Search NASA⌕ Search

SEARCH · Search NASA

Results for “Cluster Dynamics Simulations”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Modulating Solvation Structure in Concentrated Aqueous Organic Redox Flow Battery Electrolyte for Solubility and Transport Enhancement via Polycomplex Ion

Aqueous organic redox flow batteries hold great promise as a technology for creating economical grid energy storage using sustainable materials. Nonetheless, the solubility limit presents a universal barrier for all redox-active organic molecules. In this paper, a new approach is proposed to surpass the solubility limit by manipulating the solvation structure with polycomplex ion additives (PIA). Using poly(3,4-ethylenedioxythiophene) polystyrenesulfonate colloids as one example, its role in dismantling the rigid supramolecular clusters within the highly concentrated 7,8-dihydroxyphenazine-2-sulfonic acid electrolyte is investigated. 1 H and 23 Na NMR spectra and molecular dynamics simulation studies demonstrate that the bipolar structure of the PIA effectively disrupts the aggregations of DHPS and Na + ion in the highly concentrated anolyte, thus rendering a more flexible solvation structure and less restrictive ion transport, leading to substantially improved battery performance of an AORFB cell. The anolyte with PIA achieved 1.6 M and 74.3 Ah L –1 anolyte energy capacity.

25 ENERGY STORAGE↗
DOE OSTI2021

Effects of interaction strength of associating groups on linear and star polymer dynamics

A small number of associating groups incorporated onto a polymer backbone have dramatic effects on the mobility and viscoelastic response of the macromolecules in melts. These associating groups assemble, driving the formation of clusters, whose lifetime affects the properties of the polymers. In this study, we probe the effects of the interaction strength on the structure and dynamics of two topologies, linear and star polymer melts, and further investigate blends of associative and non-associating polymers using molecular dynamics simulations. Polymer chains of approximately one entanglement length are described by a bead–spring model, and the associating groups are incorporated in the form of interacting beads with an interaction strength between them that is varied from 1 to 20 k B T. We find that, for all melts and blends, interaction of a few k B T between the associating groups drives cluster formation, where the size of the clusters increases with increasing interaction strength. These clusters act as physical crosslinkers, which slow the chain mobility. Blends of chains with and without associating groups macroscopically phase separate for interaction strength between the associating groups of a few k B T and above. For weakly interacting associating groups, the static structure function S(q) is well fit by functional form predicted by the random phase approximation where a clear deviation occurs as phase segregation takes place, providing a quantitative assessment of phase segregation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Many-body reactive force field development for carbon condensation in C/O systems under extreme conditions

In this paper, we describe the development of a reactive force field for C/O systems under extreme temperatures and pressures, based on the many-body Chebyshev Interaction Model for Efficient Simulation (ChIMES). The resulting model, which targets carbon condensation under thermodynamic conditions of 6500 K and 2.5 g cm –3 , affords a balance between model accuracy, complexity, and training set generation expense. We show that the model recovers much of the accuracy of density functional theory for the prediction of structure, dynamics, and chemistry when applied to dissociative condensed phase systems at 1:1 and 1:2 C:O ratios, as well as molten carbon. Our C/O modeling approach exhibits a 104 increase in efficiency for the same system size (i.e., 128 atoms) and a linear system size scalability over standard quantum molecular dynamics methods, allowing the simulation of significantly larger systems than previously possible. We find that the model captures the condensed-phase reaction-coupled formation of carbon clusters implied by recent experiments, and that this process is susceptible to strong finite size effects. Overall, we find the present ChIMES model to be well suited for studying chemical processes and cluster formation at pressures and temperatures typical of shock waves. We expect that the present C/O modeling paradigm can serve as a template for the development of a broader high pressure–high temperature force-field for condensed phase chemistry in organic materials.

