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At least 289 records · Page 16

Effects of Traveling Magnetic Field on Dynamics of Solidification

TMF is based on imposing a controlled phase-shift in a train of electromagnets, forming a stack. Thus, the induced magnetic field can be considered to be travelling along the axis of the stack. The coupling of this traveling wave with an electrically conducting fluid results in a basic flow in a form of a single axisymmetric roll. The magnitude and direction of this flow can be remotely controlled. Furthermore, it is possible to localize the effect of this force field though activating only a number of the magnets. This force field generated in the fluid can, in principle, be used to control and modify convection in the molten material. For example, it can be used to enhance convective mixing in the melt, and thereby modify the interface shape, and macrosegregation. Alternatively, it can be used to counteract thermal and/or solutal buoyancy forces. High frequency TMF can be used in containerless processing techniques, such as float zoning, to affect the very edge of the fluid so that Marangoni flow can be counter balanced. The proposed program consists of basic fundamentals and applications. Our goal in conducting the following experiments and analyses is to establish the validity of TMF as a new tool for solidification processes. Due to its low power consumption and simplicity of design, this tool may find wide spread use in a variety of space experiments. The proposed ground based experiments are intended to establish the advantages and limitations of employing this technique. In the fundamentals component of the proposed program, we will use theoretical tools and experiments with mercury to establish the fundamental aspects of TMF-induced convection through a detailed comparison of theoretical predictions and experimental measurements of flow field. In this work, we will conduct a detailed parametric study involving the effects of magnetic field strength, frequency, wave vector, and the fluid geometry. The applications component of this work will be focused on investigating the effect of TMF on the following solidification and pre-directional solidification processes: (1) Bridgman growth of Ga:Ge with the goal of counteracting the buoyancy-driven convection; (2) Mixing of Pb-Ga and Pb-Sn alloys with the aim of initiating and maintaining a uniform melt prior to solidification processing; and (3) Float Zone growth with the aim of identifying, through simulations and model experiments, conditions needed to counteract Marangoni flow in a microgravity environment. The proposed research has strong relevance to microgravity research and the objectives of the NRA. TMF can provide a unique and accurate mechanism for generation and control of desirable flow patterns for microgravity research. These attributes have significant relevance to 1) Alloy mixing prior to solidification in a microgravity environment. TMF can provide this mixing with a low level of power consumption; (2) TMF can offset the deleterious effects of Marangoni convection in microgravity containerless processing. Thus, TMF can be instrumental in further understanding this phenomena; (3) Generation of controlled flows will allow the investigation of the effect of these flows on growth morphology and growth kinetics; and (4) On Earth, TMF has the potential to significantly counter-balance thermosolutal convection, thereby creating conditions similar to those obtained in microgravity. Once demonstrated, this new tool for use in solidification has the strong potential to find applications in a host of microgravity material research projects.

Mazuruk, Konstantin↗

When more data hurts: Optimizing data coverage while mitigating diversity-induced underfitting in an ultrafast machine-learned potential

Machine-learned interatomic potentials (MLIPs) are becoming an essential tool in materials modeling. However, optimizing the generation of training data used to parametrize the MLIPs remains a significant challenge. This is because MLIPs can fail when encountering local environments too different from those present in the training data. The difficulty of determining a priori the environments that will be encountered during molecular dynamics simulation necessitates diverse, high-quality training data. Here, this study investigates how training data diversity affects the performance of MLIPs using the Ultra-Fast force field (UF 3 ) to model amorphous silicon nitride. We employ expert and autonomously generated data to create the training data and fit four force field variants to subsets of the data. Our findings reveal a critical balance in training data diversity: insufficient diversity hinders generalization, while excessive diversity can exceed the MLIP's learning capacity, reducing simulation accuracy. Specifically, we found that the UF 3 variant trained on a subset of the training data, in which nitrogen-rich structures were removed, offered vastly better prediction and simulation accuracy than any other variant. By comparing these UF 3 variants, we highlight the nuanced requirements for creating accurate MLIPs, emphasizing the importance of application-specific training data to achieve optimal performance in modeling complex material behaviors.

ab initio molecular dynamics↗

Enabling Computational Nanotechnology through JavaGenes in a Cycle Scavenging Environment

