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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dynamical correlations leading to site and orbital selective Mott insulator transition in hydrogen doped SmNiO 3

Electron doping induces metal -to -insulator transition (MIT) in SmNiO 3 as realized by experiments. While earlier density functional theory (DFT) studies with static correlations fell short of explaining the recent MIT observations at lower hydrogen concentrations, we present a comprehensive computational investigation employing an advanced approach. We combine DFT with dynamical mean field theory (DFT + DMFT) to efficiently analyze the insulating behavior of hydrogen -doped SmNiO 3 . In contrast to previous theoretical works, our calculations predict an insulator transition occurring at a reduced doping level of H:Ni = 0.5:1. Specifically, while the DFT + U method reveals a gap opening between p-to-d orbitals, the DMFT approach highlights a gap opening between d-to-d orbitals. Our findings uncover a selective Mott transition in site and orbital characteristics, with the Ni ions proximate to the doped hydrogen exhibiting Mott -like traits. Notably, DMFT calculations highlight a pronounced dependence on Hund's parameter J, implying the presence of Hundness in the Mott insulator. Finally, this study underscores the necessity of accounting for dynamical correlations to accurately describe the electronic structure of strongly correlated electron-doped rare-earth nickelates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Refractive index of lithium fluoride at high dynamic stresses

Alkali halides are prototypical ionic solids whose refractive index is a fundamental property related to their lattice structure and ionic polarizability. In particular, lithium fluoride (LiF) has the largest band gap of any known transparent material and maintains transparency at high pressures, making it well suited for use as an optical window in dynamic compression experiments. While empirical fits to the measured density dependence of the refractive index have been provided, a model that is valid over the entire pressure range of experiments and based on a polarization-based theoretical description is lacking. We present a refractive index model for dynamically compressed LiF based on the Lorentz-Lorenz equation, where the molecular polarizability is determined using a single oscillator model with a strain polarizability parameter Λ=0.73. Here, we show that our modeling approach provides an excellent match to the LiF refractive index data for both shock and ramp compression experiments to 900 GPa (density compression greater than threefold). Additionally, updated fits are provided to determine the refractive index correction for LiF windows used in dynamic compression experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Polariton-assisted incoherent to coherent excitation energy transfer between colloidal nanocrystal quantum dots

Here, we explore the dynamics of energy transfer between two nanocrystal quantum dots placed within an optical microcavity. By adjusting the coupling strength between the cavity photon mode and the quantum dots, we have the capacity to fine-tune the effective coupling between the donor and acceptor. Introducing a non-adiabatic parameter, γ, governed by the coupling to the cavity mode, we demonstrate the system’s capability to shift from the overdamped Förster regime (γ $\ll$ 1) to an underdamped coherent regime (γ $\gg$ 1). In the latter regime, characterized by swift energy transfer rates, the dynamics are influenced by decoherence time. To illustrate this, we study the exciton energy transfer dynamics between two closely positioned CdSe/CdS core/shell quantum dots with sizes and separations relevant to experimental conditions. Employing an atomistic approach, we calculate the excitonic level arrangement, exciton–phonon interactions, and transition dipole moments of the quantum dots within the microcavity. These parameters are then utilized to define a model Hamiltonian. Subsequently, we apply a generalized non-Markovian quantum Redfield equation to delineate the dynamics within the polaritonic framework.

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

Solid-state NMR of unlabeled plant cell walls: high-resolution structural analysis without isotopic enrichment