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

The Debye-Waller factor of disordered solids: The case for amorphous silicon

This paper presents a first-principles study of the Debye-Waller factor and the Debye temperature for amorphous silicon (α-Si) from lattice-dynamical calculations and direct molecular-dynamics simulations using density-functional theory (DFT). The effects of temperature and structural disorder on the intensity of the diffraction maxima and the vibrational mean-square displacement (MSD) of Si atoms are studied in the harmonic approximation, with particular emphasis on the bond-length disorder, the presence of coordination defects, and microvoids in α-Si networks. It has been observed that the MSDs associated with tetrahedrally bonded Si atoms are considerably lower than their dangling-bond counterparts—originating from isolated and vacancy-induced clustered defects—and those on the surface of microvoids, leading to an asymmetric non-Gaussian tail in the distribution of atomic displacements. An examination of the effect of anharmonicity on the MSD at high temperatures using direct ab initio molecular-dynamics simulations (without the harmonic approximation) suggests that the vibrational motion in α-Si is practically unaffected by anharmonic effects at temperatures below 400 K, as far as the present DFT calculations are concerned. The Debye temperature of α-Si is found to be in the range of 488–541 K from specific-heat and MSD calculations using first-principles lattice-dynamical calculations in the harmonic approximation, which matches closely with the experimental value of 487–528 K obtained from specific-heat measurements of α-Si at low temperatures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Ab initio studies of the impact of the Debye-Waller factor on the structural and dynamical properties of amorphous semiconductors: The case of a-Si

This paper presents a first-principles study of the Debye-Waller factor and the Debye temperature for amorphous silicon (a-Si) from lattice-dynamical calculations and direct molecular-dynamics simulations using density-functional theory (DFT). The effects of temperature and structural disorder on the intensity of the diffraction maxima and the vibrational mean-square displacement (MSD) of Si atoms are studied in the harmonic approximation, with particular emphasis on the bond-length disorder, the presence of coordination defects, and microvoids in a-Si networks. It has been observed that the MSDs associated with tetrahedrally-bonded Si atoms are considerably lower than their dangling-bond counterparts – originating from isolated and vacancy-induced clustered defects – and those on the surface of microvoids, leading to an asymmetric non-gaussian tail in the distribution of atomic displacements. An examination of the effect of anharmonicity on the MSD at high temperatures using direct ab initio molecular-dynamics simulations (without the harmonic approximation) suggests that the vibrational motion in a-Si is practically unaffected by anharmonic effects at temperatures below 400 K, as far as the present DFT calculations are concerned. The Debye temperature of a-Si is found to be in the range of 488–541 K from specific-heat and MSD calculations using first-principles lattice-dynamical calculations in the harmonic approximation, which matches closely with the experimental value of 487–528 K obtained from specific-heat measurements of a-Si at low temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Early Career: First-Principles Tools for Nonadiabatic Attosecond Dynamics in Materials

The overarching goal of this project was to develop computer tools for predicting how electrons move in molecules and solids at the attosecond (billionth-of-a-billionth of a second) time scale, during and after interaction with intense and/or high energy laser light. An associated goal was to also determine how X-ray spectroscopy could be used as a probe of these dynamics. The project resulted in multiple methodology developments that allow for these processes to be simulated from first-principles, most notably the use of small bulk-mimicking clusters to model solids and fixes for a deficiency in a commonly used method (time-dependent density functional theory). Additionally, the simulations showed that X-ray absorption peaks can be directly related to the electron density above the absorbing atom, and can thus be used as an intuitive probe of "where the electrons are" at a given time in the system. Collectively, these tools and results expected to be valuable for predicting and interpreting future attosecond experiments, especially for X-ray pump/probe studies at free-electron laser facilities.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Crystal nucleation rates in one-component Yukawa systems

Nucleation in the supercooled Yukawa system is relevant for addressing current challenges in understanding a range of crystallizing systems including white dwarf (WD) stars. We use both brute force and seeded molecular dynamics simulations to study homogeneous nucleation of crystals from supercooled Yukawa liquids. With our improved approach to seeded simulations, we obtain quantitative predictions of the crystal nucleation rate and cluster size distributions as a function of temperature and screening length. These quantitative results show trends towards fast nucleation with short-ranged potentials. They also indicate that for temperatures T > 0.9⁢T m , where T m is the melt temperature, classical homogeneous nucleation is too slow to initiate crystallization but transient clusters of ~100 particles should be common. As a result, we apply these general results to a typical WD model and obtain a delay of ~0.6 Gyr in the onset of crystallization that may be observable.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Molecular dynamics simulation of Fe-Si alloys using a neural network machine learning potential