A genetic algorithm procedure is developed and implemented for fitting parameters for many-body inter-atomic force field functions for simulating nanotechnology atomistic applications using portable Java on cycle-scavenged heterogeneous workstations. Given a physics based analytic functional form for the force field, correlated parameters in a multi-dimensional environment are typically chosen to fit properties given either by experiments and/or by higher accuracy quantum mechanical simulations. The implementation automates this tedious procedure using an evolutionary computing algorithm operating on hundreds of cycle-scavenged computers. As a proof of concept, we demonstrate the procedure for evaluating the Stillinger-Weber (S-W) potential by (a) reproducing the published parameters for Si using S-W energies in the fitness function, and (b) evolving a "new" set of parameters using semi-empirical tightbinding energies in the fitness function. The "new" parameters are significantly better suited for Si cluster energies and forces as compared to even the published S-W potential.

Globus, Al↗

Structure of water-in-salt and water-in-bisalt electrolytes

We report a systematic diffraction study of two “water-in-salt” electrolytes and a “water-in-bisalt” electrolyte combining high-energy X-ray diffraction (HEXRD) with polarized and unpolarized neutron diffraction (ND) on both H 2 O and D 2 O solutions. The measurements provide three independent combinations of correlations between the different pairs of atom types that reveal the short- and intermediate-range order in considerable detail. The ND interference functions show pronounced peaks around a scattering vector Q ~ 0.5 Å -1 that change dramatically with composition, indicating significant rearrangements of the water network on a length scale around 12 Å. The experimental results are compared with two sets of Molecular Dynamics (MD) simulations, one including polarization effects and the other based on a non-polarizable force field. The two simulations reproduce the general shapes of the experimental structure factors and their changes with concentration, but differ in many detailed respects, suggesting ways in which their force fields might be modified to better represent the actual systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiscale Modeling of Vinyl-Addition Polynorbornenes: The Effect of Stereochemistry

Vinyl-addition polynorbornenes are candidates for designing high-performance polymers due to unique characteristics, which include a high glass transition temperature associated with a rigid backbone. Recent studies have established that the processability and properties of these polymers can be fine-tuned by using targeted substitutions. However, synthesis with different catalysts results in materials with distinct properties, potentially due to the presence of various stereoisomers that are difficult to quantify experimentally. Herein, we develop all-atom models of polynorbornene oligomers based on classical force fields and density functional theory. To establish the relationship between chemical architecture, chain conformations, and melt structure, we perform detailed molecular dynamics simulations with the fine-tuned atomistic force field and propose simpler coarse-grained descriptions to address the high molecular weight limit. All-atom simulations of oligomers suggest high glass transition temperatures in the range of 550–600 K. In the melt state (800 K), meso chains form highly rigid extended coils (C∞≈11) with amorphous structural characteristics similar to the X-ray diffraction data observed in the literature. In contrast, simulations with racemo chains predict highly helical tubular chain conformations that could promote assembly into crystalline structures.

Polymer Science↗

Electrophoresis of small particles and fluid globules in weak electrolytes

An examination is conducted of the influence of partial ionization on the electrophoresis of small particles and fluid globules, with a view to the nature of conditions under which dissociation-association (D-A) alters electrokinetics. It is found that, since D-A processes are important in cases where double-layer polarization and relaxation would otherwise prevail, the predicted effect on electrophoretic mobility is greatest for the drops and bubbles whose surfaces are fluid and convection within the interface is significant. While the computation scheme used applies only to situations where forcing-field magnitude is small, the results obtained indicate that D-A processes involving ionogenic solutes may be significant in apolar liquids where electrokinetic phenomena are driven by strong forcing fields.