Abstract Background Multidimensional solid-state nuclear magnetic resonance (ssNMR) spectroscopy has emerged as an indispensable technique for resolving polymer structure and intermolecular packing in primary and secondary plant cell walls. Isotope ( 13 C) enrichment provides feasible sensitivity for measuring 2D/3D correlation spectra, but this time-consuming procedure and its associated expenses have restricted the application of ssNMR in lignocellulose analysis. Results Here, we present a method that relies on the sensitivity-enhancing technique Dynamic Nuclear Polarization (DNP) to eliminate the need for 13 C-labeling. With a 26-fold sensitivity enhancement, a series of 2D 13 C– 13 C correlation spectra were successfully collected using the unlabeled stems of wild-type Oryza sativa (rice). The atomic resolution allows us to observe a large number of intramolecular cross peaks for fully revealing the polymorphic structure of cellulose and xylan. NMR relaxation and dipolar order parameters further suggest a sophisticated change of molecular motions in a ctl1 ctl2 double mutant: both cellulose and xylan have become more dynamic on the nanosecond and microsecond timescale, but the motional amplitudes are uniformly small for both polysaccharides. Conclusions By skipping isotopic labeling, the DNP strategy demonstrated here is universally extendable to all lignocellulose materials. This time-efficient method has landed the technical foundation for understanding polysaccharide structure and cell wall assembly in a large variety of plant tissues and species.

09 BIOMASS FUELS↗
DOE OSTI2023

Conformal freeze-in, composite dark photon, and asymmetric reheating

Large classes of dark sector models feature mass scales and couplings very different from the ones we observe in the Standard Model (SM). Moreover, in the freeze-in mechanism, often employed by the dark sector models, it is also required that the dark sector cannot be populated during the reheating process like the SM. This is the so called asymmetric reheating. Such disparities in sizes and scales often call for dynamical explanations. In this paper, we explore a scenario in which slow evolving conformal field theories (CFTs) offer such an explanation. Building on the recent work on conformal freeze-in (COFI), we focus on a coupling between the Standard Model Hypercharge gauge boson and an anti-symmetric tensor operator in the dark CFT. We present a scenario which dynamically realizes the asymmetric reheating and COFI production. With a detailed study of dark matter production, and taking into account limits on the dark matter (DM) self-interaction, warm DM bound, and constraints from the stellar evolution, we demonstrate that the correct relic abundance can be obtained with reasonable choices of parameters. The model predicts the existence of a dark photon as an emergent composite particle, with a small kinetic mixing also determined by the CFT dynamics, which correlates it with the generation of the mass scale of the dark sector. At the same time, COFI production of dark matter is very different from those freeze-in mediated by the dark photon. This is an example of the physics in which a realistic dark sector model can often be much richer and with unexpected features.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Interference Control of Fano Resonances and Dynamical Imaging of an Electron Wave Packet

The Fano line shape, arising from the interference of pathways for the excitation of discrete and continuum states, plays a fundamental role in many branches of physics, chemistry, and materials science. Exciting the resonance with a high harmonic provides naturally a phase delay between the pathways leading to a complex asymmetry parameter. We demonstrate that its amplitude and phase can be controlled on the femtosecond and attosecond time scales, respectively. With our high-energy-resolution (10-meV) experiment, we dynamically image a resonance-enhanced electron wave packet during its temporal evolution, extracting both the amplitude and the phase. Calculations reproduce our experimental results. Our approach constitutes a method for measuring the photoionization delays of a resonance and enables the reconstruction of the electron wave packet in the time domain. This concept of an interference-controlled Fano line shape is a step toward attosecond quantum optics with potential ramifications into nanoscience and next-generation optical materials.

Han, Meng [ETH Zürich (Switzerland); Kansas State ↗
DOE OSTI2023

Experimental approach for development of a powder spreading metric in additive manufacturing

The powder spreading is a vital step of powder-based additive manufacturing (AM) processes. The quality of spread powder can considerably influence the properties of fabricated parts. Poorly packed powder beds with high surface roughness result in printed part layers with large porosity and low dimensional accuracy, leading to poor mechanical properties. Therefore, the powder spreadability and its dependence on process parameters and powder characteristics should be quantified to improve the efficiency of powder-based AM methods. This study proposes a novel dimensionless powder spreadability metric that can be commonly used in different powder-based AM processes. The quality of spread powder in terms of powder bed density and surface roughness was evaluated by adjusting the process parameters including recoating velocity and layer thickness, and powder characteristics including particle size distribution. In addition, the dynamic repose angle was proposed and examined as another powder spreadability metric. Furthermore, the results showed that these two proposed metrics were strongly correlated and lower recoating velocity and larger layer thickness led to higher spreadability and lower dynamic repose angle.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Application of Atmospheric Gases and Particulate Matter to the Assessment of Urban Heat Island

