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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Integrable Systems on the Tangent Bundle of a Multi-Dimensional Sphere

This paper contains a systematic exposition of some results on the equations of motion of a dynamically symmetric n-dimensional rigid body in a nonconservative field of forces. Similar bodies are considered in the dynamics of actual rigid bodies interacting with a resisting medium under the conditions of jet flow past the body with a nonconservative following force acting on the body in such a way that its characteristic point has a constant velocity, which means that the system has a nonintegrable servo-constraint.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Effect of Temperature and Fluid Flow on Dendrite Growth During Solidification of Al-3 Wt Pct Cu Alloy by the Two-Dimensional Cellular Automaton Method

A two-dimensional cellular automaton–finite volume model was developed to simulate dendrite growth of Al-3 wt pct Cu alloy during solidification to investigate the effect of temperature and fluid flow on dendrite morphology, solute concentration distribution, and dendrite growth velocity. Different calculation conditions that may influence the results of the simulation, including temperature and flow, were considered. The model was also employed to study the effect of different undercoolings, applied temperature fields, and forced flow velocities on solute segregation and dendrite growth. The initial temperature and fluid flow have a significant impact on the dendrite morphologies and solute profiles during solidification. The release of energy is operated with solidification and results in the increase of temperature. A larger undercooling leads to larger solute concentration near the solid/liquid interface and solute concentration gradient at the same time-step. Solute concentration in the solid region tends to increase with the increase of undercooling. Four vortexes appear under the condition when natural flow exists: the two on the right of the dendrite rotate clockwise, and those on the left of the dendrite rotate counterclockwise. With the increase of forced flow velocity, the rejected solute in the upstream region becomes easier to be washed away and enriched in the downstream region, resulting in acceleration of the growth of the dendrite in the upstream and inhibiting the downstream dendrite growth. The dendrite perpendicular to fluid flow shows a coarser morphology in the upstream region than that of the downstream. Almost no secondary dendrite appears during the calculation process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling

The Langevin Dynamics (LD) method (also known in the literature as Brownian Dynamics) is routinely used to simulate aerosol particle trajectories for transport rate constant calculations as well as to understand aerosol particle transport in internal and external fluid flows. This tutorial intends to explain the methodological details of setting up a LD simulation of a population of aerosol particles and to deduce rate constants from an ensemble of classical trajectories. We discuss the applicability and limitations of the translational Langevin equation to model the combined stochastic and deterministic motion of particles in fields of force or fluid flow. The drag force and stochastic “diffusion” force terms that appear in the Langevin equation are discussed elaborately, along with a summary of common forces relevant to aerosol systems (electrostatic, gravity, van der Waals, …); a commonly used first order and a fourth order Runge-Kutta time stepping schemes for linear stochastic ordinary differential equations are presented. A MATLAB® implementation of a LD code for simulating particle settling under gravity using the first order scheme is included for illustration. Scaling analysis of aerosol transport processes and the selection of timestep and domain size for trajectory simulations are demonstrated through two specific aerosol processes: particle diffusion charging and coagulation. Fortran® implementations of the first order and fourth order time-stepping schemes are included for simulating the 3D motion of a particle in a periodic domain. Lastly, potential applications and caveats to the usage of LD are included as a summary.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Peptoid Backbone Flexibilility Dictates Its Interaction with Water and Surfaces: A Molecular Dynamics Investigation

Peptoids are peptide-mimetic biopolymers that are easy-to-synthesize and adaptable for use in drugs, chemical scaffolds, and coatings. However, there is insufficient information about their structural preferences and interactions with the environment in various applications. We conducted a study to understand the fundamental differences between peptides and peptoids using molecular dynamics simulations with semi-empirical (PM6) and empirical (AMBER) potentials, in conjunction with metadynamics enhanced sampling. From studies of single molecules in water and on surfaces, we found that sarcosine (model peptoid) is much more flexible than alanine (model peptide) in different environments. However, the sarcosine and alanine interact similarly with a hydrophobic or a hydrophilic. Finally, this study highlights the conformational landscape of peptoids and the dominant interactions that drive peptoids towards these conformations. ACKNOWLEDGMENT: MD simulations and manuscript preparation were supported by the MS3 (Materials Synthesis and Simulation Across Scales) Initiative at Pacific Northwest National Laboratory (PNNL), a multi-program national laboratory operated by Battelle for the U.S. Department of Energy. CJM was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences Division of Chemical Sciences, Geosciences, and Biosciences. MDB was supported by the US Department of Energy, Office of Basic Energy Sciences, Biomolecular Materials Program at PNNL. Computing resources were generously allocated by University of Washington's IT department and PNNL's Institutional Computing program. The authors greatly acknowledge conversations with Dr. Kayla Sprenger, Josh Smith, and Dr. Yeneneh Yimer.