Baygents, J. C.↗

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems

Here, we present a perspective on recent progress in machine-learning (ML) force-field approaches for large-scale Landau–Lifshitz–Gilbert (LLG) simulations of metallic spin systems. Building on a generalization of the Behler–Parrinello (BP) architecture originally developed for quantum molecular dynamics, we develop scalable and transferable ML models that faithfully capture the complex, environment-dependent electron-mediated exchange fields characteristic of itinerant magnets. A central ingredient of this framework is the implementation of symmetry-aware magnetic descriptors based on group-theoretical bispectrum formalisms. Leveraging these ML force fields, LLG simulations faithfully reproduce hallmark non-collinear magnetic orders—such as the 120° and tetrahedral states—on the triangular lattice, and successfully capture the complex spin textures emerging in the mixed-phase states of a square-lattice double-exchange model under thermal quench. We further discuss a generalized potential theory that extends the BP formalism to incorporate both conservative and nonconservative electronic torques, thereby enabling ML models to learn nonequilibrium exchange fields from computationally demanding microscopic approaches such as nonequilibrium Green’s-function techniques. This extension yields quantitatively accurate predictions of voltage-driven domain-wall motion and establishes a foundation for quantum-accurate, multiscale modeling of nonequilibrium spin dynamics and spintronic functionalities.

Descriptors↗

Extended Lagrangian Born–Oppenheimer molecular dynamics for orbital-free density-functional theory and polarizable charge equilibration models

We report extended Lagrangian Born–Oppenheimer molecular dynamics (XL-BOMD) is formulated for orbital-free Hohenberg–Kohn density-functional theory and for charge equilibration and polarizable force-field models that can be derived from the same orbital-free framework. The purpose is to introduce the most recent features of orbital-based XL-BOMD to molecular dynamics simulations based on charge equilibration and polarizable force-field models. These features include a metric tensor generalization of the extended harmonic potential, preconditioners, and the ability to use only a single Coulomb summation to determine the fully equilibrated charges and the interatomic forces in each time step for the shadow Born–Oppenheimer potential energy surface. The orbital-free formulation has a charge-dependent, short-range energy term that is separate from long-range Coulomb interactions. This enables local parameterizations of the short-range energy term, while the long-range electrostatic interactions can be treated separately. The theory is illustrated for molecular dynamics simulations of an atomistic system described by a charge equilibration model with periodic boundary conditions. The system of linear equations that determines the equilibrated charges and the forces is diagonal, and only a single Ewald summation is needed in each time step. The simulations exhibit the same features in accuracy, convergence, and stability as are expected from orbital-based XL-BOMD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonlinear force-free magnetic fields

The nonlinear properties of force-free magnetic fields are reviewed with particular reference to the mechanisms for the sudden release of stored energy in flares during the quasi-steady evolution of solar fields. It is shown that in the solar atmosphere, force-free fields with a nonconstant scalar function in the field equations are more likely to occur than those with a constant scalar function, and the nonlinear properties of these fields may give rise to many interesting physical effects. Consideration is then given to two possible mechanisms of field evolution: a model in which a force-free field in a medium of infinite electrical conductivity evolves in response to slowly changing boundary conditions brought about by photospheric motions in the solar active region, and a model in which a field in a medium of small finite electrical conductivity evolves in response to the slow Ohmic dissipation of the electric current.

Low, B. C.↗

Determination of the dispersion constant in a constrained vapor bubble thermosyphon

The isothermal profiles of the extended meniscus in a quartz cuvette were measured in a gravitational field using an image analyzing interferometer which is based on computer enhanced video microscopy of the naturally occurring interference fringes. The experimental results for heptane and pentane menisci were analyzed using the extended Young Laplace Equation. These isothermal results characterized the interfacial force field in-siru at the start of the heat transfer experiments by quantifying the dispersion constant, which is a function of the liquid-solid system and cleaning procedures. The experimentally obtained values of the disjoining pressure and the dispersion constants were compared to that predicted from the DLP theory and good agreements were obtained. The measurements are critical to the subsequent non-isothermal experiments because one of the major variables in the heat sink capability of the Constrained Vapor Bubble Thermosyphon, CVBT, is the dispersion constant. In all previous studies of micro heat pipes the value of the dispersion constant has been 'estimated'. One of the major advantages of the current glass cell is the ability to view the extended meniscus at all times. Experimentally, we find that the extended Young-Laplace Equation is an excellent model for the force field at the solid-liquid-vapor interfaces.