Background: Urban heat island (UHI), where built areas are warmer compared to non-urban regions, increases human related diseases and mortality. A key challenge in UHI analysis is the designation of sites as urban or suburban/rural; however, the growing complexity of green spaces in urban areas and the predominance of the transportation sector in nonurban areas creates a dilemma for distinct delineation. Objectives: This study aims to utilize the variability of atmospheric components such as particulate matter (PM), inorganic gases, and volatile organic compounds (VOCs) as direct tracers of the degree of urbanization for ground-based measurements to fully comprehend UHI in convoluted regions with indistinct delineation of urban and nonurban environments. Methods: Atmospheric gases and aerosols were used as direct tracers of urbanization for UHI analysis. Inorganic gases and particulate matter were monitored in two sites in a southeastern US city with varying degrees of urbanization. VOCs were analyzed using a proton transfer reaction time-of-flight mass spectrometer. Results: The more-urbanized site exhibited warmer night conditions and elevated total oxidant levels, leading to the formation of nanometer-sized particles. Machine learning analysis revealed similar atmospheric pollutant profiles for both sites, suggesting comparable sources and variability. Biogenic VOCs were enhanced at the less-urbanized site; however, levels of anthropogenic aromatic VOCs were comparable for both sites. A comprehensive mass spectra analysis revealed distinct molecular backbones per site that further affirmed the applicability of VOCs as indicators of urbanization. Conclusion: This study concludes that VOCs provide more direct and accurate information than typical inorganic gases and PM parameters for characterizing the degree of urbanization. Further exploration of VOCs can enhance our understanding of UHI dynamics and its interaction with vegetation in urban green spaces.

Air quality sensor↗
DOE OSTI2020

Development of intelligent control module for the J-TEXT electron cyclotron emission imaging system

An Electron Cyclotron Emission Imaging (ECEI) system has been developed on the J-TEXT tokamak and employed for the multi-dimensional electron temperature fluctuation imaging measurement in 2019 campaign. The intelligent control module has been developed and been used to flexibly setup the 256-channel ECEI system configurations for different plasma scenarios. The adjustments of key parameters are merged in this module including size and position of the geometric observation window, and the dynamic range of the signal and image resolution. The user-friendly interface is also developed for the tokamak operator to set the ECEI system focusing on physics interested region. Furthermore, this module is installed close to the diagnostic system around the J-TEXT tokamak, which can be remotely controlled by authorized operators in the control room. It significantly improves ECEI flexibility and stability, and also keeps the operation technician away from the harsh radiation environment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Modeling Molecules under Pressure with Gaussian Potentials

The computational modeling of molecules under high pressure is a growing research area that augments experimental high-pressure chemistry. Here, a new electronic structure method for modeling atoms and molecules under pressure, Gaussians On Surface Tesserae Simulate HYdrostatic Pressure (GOSTSHYP) approach, is introduced. In this method, a set of Gaussian potentials is distributed evenly on the van der Waals surface of the investigated chemical system, leading to a compression of the electron density and the atomic scaffold. Since no parameters other than pressure need to be specified, GOSTSHYP allows straightforward geometry optimizations and ab initio molecular dynamics simulations of chemical systems under pressure for nonexpert users. In this work, calculated energies, bond lengths, and dipole moments under pressure fall within the range of established computational methods for high-pressure chemistry. A Diels-Alder reaction and the cyclotrimerization of acetylene showcase the ability of GOSTSHYP to model pressure-induced chemical reactions. The connection to mechanochemistry is pointed out.

