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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Self-assembly and glass-formation in a lattice model of telechelic polymer melts: Influence of stiffness of the sticky bonds

Telechelic polymers are chain macromolecules that may self-assemble through the association of their two mono-functional end groups (called “stickers”). A deep understanding of the relation between microscopic molecular details and the macroscopic physical properties of telechelic polymers is important in guiding the rational design of telechelic polymer materials with desired properties. The lattice cluster theory (LCT) for strongly interacting, self-assembling telechelic polymers provides a theoretical tool that enables establishing the connections between important microscopic molecular details of self-assembling polymers and their bulk thermodynamics. The original LCT for self-assembly of telechelic polymers considers a model of fully flexible linear chains [J. Dudowicz and K. F. Freed, J. Chem. Phys. 136, 064902 (2012)], while our recent work introduces a significant improvement to the LCT by including a description of chain semiflexibility for the bonds within each individual telechelic chain [W.-S. Xu and K. F. Freed, J. Chem. Phys. 143, 024901 (2015)], but the physically associative (or called “sticky”) bonds between the ends of the telechelics are left as fully flexible. Motivated by the ubiquitous presence of steric constraints on the association of real telechelic polymers that impart an additional degree of bond stiffness (or rigidity), the present paper further extends the LCT to permit the sticky bonds to be semiflexible but to have a stiffness differing from that within each telechelic chain. An analytical expression for the Helmholtz free energy is provided for this model of linear telechelic polymer melts, and illustrative calculations demonstrate the significant influence of the stiffness of the sticky bonds on the self-assembly and thermodynamics of telechelic polymers. A brief discussion is also provided for the impact of self-assembly on glass-formation by combining the LCT description for this extended model of telechelic polymers with the Adam-Gibbs relation between the structural relaxation time and the configurational entropy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Strong bonds and far-from-equilibrium conditions minimize errors in lattice-gas growth

We use computer simulation to study the layer-by-layer growth of particle structures in a lattice gas, taking the number of incorporated vacancies as a measure of the quality of the grown structure. A dynamic scaling relation describes the quality of structures in and out of equilibrium and reveals that the highest-quality structures are obtained, for fixed observation time, using strong interactions and far-from-equilibrium growth conditions. This result contrasts with the usual assumption that weak interactions and mild nonequilibrium conditions are the best way to minimize errors during assembly.

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

Structure and dynamics of hydrodynamically interacting finite-size Brownian particles in a spherical cavity: Spheres and cylinders

The structure and dynamics of confined suspensions of particles of arbitrary shape are of interest in multiple disciplines from biology to engineering. Theoretical studies are often limited by the complexity of long-range particle-particle and particle-wall forces, including many-body fluctuating hydrodynamic interactions. Here, we report a computational study on the diffusion of spherical and cylindrical particles confined in a spherical cavity. We rely on an immersed-boundary general geometry Ewald-like method to capture lubrication and long-range hydrodynamics and include appropriate non-slip conditions at the confining walls. A Chebyshev polynomial approximation is used to satisfy the fluctuation-dissipation theorem for the Brownian suspension. We explore how lubrication, long-range hydrodynamics, particle volume fraction, and shape affect the equilibrium structure and the diffusion of the particles. It is found that once the particle volume fraction is greater than 10%, the particles start to form layered aggregates that greatly influence particle dynamics. Hydrodynamic interactions strongly influence the particle diffusion by inducing spatially dependent short-time diffusion coefficients, stronger wall effects on the particle diffusion toward the walls, and a sub-diffusive regime-caused by crowding-in the long-time particle mobility. The level of asymmetry of the cylindrical particles considered here is enough to induce an orientational order in the layered structure, decreasing the diffusion rate and facilitating a transition to the crowded mobility regime at low particle concentrations. Our results offer fundamental insights into the diffusion and distribution of globular and fibrillar proteins inside cells.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Microscopic-macroscopic level densities for low excitation energies