Dasgupta, Sunando↗

Determination of the dispersion constant in a constrained vapor bubble thermosyphon

The isothermal profiles of the extended meniscus in a quartz cuvette were measured in a gravitational field using an image analyzing interferometer which is based on computer enhanced video microscopy of the naturally occurring interference fringes. The experimental results for heptane and pentane menisci were analyzed using the extended Young-Laplace equation. These isothermal results characterized the interfacial force field in-situ at the start of the heat transfer experiments by quantifying the dispersion constant, which is a function of the liquid-solid system and cleaning procedures. The experimentally obtained values of the disjoining pressure and the dispersion constants were compared to that predicted from the DLP theory and good agreements were obtained. The measurements are critical to the subsequent non-isothermal experiments because one of the major variables in the heat sink capability of the CVBT is the dispersion constant. In all previous studies of micro heat pipes the value of the dispersion constant has been 'guesstimated'. One of the major advantages of the current glass cell is the ability to view the extended meniscus at all times. Experimentally. we find that the extended Young-Laplace equation is an excellent model for the force field at the solid-liquid-vapor interfaces.

Dasgupta, SUNANDO.↗

Structure and Dynamics of CO 2 at the Air–Water Interface from Classical and Neural Network Potentials

The accurate description of the structure and dynamics of CO 2 at the instantaneous air–water interface, along with the effects of surface fluctuations on the CO 2 -transport processes, is essential for the development of negative emission technologies aimed at minimizing climate change. In this study, we performed molecular dynamics simulations of CO 2 at the air–water interface using neural network potentials (NNPs) trained on ab initio data generated through density-functional-theory-based molecular dynamics simulations. We compared these results with classical force fields to assess their performance in modeling interfacial CO 2 behavior. Our findings revealed that the asymmetric interactions, coupled with thermal surface fluctuations at the air–water interface, significantly influence CO 2 transport into the aqueous phase. The simulations demonstrate that classical force fields underestimate both the free energy of CO 2 transport and the strength of its interactions at the interface compared with the neural network potentials. In conclusion, the free energy and the interfacial dynamics of CO 2 are primarily influenced by the distribution of water within the instantaneous interfacial water layer, responsible for creating an asymmetric intermolecular interaction environment within the interfacial region.

Ab initio molecular dynamics↗

Polarization Effects in Water-Mediated Selective Cation Transport across a Narrow Transmembrane Channel

We report despite the progress in modeling complex molecular systems of ever-increasing complexity, a quantitatively accurate computational treatment of ion permeation through narrow membrane channels remains challenging. An important factor to reach this goal is induced electronic polarization, which is likely to impact the permeation rate of small ions through narrow molecular pores. In this work, we extended the recently developed polarizable force field based on the classical Drude oscillators to assess the role of induced polarization effects on the energetics of sodium and potassium ion transport across the gramicidin A (gA) ion channel. The inclusion of induced polarization lowers barriers present in 1D potential of mean force (PMF) for cation permeation by ~50% compared to those obtained with the additive force field. Conductance properties calculated with 1D PMFs from Drude simulations are in better agreement with experimental results. Polarization of single-file water molecules and protein atoms forming the narrow pore has a direct impact on the free-energy barriers and cation-specific solid-state NMR chemical shifts. Sensitivity analysis indicates that small changes to water–channel interactions can alter the free energy barrier for ion permeation. These results, illustrating polarization effects present in the complex electrostatic environment of the gA channel, have broad implications for revising proposed mechanisms of ion permeation and selectivity in a variety of ion channels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of Martini 2.2 parameters for N -glycans: a case study of the HIV-1 Env glycoprotein dynamics

N-linked glycans are ubiquitous in nature and play key roles in biology. For example, glycosylation of pathogenic proteins is a common immune evasive mechanism, hampering the development of successful vaccines. Due to their chemical variability and complex dynamics, an accurate molecular understanding of glycans is still limited by the lack of effective resolution of current experimental approaches. Here, we have developed and implemented a reductive model based on the popular Martini 2.2 coarse-grained force field for the computational study of N-glycosylation. We used the HIV-1 Env as a direct applied example of a highly glycosylated protein. Finally, our results indicate that the model not only reproduces many observables in very good agreement with a fully atomistic force field but also can be extended to study large amount of glycosylation variants, a fundamental property that can aid in the development of drugs and vaccines.

