal gland, not only regulates circadian rhythms, but also influences the structural and biophysical properties of neuronal membranes. Its amphiphilic nature enables direct incorporation into lipid bilayers and preferential interactions with cholesterol-rich lipid rafts, critical hubs for cellular signaling and membrane organization. Despite increasing recognition of its membrane activity, the molecular basis of melatonin’s interactions with coexisting liquid-ordered (L o ) and liquid-disordered (L d ) phases remains unclear. Here, in this study, we combine small-angle neutron scattering (SANS) and all-atom molecular dynamics simulations to examine model neuronal membranes composed of DSPC, DOPC, POPC, and cholesterol. Our results show that melatonin preserves domain morphology while adopting distinct orientations within the bilayer and at the membrane interface, allowing both lateral and transmembrane bridging across lipid phases. These findings establish the molecular underpinnings of melatonin’s modulation of membrane heterogeneity and provide strong support for its receptor-independent actions.

atomistic simulations↗
DOE OSTI2021

Segregation competition and complexion coexistence within a polycrystalline grain boundary network

Interfacial segregation can stabilize grain structures and even lead to grain boundary complexion transitions. However, understanding of the complexity of such phenomena in polycrystalline materials is limited, as most studies focus on bicrystal geometries. In this work, we investigate interfacial segregation and subsequent complexion transitions in polycrystalline Cu-Zr alloys using hybrid Monte Carlo/molecular dynamics simulations. No significant change in the grain size or structure is observed upon Zr dopant addition to a pure Cu polycrystal at moderate temperature, where grain boundary segregation is the dominant behavior. Segregation within the boundary network is inhomogeneous, with some boundaries having local concentrations that are an order of magnitude larger than the global value and others having almost no segregation, and changes to physical parameters such as boundary free volume and energy are found to correlate with dopant concentration. Further, another alloy sample is investigated at a higher temperature to probe the occurrence of widespread transitions in interfacial structure, where a significant fraction of the originally ordered boundaries transition to amorphous complexions, demonstrating the coexistence of multiple complexion types, each with their own distribution of boundary chemical composition. Overall, this work highlights that interfacial segregation and complexion structure can be diverse in a polycrystalline network. Here, the findings shown here complement existing computational and experimental studies of individual interfaces and help pave the way for unraveling the complexity of interfacial structure in realistic microstructures.

36 MATERIALS SCIENCE↗