Interatomic potential development using machine learning (ML) approaches has attracted a lot of attention in recent years because these potentials can effectively describe the structural and dynamical properties of complex materials at the atomistic level. Here, in this work, we present the development of a neural network (NN) deep ML interatomic potential for Fe-Si alloys, and we demonstrate the effectiveness of the NN-ML potential in predicting the structures and energies of liquid and crystalline phases of Fe-Si alloys in comparison with the results from ab initio molecular dynamics simulations or experimental data. The developed NN-ML potential is also used to perform molecular dynamics simulations to study the structures of Fe-Si alloys with various compositions under rapid solidification conditions. The short-ranged orders in the rapidly solidified Fe-Si alloys are also analyzed by a cluster alignment method.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Proton Dissociation and Delocalization under Stepwise Hydration of Zeolite HZSM-5

The protonation behavior of zeolite Brønsted acid sites (BAS) in the presence of water is important for the performance of these widely used catalysts. Despite extensive study, the number of water molecules necessary for deprotonation is not well understood, in large part because experiments have been unable to access this information. In this work, we report experimental evidence for full deprotonation of the BAS in the presence of two or more water molecules, with a deprotonation energy of 1.6 kcal/mol. Linear IR absorption and 2D IR spectra were measured over a wide range of controlled hydration levels from 0.5 to 8.0 equivalents of H 2 O/Al at a constant temperature. Distinct spectral signatures of the protonated BAS and excess proton are identified, and their hydration dependence is analyzed quantitatively. Using the experiment as a benchmark, ab initio molecular dynamics simulations are reported that reproduce the experimental trends in the protonation state and IR spectra. The proton charge position and delocalization are quantified in clusters of 1–8 H 2 O molecules using the recently developed rCEC method. This analysis provides insight into the proton structure in confined water clusters, showing that the excess charge remains relatively localized between two oxygen atoms across the hydration range.

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

Reversible motions and disordered structure of soft particles in amorphous solids

In amorphous solids, soft vibrational modes derived from normal mode analysis can be utilized to identify the soft particles that are prone to irreversible rearrangements. However, the normal mode analysis approach cannot explain why the spatial distributions of clustered soft particles do not change over time. We define a softness parameter based on the vibrational density of states calculated directly from molecular dynamics simulations with both the harmonic vibrations and anharmonic relaxations being properly captured at finite temperatures. This parameter spontaneously correlates with the real space atomic motions and the dynamics heterogeneity. Using the softness parameter, we show that the softest particles are confined within rigid cages. These particles keep rearranging reversibly without long-range diffusion. The moderately soft particles rearrange irreversibly, and the hard particles mainly participate in vibrations without rearrangement. Here, we also show that the soft particles form locally disordered structures, while the hard particles present strong ordering. These findings confirm the defective nature of soft particles, and provide insights on the nature of softness as the ability to rearrange, but not necessarily irreversibly.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Infrared Spectroscopy of Li + Solvation in EmimBF 4 and in Propylene Carbonate: Ab Initio Molecular Dynamics and Experiment

Infrared (IR) spectra of solutions of the lithium salt LiBF 4 in the ionic liquid 1-ethyl-3-methylimidazolium tetrafluoroborate (EmimBF 4 ) and in the organic solvent propylene carbonate (PC) are studied via infrared spectroscopy and ab initio molecular dynamics (AIMD) simulations. The measurements show that the major effects of LiBF 4 in both solutions, compared to their neat counterparts, are the appearance of a new broad band in the 300-450 cm -1 frequency region and a broadening of the IR structure in the 900-1200 cm -1 region with the development of a new peak at 980 cm -1 . Computational analysis indicates that hindered translational motions of Li + in its solvation cage are mainly responsible for the former, while the latter is due to Li + -induced structural changes and accompanying vibrational frequency shifts of constituent ions and molecules of the solutions. In addition, molecular motions in these and lower frequency regions are generally correlated, disclosing the collective nature of the vibrational dynamics, which involve multiple ions/molecules. Herein, detailed analysis of these features via AIMD simulations of the spectrum and its components arising from auto- and cross-correlations of motions of constituent molecular species, combined with generalized normal modes of the solutions and normal modes of small Li + -containing clusters, is presented. Furthermore, other minor spectral changes caused by the lithium salt as well as the interaction-induced effect on IR spectra are also discussed.