59 BASIC BIOLOGICAL SCIENCES↗

Adaptive mass expulsion attitude control system

An attitude control system and method operative with a thruster controls the attitude of a vehicle carrying the thruster, wherein the thruster has a valve enabling the formation of pulses of expelled gas from a source of compressed gas. Data of the attitude of the vehicle is gathered, wherein the vehicle is located within a force field tending to orient the vehicle in a first attitude different from a desired attitude. The attitude data is evaluated to determine a pattern of values of attitude of the vehicle in response to the gas pulses of the thruster and in response to the force field. The system and the method maintain the attitude within a predetermined band of values of attitude which includes the desired attitude. Computation circuitry establishes an optimal duration of each of the gas pulses based on the pattern of values of attitude, the optimal duration providing for a minimal number of opening and closure operations of the valve. The thruster is operated to provide gas pulses having the optimal duration.

Rodden, John J.↗

Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure

Coarse-grained modeling can be used to explore general theories that are independent of specific chemical detail. In this paper, we present cg_openmm, a Python-based simulation framework for modeling coarse-grained hetero-oligomers and screening them for structural and thermodynamic characteristics of cooperative secondary structures. cg_openmm facilitates the building of coarse-grained topology and random starting configurations, setup of GPU-accelerated replica exchange molecular dynamics simulations with the OpenMM software package, and features a suite of postprocessing thermodynamic and structural analysis tools. In particular, native contact analysis, heat capacity calculations, and free energy of folding calculations are used to identify and characterize cooperative folding transitions and stable secondary structures. In this work, we demonstrate the capabilities of cg_openmm on a simple 1–1 Lennard-Jones coarse-grained model, in which each residue contains 1 backbone and 1 side-chain bead. By scanning both nonbonded and bonded force-field parameter spaces at the coarse-grained level, we identify and characterize sets of parameters which result in the formation of stable helices through cooperative folding transitions. Furthermore, we show that the geometries and stabilities of these helices can be tuned by manipulating the force-field parameters.

36 MATERIALS SCIENCE↗

Structure prediction of porous organic crystals

In this work, we explore the possibility of applying automated crystal structure prediction to reproduce the experimentally identified metastable porous polymorphs. Using our recently developed High-Throughput Organic Crystal Structure Prediction ( HTOCSP ) framework, we conducted a systematic study on five representative organic crystalline systems including hydrogen-bonded frameworks (HOFs), featured by the presence of significant porosity, in conjunction with different choices of energy models from classical, machine learning force fields, tight binding to density functional theory. Our results suggest that the current structure generation framework, with careful selection of symmetry conditions, is likely to generate rather complex and abundant metastable crystal candidates for porous crystals. In conjunction with the recent advance in universal machine learning force fields, it becomes possible to identify experimental structures as the energetically favorable candidates from a simple energy versus density analysis, thus paving the way for computational design of complex porous materials with the target systems prior to the experimental synthesis and characterization.

36 MATERIALS SCIENCE↗

Lithium oxidation and electrolyte decomposition at Li-metal/liquid electrolyte interfaces

In this work, we examine the evolution of events occurring when a Li metal surface is in contact with a 2 M solution of a Li salt in a solvent or mixture of solvents, via classical molecular dynamics simulations with a reactive force field allowing bond breaking and bond forming. The main events include Li oxidation and electrolyte reduction along with expansion of the Li surface layers forming a porous phase that is the basis for the formation of the solid-electrolyte interphase (SEI) components. Nucleation of the main SEI components (LiF, Li oxides, and some organics) is characterized. The analysis clearly reveals the details of these physical–chemical events as a function of time, during 20 nanoseconds. The effects of the chemistry of the electrolyte on Li oxidation and dissolution in the liquid electrolyte, and SEI nucleation and structure are identified by testing two salts: LiPF 6 and LiCF 3 SO 3 , and various solvents including ethers and carbonates and mixtures of them. The kinetics and thermodynamics of Li 6 F, the core nuclei in the LiF crystal, are studied by analysis of the MD trajectories, and via density functional theory calculations respectively. The SEI formed in this computational experiment is the “native” film that would form upon contact of the Li foil with the liquid electrolyte. As such, this work is the first in a series of computational experiments that will help elucidate the intricate interphase layer formed during battery cycling using metal anodes.

25 ENERGY STORAGE↗