alanine↗
DOE OSTI2018

Higher-Order Extended Lagrangian Born–Oppenheimer Molecular Dynamics for Classical Polarizable Models

Generalized extended Lagrangian Born-Oppenheimer molecular dynamics (XLBOMD) methods provide a framework for fast iteration-free simulations of models that normally require expensive electronic ground state optimizations prior to the force evaluations at every time step. XLBOMD uses dynamically driven auxiliary degrees of freedom that fluctuate about a variationally optimized ground state of an approximate “shadow” potential which approximates the true reference potential. While the requirements for such shadow potentials are well understood, constructing such potentials in practice has previously been ad hoc, and in this work, we present a systematic development of XLBOMD shadow potentials that match the reference potential to any order. We also introduce a framework for combining friction-like dissipation for the auxiliary degrees of freedom with general-order integration, a combination that was not previously possible. These developments are demonstrated with a simple fluctuating charge model and point induced dipole polarization models.

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

Modeling Equilibrium Solid–Liquid Interfaces under Effective Constant Chemical Potential Using Machine Learning Interatomic Potentials

The chemical potential (μ) of species in solution is essential for understanding various chemical processes at interfaces. Molecular dynamics (MD) simulations, constrained by fixed compositions, cannot maintain constant chemical potential with reference to a targeted concentration or chemical potential under nonequilibrium or dynamic conditions, as solute species can migrate to the interface and deplete (or enrich) the bulk due to solute-interface interactions. In this study, we introduce a simple and computationally efficient approach named iterative quasi-constant chemical potential molecular dynamics (iqCμMD) simulation, which helps simulate targeted molar concentrations of species in solution. iqCμMD overcomes the limitations of conventional MD by adjusting the number of species in the solution to reach a target bulk concentration (chemical potential), which allows simulation of the interface under the bulk conditions comparable to experiment. We demonstrate our approach using machine learning interatomic potential (MLIP)-based MD simulations of the Na 2 SO 4,aq –graphene interface, and to show the transferability of our approach, we also perform classical force field-based MD simulations of NaCl aq –air and NaCl aq –graphite interfaces, which produce comparable results to previous CμMD simulations. Our results also show that the iqCμMD approach efficiently achieves the desired bulk ion concentration within two iterations, and by utilizing MLIPs, we can achieve converged results using relatively small-scale simulations compared to previous CμMD simulations. By combining iqCμMD with MLIP-driven simulations, solid–liquid interfaces can be modeled under an effective constant chemical potential with DFT-level accuracy. Here, we show that iqCμMD offers a robust and simple computational framework for constant chemical potential simulations, as its only requirement is to be able to converge interfacial simulations with a measurable bulk region.

Chemical structure↗
DOE OSTI2022

Nucleation Rate Theory for Coordination Number: Elucidating Water-Mediated Formation of a Zigzag Na 2 SO 4 Morphology

Predicting and controlling nanostructure formation during nucleation can pave the way to synthesizing novel energy materials via crystallization. However, such control over nucleation and crystallization remains challenging due to an inadequate understanding of critical factors that govern evolving atomistic structures and dynamics. Here, in this paper, we utilize coordination number as a reaction coordinate and rate theory to investigate how sodium sulfate, commonly known as a phase-change energy material, nucleates in a supersaturated aqueous solution. In conjunction with ab initio and force field-based molecular dynamics simulation, the rate theoretical analysis reveals that sodium sulfate from an initially dissolved metastable state transits to a heterogeneous mixture of prenucleated clusters and finally to a large cylindrical zigzag morphology. Measurements of Raman spectra and their ab initio modeling confirm that this nucleated morphology contains a few waters for every sulfate. Rate processes such as solvent exchange and desolvation exhibit high sensitivity to the evolving prenucleation/nucleation structures, providing a means to distinguish between critical nucleation precursors. Desolvation and forming the first-shell interionic coordination structure via monomer-by-monomer addition around sulfates are found to explain the formation of large nuclei. Thus, a detailed understanding of the step-by-step structure formation across scales has been achieved. This can be leveraged to predict nucleation-related structures and dynamics and potentially control the synthesis of novel phase-change materials for energy applications.