Level density ρ(E,Q) is derived within the micro-macroscopic approximation (MMA) for a system of strongly interacting Fermi particles with the energy E and additional integrals of motion Q , in line with several topics of the universal and fruitful activity of A. S. Davydov. Within the extended Thomas Fermi and semiclassical periodic orbit theory beyond the Fermi-gas saddle-point method, we obtain ρ ∝ I ν (S)/S ν , where I ν (S) is the modified Bessel function of the entropy S . For small shell-structure contribution, one finds ν = κ/2 + 1, where κ is the number of additional integrals of motion. This integer number is a dimension of Q, Q = { N, Z , …} for the case of two-component atomic nuclei, where N and Z are the numbers of neutrons and protons, respectively. For much larger shell structure contributions, one obtains ν = κ /2 + 2. The MMA level density ρ reaches the well-known Fermi gas asymptote for large excitation energies and the finite micro-canonical combinatoric limit for low excitation energies. Further, the additional integrals of motion can also be the projection of the angular momentum of a nuclear system for nuclear rotations of deformed nuclei, number of excitons for collective dynamics, and so on. Fitting the MMA total level density ρ( E , Q) for a set of the integrals of motion Q = { N, Z }, to experimental data on a long nuclear isotope chain for low excitation energies, one obtains the results for the inverse level-density parameter K , which differs significantly from those of neutron resonances due to shell, isotopic asymmetry, and pairing effects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Excited nucleon spectrum and structure studies with CLAS and CLAS12

The study of the spectrum and structure of excited nucleon states employing the electroproduction of exclusive reactions is an important avenue for exploring the nature of the non-perturbative strong interaction. The CLAS detector in Hall B has provided the dominant part of the available world data on most relevant meson electroproduction channels off the nucleon in the resonance region for Q2 up to 5 GeV2. Analyses of CLAS data for the exclusive channels πN, ηN, and π+π-p on a proton target have provided the only results available on the Q2 evolution of the electro-excitation amplitudes for the transitions from the initial photon-proton to the final N* states in the mass range up to W =1.8 GeV. These electrocouplings allow for exploration of the internal structure of the produced excited nucleon states. This work has made it clear that consistent results from independent analyses of several exclusive channels with different resonance hadronic decay parameters and non-resonant backgrounds but the same N* electro-excitation amplitudes, is essential to have confidence in the extracted results. Starting in early 2018, a program to study the spectrum and structure of N* states in various exclusive electroproduction channels using the new CLAS12 spectrometer commenced. These studies will probe the structure of N* states in the mass range up to W =3 GeV and for Q2 as low as 0.05 GeV2 and as high as 10-12 GeV2, thus providing a means to access N* structure information spanning a broad range of distance scales. Quasi-real photoproduction studies are also planned to search for additional N* states, the so-called hybrid baryons, for which the glue serves as an active structural component. In this talk the N* programs from both CLAS and CLAS12 will be reviewed.

Carman, D. S.↗
DOE OSTI2020

Mixtures of octanol and an ionic liquid: Structure and transport

Ionic liquids (ILs) with long alkyl substituents are amphiphilic, which leads to a bicontinuous liquid structure. The strongly interacting anionic and cationic head groups form a long range charge network, with the hydrocarbon tails forming a nonpolar domain. Such nonpolar domains have been shown to dissolve a variety of neutral organic solvents. In mixtures of ILs with solvents the neutral organic molecules residing in the nonpolar domains experience different environments and friction from the charged cations and anions. Thus, the neutral molecules diffuse much faster than predicted by hydrodynamic scaling using the average viscosity of the mixture. Here, we report studies on the structure and transport properties of mixtures of 1-octanol with the IL trihexyltetradecylphosphonium bis(trifluoromethylsulfonyl)imide (P 6,6,6,14 + /NTf 2 – ). The majority of the atom fraction in the P 6,6,6,14 + cation comprises four hydrocarbon substituents. The unique amphiphilic nature of ILs with the P 6,6,6,14 + cation makes 1-octanol fully miscible with the IL at ambient temperatures. X-ray scattering experiments show that the IL structure persists in the mixtures for 1-octanol mole fractions as large as x oct = 0.90. The self-diffusion coefficients of the three molecular species in the mixtures were measured by NMR experiments. The self-diffusion of the P 6,6,6,14 + cation is well described by the Stokes–Einstein equation, while the diffusivity of the NTf 2 – anion is slightly lower than the hydrodynamic prediction. The measured diffusivities of octanol in these mixtures are 1.3–4 times higher than the hydrodynamic predictions.

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

From predicting to learning dissipation from pair correlations of active liquids

Active systems, which are driven out of equilibrium by local non-conservative forces, can adopt unique behaviors and configurations. Towards designing such materials, an important challenge is to precisely connect the static structure of active systems to the dissipation of energy induced by the local driving. Here, we use tools from liquid-state theories and machine learning to take on these challenges. We first demonstrate analytically for an isotropic active matter system that dissipation and pair correlations are closely related when driving forces behave like an active temperature. We then extend a nonequilibrium mean-field framework for predicting these pair correlations which, unlike most existing approaches, is applicable even for strongly interacting particles and far from equilibrium, to predict dissipation in these systems. Based on this theory, we reveal analytically a robust relation between dissipation and structure which holds even as the system approaches a nonequilibrium phase transition. Finally, we construct a neural network which maps static configurations of particles to their dissipation rate without any prior knowledge of the underlying dynamics. Furthermore, our results open novel perspectives on the interplay between dissipation and organization out-of-equilibrium.