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

Using Computationally-Determined Properties for Machine Learning Prediction of Self-Diffusion Coefficients in Pure Liquids

The ability to predict transport properties of liquids quickly and accurately will greatly improve our understanding of fluid properties both in bulk and complex mixtures, as well as in confined environments. Such information could then be used in the design of materials and processes for applications ranging from energy production and storage to manufacturing processes. As a first step, we consider the use of machine learning (ML) methods to predict the diffusion properties of pure liquids. Recent results have shown that Artificial Neural Networks (ANNs) can effectively predict the diffusion of pure compounds based on the use of experimental properties as the model inputs. In the current study, a similar ANN approach is applied to modeling diffusion of pure liquids using fluid properties obtained exclusively from molecular simulations. A diverse set of 102 pure liquids is considered, ranging from small polar molecules (e.g., water) to large nonpolar molecules (e.g., octane). Self-diffusion coefficients were obtained from classical molecular dynamics (MD) simulations. Since nearly all the molecules are organic compounds, a general set of force field parameters for organic molecules was used. The MD methods are validated by comparing physical and thermodynamic properties with experiment. Computational input features for the ANN include physical properties obtained from the MD simulations as well as molecular properties from quantum calculations of individual molecules. Furthermore, fluid properties describing the local liquid structure were obtained from center of mass radial distribution functions (COM-RDFs). Feature sensitivity analysis revealed that isothermal compressibility, heat of vaporization, and the thermal expansion coefficient were the most impactful properties used as input for the ANN model to predict the MD simulated self-diffusion coefficients. The MD-based ANN successfully predicts the MD self-diffusion coefficients with only a subset (2 to 3) of the available computationally determined input features required. A separate ANN model was developed using literature experimental self-diffusion coefficients as model targets. Although this second ML model was not as successful due to a limited number of data points, a good correlation is still observed between experimental and ML predicted self-diffusion coefficients.

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

Effect of Flexibility in Molecular Simulations of Carbon Dioxide Adsorption and Diffusion in a Cuprous Triazolate Framework

Using fixed atom force fields to model gas adsorption in flexible metal organic frameworks (MOFs) is known to pose difficulties in accurately reproducing and predicting experimental results. This paper studies the difference in accuracy between flexible and fixed atom force fields in reproducing CO 2 adsorption measurements in MAF-2 ([Cu(etz)]∞ (MAF-2, Hetz) 3,5-diethyl-1,2,4-triazole), an NbO-type triazolate scaffold with a bcu cavity system and attached ethyl groups. The flexible force field used to run the hybrid molecular dynamics and grand canonical Monte Carlo calculations were generated using the QuickFF software incorporating van der Waals parameters from the Universal Force Field (UFF) and density derived electrostatic and chemical (DDEC) charges. The fixed atom force field used was composed of UFF van der Waals parameters together with DDEC charges. The calculations were run at 298 K and at pressures of 0.1, 0.3, 0.5, 0.8, and 1 bar. It was observed that for this MOF the rigid force field overpredicted gas adsorption, whereas the flexible force field values closely matched experimental data. In the flexible structure, the freely moving ethyl groups of MAF-2 hindered adsorption, reducing the interaction energy between CO 2 and the N atoms of the triazolate framework as well as reducing the size of the largest cavity diameter. Here, the combination of these factors led to improved prediction of adsorption values with the flexible forcefield as compared to the rigid forcefield, demonstrating the need for modeling MOFs in a way more indicative of their behavior.

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

Kinetic Separation of Siloxanes in Metal–Organic Frameworks

We present an in silico assessment of metal–organic frameworks (MOFs) for the kinetic separation of linear and cyclic siloxanes. We employed molecular dynamics simulations investigating both rigid and flexible 1D MOF frameworks to identify a specific range of pore parameters that enables the diffusion of linear siloxanes but leads to slow diffusion of cyclic siloxanes. We then extended our analysis to flexible 3D MOFs to select adsorbents for the kinetic separation of cyclic and linear siloxanes. Based on synthesizability metrics we identified four 3D MOFs capable of discriminating between cyclic and linear siloxanes. One of the MOFs with structure code WIYFAM stood out with the ability to distinguish between cyclic and linear siloxanes and facilitate the diffusion of all linear siloxanes investigated in this study. One of the other MOFs, IRMOF-6, is found to be capable of not only discriminating between cyclic and linear siloxanes, but even between shorter and longer linear siloxanes.