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

Machine learning–driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins

Significance Here we present an unprecedented multiscale simulation platform that enables modeling, hypothesis generation, and discovery across biologically relevant length and time scales to predict mechanisms that can be tested experimentally. We demonstrate that our predictive simulation-experimental validation loop generates accurate insights into RAS-membrane biology. Evaluating over 100,000 correlated simulations, we show that RAS–lipid interactions are dynamic and evolving, resulting in: 1) a reordering and selection of lipid domains in realistic eight-lipid bilayers, 2) clustering of RAS into multimers correlating with specific lipid fingerprints, 3) changes in the orientation of the RAS G-domain impacting its ability to interact with effectors, and 4) demonstration that RAS–RAS G-domain interfaces are nonspecific in these putative signaling domains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

ELG×LRG Distribution through Dark Matter Halo Dynamics

We investigate the clustering and halo occupation distribution (HOD) of DESI Y1 emission-line (ELGs) and luminous red (LRGs) galaxies at 0.8 < z < 1.1, including their cross-correlation (ELG×LRG), using the A BACUS S UMMIT suite and a new Halo Occupation Model (H OME ) for galaxy multitracers. This integrates intrahalo dynamics, halo exclusion, and quenching, bridging insights from hydrodynamical, HOD, abundance-matching, and semianalytic studies. Leveraging full phase-space information from the Uchuu N-body simulation, and sampling satellites from dark-matter particle positions via physically motivated prescriptions, Home reproduces the anisotropic clustering down to s = 200 h −1 kpc with unprecedented accuracy. Model parameters are inferred solely from two-point statistics using a two-level Bayesian framework, yielding high-fidelity ELG, LRG, and cross-reference catalogs. We find that satellite ELGs behave as incoherent flows within their parent halos, dominating the clustering below 4 h −1 Mpc. The HOD from the best-fit Home has the following properties: (i) 90.50% (85.91%) of ELGs (LRGs) are central galaxies without satellites, residing in halos of M vir ∼ 6.6 × 10 11 (1.2 × 10 13 ) h −1 M ⊙ ; (ii) the ELG×LRG cross-correlation is governed by central-central pairs and shaped by halo exclusion on 2–5 h −1 Mpc scales; (iii) 9.50% (14.09%) of ELGs (LRGs) are satellites, of which 1.09% (3.52%) inhabit halos with a central galaxy of the same species in a maximally conformal configuration, 7.02% (0.005%) orbit complementary hosts in a minimally conformal state, and 0.58% (10.57%) are orphans. The high sensitivity of Home precisely captures the dynamics of satellites in different host environments, opening a promising avenue for understanding systematics and the dynamical nature of dark matter, potentially distinguishing gravity models.

Favole, Ginevra [Universidad de La Laguna (Spain);↗
DOE OSTI2025

Cluster Dynamics Modeling Needs for the Advanced Materials and Manufacturing Technologies Program

This milestone report aims to identify and assess the cluster dynamics (CD) modeling requirements within the Department of Energy's Office of Nuclear Energy (DOE-NE) Advanced Materials and Manufacturing Technologies (AMMT) program and to communicate these needs to the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The goal is to ensure NEAMS is well-informed about the CD modeling requirements to support AMMT's mission of accelerating the development, qualification, demonstration, and deployment of advanced structural materials and manufacturing for nuclear energy applications. CD modeling is an essential tool for predicting the degradation of structural materials under irradiation, which is a key component of AMMT's accelerated qualification process. The AMMT program focuses on both additively manufactured and wrought structural alloys, such as laser powder-bed fusion 316H austenitic stainless steel, alloy 709, Haynes 244, and alloy 617. These materials require a generalized CD modeling framework to facilitate rapid model development and computational simulation. A flexible, generalized CD software, similar to the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, would enable modeling of various cluster types, including defect clusters, defect-solute clusters, and multicomponent clusters, incorporating thermodynamics and kinetics parameters. Radiation effects, microstructural feature evolution, and multi-dimensional modeling are critical considerations for the CD model. The usability of the CD code should allow for easy modification and coupling with MOOSE-based simulations. Additionally, the software should adhere to Nuclear Quality Assurance-1 standards, include a testing suite for verification and validation, and be version-controlled within a national laboratory-managed Git repository. Benchmark problems are needed to assess code predictions and performance.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Chemistry-mediated Ostwald ripening in carbon-rich C/O systems at extreme conditions