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

A physics-constrained neural network for multiphase flows

The present study develops a physics-constrained neural network (PCNN) to predict sequential patterns and motions of multiphase flows (MPFs), which includes strong interactions among various fluid phases. To predict the order parameters, which locate individual phases in the future time, a neural network (NN) is applied to quickly infer the dynamics of the phases by encoding observations. The multiphase consistent and conservative boundedness mapping algorithm (MCBOM) is next implemented to correct the predicted order parameters. This enforces the predicted order parameters to strictly satisfy the mass conservation, the summation of the volume fractions of the phases to be unity, the consistency of reduction, and the boundedness of the order parameters. Then, the density of the fluid mixture is updated from the corrected order parameters. Finally, the velocity in the future time is predicted by another NN with the same network structure, but the conservation of momentum is included in the loss function to shrink the parameter space. The proposed PCNN for MPFs sequentially performs (NN)-(MCBOM)-(NN), which avoids nonphysical behaviors of the order parameters, accelerates the convergence, and requires fewer data to make predictions. Numerical experiments demonstrate that the proposed PCNN is capable of predicting MPFs effectively.

Mechanics↗
DOE OSTI2023

Non-perturbative many-body treatment of molecular magnets

Molecular magnets have received significant attention because of their potential applications in quantum information and quantum computing. A delicate balance of electron correlation, spin–orbit coupling (SOC), ligand field splitting, and other effects produces a persistent magnetic moment within each molecular magnet unit. The discovery and design of molecular magnets with improved functionalities would be greatly aided by accurate computations. However, the competition among the different effects poses a challenge for theoretical treatments. Electron correlation plays a central role since d- or f-element ions, which provide the magnetic states in molecular magnets, often require explicit many-body treatments. SOC, which expands the dimensionality of the Hilbert space, can also lead to non-perturbative effects in the presence of strong interaction. Furthermore, molecular magnets are large, with tens of atoms in even the smallest systems. We show how an ab initio treatment of molecular magnets can be achieved with auxiliary-field quantum Monte Carlo, in which electron correlation, SOC, and material specificity are included accurately and on an equal footing. Furthermore, the approach is demonstrated by an application to compute the zero-field splitting of a locally linear Co 2+ complex.

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

Ion dynamics in hexagonal boron nitride ionogel electrolytes

Ionogel electrolytes incorporating exfoliated hexagonal boron nitride (hBN) nanoplatelets are promising materials for next-generation energy storage systems. However, detailed understanding of their ion transport properties at the molecular level remains limited. This study employs diffusion and relaxation nuclear magnetic resonance (NMR) techniques, including fast-field cycling (FFC) NMR, to investigate the dynamics of ionic species in hBN-ionogels. By spanning a broad frequency range from 30 kHz using FFC NMR to high-field NMR (500–800 MHz), we reveal distinct relaxation mechanisms governing ion dynamics in ionogels with and without lithium salts. Our results highlight the role of hBN in modulating molecular rotation and translational motion, significantly affecting 1 H and 19 F relaxation profiles. The presence of Li + alters the dynamic behavior in ionogels, enhancing anion mobility at the interface. Notably, 7 Li relaxation reveals strong interactions with the hBN surface that cannot be detected by diffusion NMR. Furthermore, these findings underscore the importance of spanning a broad frequency range in NMR studies of ionogels and provide critical insights into optimizing their design as novel electrolytes.

Electrolytes↗
DOE OSTI2025

Ice sculpting: An artificial spin ice Tutorial on controlling microstate and geometry for magnonics and neuromorphic computing

Artificial spin ice, arrays of strongly interacting nanomagnets, are complex magnetic systems with many emergent properties, rich microstate spaces, intrinsic physical memory, high-frequency dynamics in the GHz range, and compatibility with a broad range of measurement approaches. This Tutorial article aims to provide the foundational knowledge needed to understand, design, develop, and improve the dynamic properties of artificial spin ice. Special emphasis is placed on introducing the theory of micromagnetics, which describes the complex dynamics within these systems, along with their design, fabrication methods, and standard measurement and control techniques. The article begins with a review of the historical background, introducing the underlying physical phenomena and interactions that govern artificial spin ice. We then explore the standard experimental techniques used to prepare the microstate space of the nanomagnetic array and to characterize magnetization dynamics, both in artificial spin ice and more broadly in ferromagnetic materials. Finally, we introduce the basics of neuromorphic computing applied to the case of artificial spin ice systems with a goal to help researchers new to the field grasp these exciting new developments.