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

Effects of interlayer confinement and hydration on capacitive charge storage in birnessite

Nanostructured birnessite exhibits high specific capacitance and nearly ideal capacitive behaviour in aqueous electrolytes, rendering it an important electrode material for low-cost, high-power energy storage devices. The mechanism of electrochemical capacitance in birnessite has been described as both Faradaic (involving redox) and non-Faradaic (involving only electrostatic interactions). To clarify the capacitive mechanism, we characterized birnessite’s response to applied potential using ex situ X-ray diffraction, electrochemical quartz crystal microbalance, in situ Raman spectroscopy and operando atomic force microscope dilatometry to provide a holistic understanding of its structural, gravimetric and mechanical responses. These observations are supported by atomic-scale simulations using density functional theory for the cation-intercalated structure of birnessite, ReaxFF reactive force field-based molecular dynamics and ReaxFF-based grand canonical Monte Carlo simulations on the dynamics at the birnessite–water–electrolyte interface. We show that capacitive charge storage in birnessite is governed by interlayer cation intercalation. We conclude that the intercalation appears capacitive due to the presence of nanoconfined interlayer structural water, which mediates the interaction between the intercalated cation and the birnessite host and leads to minimal structural changes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Microporous water with high gas solubilities

Liquids with permanent microporosity can absorb larger quantities of gas molecules than conventional solvents , providing new opportunities for liquid-phase gas storage, transport, and reactivity. Current approaches to designing porous liquids rely on sterically bulky solvent molecules or surface ligands and thus are not amenable to many important solvents, including water. Here, we report a generalizable thermodynamic strategy to preserve permanent microporosity and impart high gas solubilities to liquid water. Specifically, we show how the external and internal surface chemistry of microporous zeolite and metal–organic framework nanocrystals can be tailored to promote the formation of stable dispersions in water while maintaining dry networks of micropores that are accessible to gas molecules. As a result of their permanent microporosity, these aqueous fluids can concentrate gases, including oxygen (O 2 ) and carbon dioxide (CO 2 ), to much higher densities than are found in typical aqueous environments. Furthermore, when these fluids are oxygenated, record-high capacities of O 2 can be delivered to hypoxic red blood cells, highlighting one potential application of this new class of microporous liquids for physiological gas transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Polymer encapsulated microcavity optomechanical magnetometer

We demonstrate a magnetometer using polymer encapsulated whispering-gallery-mode microcavity actuated by a micro-magnet. The magnetic field induces force on the micro-magnet causing deformation in the polymer around the microcavity. Subsequently the microcavity detects the change in the refractive index of the polymer resulted from the deformation. This magnetometer works in the frequency range of hertz-to-kilohertz range and achieves a sensitivity of 880 pT/Hz 1/2 at 200 Hz in a micro-scale sensor volume. Polymer encapsulation of the magnetometer and fiber optical connection ensures environmental robustness and practicality of the sensor.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Condensation and growth of amorphous aluminosilicate nanoparticles via an aggregation process

The precipitation of zeolite nanoparticles involves the initial formation of metastable precursors, such as amorphous entities, that crystallize through non-classical pathways. Here, using reactive force field-based simulations, we reveal how aluminosilicate oligomers grow concomitantly to the decondensation of silicate entities during the initial step of the reaction. Aluminate clusters first form in the solution, thus violating the Loewenstein rule in the first instant of the reaction, which is then followed by their connection with silicate oligomers at the terminal silanol groups before reorganization to finally diffuse within the silicate oligomers to form stable amorphous aluminosilicate nanoparticles that do obey the Loewenstein rule. Our results clearly indicate that aluminate does not serve as the nucleation center for the growth of aluminosilicates in a nucleation-like process but rather proceeds via an aggregation process. Furthermore, the coexistence of aluminosilicate oligomers and small silicate entities induces a phase separation that promotes the precipitation of zeolites with aging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An Entropy-Maximization Approach to Automated Training Set Generation for Interatomic Potentials

Machine learning-based interatomic potentials are currently garnering a lot of attention as they strive to achieve the accuracy of electronic structure methods at the computational cost of empirical potentials. Given their generic functional forms, the transferability of these potentials is highly dependent on the quality of the training set, the generation of which can be highly labor-intensive. Good training sets should at once contain a very diverse set of configurations while avoiding redundancies that incur cost without providing benefits. We formalize these requirements in a local entropy-maximization framework and propose an automated sampling scheme to sample from this objective function. We show that this approach generates much more diverse training sets than unbiased sampling and is competitive with hand-crafted training sets.

74 ATOMIC AND MOLECULAR PHYSICS↗