Abstract There is significant interest in establishing a capability for tailored synthesis of next-generation carbon-based nanomaterials due to their broad range of applications and high degree of tunability. High pressure (e.g., shockwave-driven) synthesis holds promise as an effective discovery method, but experimental challenges preclude elucidating the processes governing nanocarbon production from carbon-rich precursors that could otherwise guide efforts through the prohibitively expansive design space. Here we report findings from large scale atomistically-resolved simulations of carbon condensation from C/O mixtures subjected to extreme pressures and temperatures, made possible by machine-learned reactive interatomic potentials. We find that liquid nanocarbon formation follows classical growth kinetics driven by Ostwald ripening (i.e., growth of large clusters at the expense of shrinking small ones) and obeys dynamical scaling in a process mediated by carbon chemistry in the surrounding reactive fluid. The results provide direct insight into carbon condensation in a representative system and pave the way for its exploration in higher complexity organic materials. They also suggest that simulations using machine-learned interatomic potentials could eventually be employed as in-silico design tools for new nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Neuromorphic learning with Mott insulator NiO

Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence found in nature in the solid state can serve as inspiration for algorithmic simulations in artificial neural networks and potential use in neuromorphic computing. In this work, we demonstrate nonassociative learning with a prototypical Mott insulator, nickel oxide (NiO), under a variety of external stimuli at and above room temperature. Similar to biological species such as Aplysia, habituation and sensitization of NiO possess time-dependent plasticity relying on both strength and time interval between stimuli. A combination of experimental approaches and first-principles calculations reveals that such learning behavior of NiO results from dynamic modulation of its defect and electronic structure. An artificial neural network model inspired by such nonassociative learning is simulated to show advantages for an unsupervised clustering task in accuracy and reducing catastrophic interference, which could help mitigate the stability–plasticity dilemma. Mott insulators can therefore serve as building blocks to examine learning behavior noted in biology and inspire new learning algorithms for artificial intelligence.

42 ENGINEERING↗
DOE OSTI2023

Graphic contrastive learning analyses of discontinuous molecular dynamics simulations: Study of protein folding upon adsorption

A comprehensive understanding of the interfacial behaviors of biomolecules holds great significance in the development of biomaterials and biosensing technologies. In this work, we used discontinuous molecular dynamics (DMD) simulations and graphic contrastive learning analysis to study the adsorption of ubiquitin protein on a graphene surface. Our high-throughput DMD simulations can explore the whole protein adsorption process including the protein structural evolution with sufficient accuracy. Contrastive learning was employed to train a protein contact map feature extractor aiming at generating contact map feature vectors. Subsequently, these features were grouped using the k-means clustering algorithm to identify the protein structural transition stages throughout the adsorption process. The machine learning analysis can illustrate the dynamics of protein structural changes, including the pathway and the rate-limiting step. Our study indicated that the protein–graphene surface hydrophobic interactions and the π–π stacking were crucial to the seven-stage adsorption process. Upon adsorption, the secondary structure and tertiary structure of ubiquitin disintegrated. The unfolding stages obtained by contrastive learning-based algorithm were not only consistent with the detailed analyses of protein structures but also provided more hidden information about the transition states and pathway of protein adsorption process and structural dynamics. Our combination of efficient DMD simulations and machine learning analysis could be a valuable approach to studying the interfacial behaviors of biomolecules.

97 MATHEMATICS AND COMPUTING↗