Sultana, Rawnak [Univ. of Delaware, Newark, DE (Un↗
DOE OSTI2025

Control simulations of many-body quantum systems by a synergism of discrete real-time learning and optimal control theory

We present a self-consistent algorithm for optimal control simulations of many-body quantum systems. The algorithm features a two-step synergism that combines discrete real-time machine learning (DRTL) with Quantum Optimal Control Theory (QOCT) using the time-dependent Schrödinger equation. Specifically, in step (1), DRTL is employed to identify a compact working space (i.e., the important portion of the Hilbert space) for the time evolution of the many-body quantum system in the presence of a control field (i.e., the initial or previously updated field), and in step (2), QOCT utilizes the DRTL-determined working space to find a newly updated control field for a chosen objective. Steps 1 and 2 are iterated until a self-consistent control objective value is reached such that the resulting optimal control field yields the same targeted objective value when the corresponding working space is systematically enlarged. Furthermore, to demonstrate this two-step self-consistent DRTL-QOCT synergistic algorithm, we perform optimal control simulations of strongly interacting 1D as well as 2D Heisenberg spin systems. In both scenarios, only a single spin (at the left end site for 1D and the upper left corner site for 2D) is driven by the time-dependent control fields to create an excitation at the opposite site as the target. It is found that, starting from all spin-down zero excitation states, the synergistic method is able to identify working spaces and convergence of the desired controlled dynamics with just a few iterations of the overall algorithm. In the cases studied, the dimensionality of the working space scales only quasi-linearly with the number of spins.

Artificial neural networks↗
DOE OSTI2025

Key Factors in Semi-Generic Coarse-Grained Modeling of Solid Polymer Electrolytes

Given the long length and time scales of interest and strong interactions present in solid polymer electrolytes, coarse-grained molecular models can be useful in understanding the molecular basis of their structure and transport properties. Rather than representing atoms individually, coarse-grained models use beads representing groups of atoms, making the system simpler and more efficient. Generic coarse-grained models, that are not built based on matching a particular atomistic system, can provide insight into the important physical considerations that apply across different chemical systems, though it can be unclear how to best match to experimental systems and capture relevant experimental behaviors with as simple of a model as possible. Here, we build on generic bead-spring models, but use stiff angle potentials, set different bead properties for different polymer types, and include additional ion parameters, creating a semi-generic coarse-grained model that can map more specifically to polymers and copolymers with different chain architectures, component glass transition temperatures, and ion solvation behaviors. We set most parameters with basic homopolymer data such as glass transition temperatures, Kuhn length, density, and dielectric constant, with further adjustment based on data from the polymer electrolyte system. We specifically model polystyrene-block-poly(oligo-oxyethylene methyl ether methacrylate) (PS-b-POEM) with lithium triflate salt, considering the POEM to be made of a poly(methylmethacrylate) backbone with poly(ethylene oxide) side chains. Solvation of ions is accounted for by additional polymer-ion interactions of the form -S/r4, plus additional lithium-polymer Lennard-Jones interactions. We find these potentials have different effects and discuss strategies for setting these parameters.

Zhang, Yuanhao↗
DOE OSTI2015

Defect tolerance and the effect of structural inhomogeneity in plasmonic DNA-nanoparticle superlattices

Significance Materials constructed with metal nanoparticles interact strongly with light, enabling functions such as tunable color, molecular sensors, and light-based electronics. These materials, however, are often imperfect; nanoparticles vary in their size, shape, and surface morphology, which can affect the quality of their arrangement as well as their properties. We use DNA to synthesize precisely controlled crystalline arrangements of gold nanoparticles and survey how a variety of structural inhomogeneities affects their optical properties. The results reported herein identify specific metal nanoparticle-based materials whose optical properties are either sensitive or insensitive to inhomogeneity.

36 MATERIALS SCIENCE↗
DOE OSTI2019

High-performance all-solid-state batteries enabled by salt bonding to perovskite in poly(ethylene oxide)

Flexible and low-cost poly(ethylene oxide) (PEO)-based electrolytes are promising for all-solid-state Li-metal batteries because of their compatibility with a metallic lithium anode. However, the low room-temperature Li-ion conductivity of PEO solid electrolytes and severe lithium-dendrite growth limit their application in high-energy Li-metal batteries. Here we prepared a PEO/perovskite Li 3/8 Sr 7/16 Ta 3/4 Zr 1/4 O 3 composite electrolyte with a Li-ion conductivity of 5.4 × 10 −5 and 3.5 × 10 −4 S cm −1 at 25 and 45 °C, respectively; the strong interaction between the F − of TFSI − (bis-trifluoromethanesulfonimide) and the surface Ta 5+ of the perovskite improves the Li-ion transport at the PEO/perovskite interface. A symmetric Li/composite electrolyte/Li cell shows an excellent cyclability at a high current density up to 0.6 mA cm −2 . A solid electrolyte interphase layer formed in situ between the metallic lithium anode and the composite electrolyte suppresses lithium-dendrite formation and growth. All-solid-state Li|LiFePO 4 and high-voltage Li|LiNi 0.8 Mn 0.1 Co 0.1 O 2 batteries with the composite electrolyte have an impressive performance with high Coulombic efficiencies, small overpotentials, and good cycling stability.

25 ENERGY STORAGE↗
DOE OSTI2020

Designing electrolytes with polymerlike glass-forming properties and fast ion transport at low temperatures

Significance Liquid electrolytes with thermophysical properties analogous to solid polymers, but with exceptional liquidlike ionic conductivities, are formed spontaneously when moderate amounts (≤1 M) of inorganic salts coordinate strongly with small molecules in a conventional aprotic solvent. Specifically, we report that electrolytes composed of the cyclic liquid ether, dioxolane (DOL), and containing the simple salt LiNO 3 are able to completely bypass the liquid → crystalline solid thermal transition, and to exhibit abnormally high bulk and interfacial ionic conductivities down to temperatures as low as −50 °C. Through physical, spectroscopic, and ion-transport measurements it is shown that strong interactions between LiNO 3 and DOL distort bonds in DOL, couple motions of individual solvent molecules, and lower the thermodynamic activity of the electrolyte.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nonadiabatic coupling of the dynamical structure to the superconductivity in YSr 2 Cu 2.75 Mo 0.25 O 7.54 and Sr 2 CuO 3.3

A crucial issue in cuprates is the extent and mechanism of the coupling of the lattice to the electrons and the superconductivity. Here we report Cu K edge extended X-ray absorption fine structure measurements elucidating the internal quantum tunneling polaron (iqtp) component of the dynamical structure in two heavily overdoped superconducting cuprate compounds, tetragonal YSr 2 Cu 2.75 Mo 0.25 O 7.54 with superconducting critical temperature, T c = 84 K and hole density p = 0.3 to 0.5 per planar Cu, and the tetragonal phase of Sr 2 CuO 3.3 with T c = 95 K and p = 0.6. In YSr 2 Cu 2.75 Mo 0.25 O 7.54 changes in the Cu-apical O two-site distribution reflect a sequential renormalization of the double-well potential of this site beginning at T c , with the energy difference between the two minima increasing by ~6 meV between T c and 52 K. Sr 2 CuO 3.3 undergoes a radically larger transformation at T c , >1-Å displacements of the apical O atoms. The principal feature of the dynamical structure underlying these transformations is the strongly anharmonic oscillation of the apical O atoms in a double-well potential that results in the observation of two distinct O sites whose Cu–O distances indicate different bonding modes and valence-charge distributions. The coupling of the superconductivity to the iqtp that originates in this nonadiabatic coupling between the electrons and lattice demonstrates an important role for the dynamical structure whereby pairing occurs even in a system where displacements of the atoms that are part of the transition are sufficiently large to alter the Fermi surface. The synchronization and dynamic coherence of the iqtps resulting from the strong interactions within a crystal would be expected to influence this process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Unnuclear physics: Conformal symmetry in nuclear reactions

Significance Symmetry plays a key role in modern physics as a guiding principle for fundamental theories of nature. We use the nonrelativistic conformal symmetry to predict universal energy spectra of final states in reactions of quantum particles at vastly different length scales. Our work extends Georgi’s “unparticle” proposal to nonrelativistic spin-1/2 fermions in the unitary regime of strong interactions. These systems form so-called unparticles, which behave characteristically different from normal particles. They can be engineered with ultracold atoms and occur naturally in nuclear reactions with multiple neutrons—a situation we dub “unnuclear physics.” We present the general scenario of unnuclear physics, apply it to identify unnuclei in nuclear reactions, and highlight the opportunity to measure unnuclei at radioactive beam facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