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

Tailoring On-Surface Molecular Reactions and Assembly through Hydrogen-Modified Synthesis: From Triarylamine Monomer to 2D Covalent Organic Framework

Relative to conventional wet-chemical synthesis techniques, on-surface synthesis of organic networks in ultrahigh vacuum has few control parameters. The molecular deposition rate and substrate temperature are typically the only synthesis variables to be adjusted dynamically. Here we demonstrate that reducing conditions in the vacuum environment can be created and controlled without dedicated sources-relying only on backfilled hydrogen gas and ion gauge filaments-and can dramatically influence the Ullmann-like on-surface reaction used for synthesizing two-dimensional covalent organic frameworks (2D COFs). Using tribromo dimethylmethylene-bridged triphenylamine ((Br 3 )DTPA) as monomer precursors, we find that atomic hydrogen (H*) blocks aryl-aryl bond formation to such an extent that we suspect this reaction may be a factor in limiting the ultimate size of 2D COFs created through on-surface synthesis. Conversely, we show that control of the relative monomer and hydrogen fluxes can be used to produce large self-assembled islands of monomers, dimers, or macrocycle hexamers, which are of interest in their own right. On-surface synthesis of oligomers, from a single precursor, circumvents potential challenges with their protracted wet-chemical synthesis and with multiple deposition sources. Using scanning tunneling microscopy and spectroscopy (STM/STS), we show that changes in the electronic states through this oligomer sequence provide an insightful view of the 2D COF (synthesized in the absence of atomic hydrogen) as the end point in an evolution of electronic structures from the monomer.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Leveraging prior mean models for faster Bayesian optimization of particle accelerators

Tuning particle accelerators is a challenging and time-consuming task that can be automated and carried out efficiently using suitable optimization algorithms, such as model-based Bayesian optimization techniques. One of the major advantages of Bayesian algorithms is the ability to incorporate prior information about beam physics and historical behavior into the model used to make control decisions. In this work, we examine incorporating prior accelerator physics information into Bayesian optimization algorithms by utilizing fast executing, neural network models trained on simulated or historical datasets as prior mean functions in Gaussian process models. We show that in ideal cases, this technique substantially increases convergence speed to optimal solutions in high-dimensional tuning parameter spaces. Additionally, we demonstrate that even in non-ideal cases, where prior models of beam dynamics do not exactly match experimental conditions, the use of this technique can still enhance convergence speed. Finally, we demonstrate how these methods can be used to improve optimization in practical applications, such as transferring information gained from beam dynamics simulations to online control of the LCLS injector, and transferring knowledge gained from experimental measurements across different operating modes, such as accelerating different ion species at the ATLAS heavy ion accelerator.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Assembly of small silica nanoparticles using lipid-tethered DNA ‘bonds’

Single-stranded DNA molecules modified with cholesterol functional groups are physically tethered to silica nanoparticles (diameter 25 nm) that are encapsulated in a lipid bilayer. Such tethering increases the azimuthal mobility of the DNA molecules across the nanoparticle surface and enables nonspecific bonding, eliminating the need for specialized surface chemistries (such as silane or thiol ligands). To induce assembly, double-stranded DNA ‘bridge’ molecules are then added with complementary nucleotides to the DNA ‘anchor’ molecules that are physically tethered to the lipids on the surface of the particles. Assembly is observed to occur at room temperature and without the need for temperature annealing. Using automated liquid handling tools, assemblies are created in high throughput and rapidly characterized using SAXS. It is determined that the relative concentration of DNA-to-silica and the ionic strength of the solution are important parameters that affect the resulting assembly. Analysis of SAXS data is performed using coarse-grained particle dynamics simulations. The results support the spontaneous formation of semi-crystalline particle assemblies by particle condensation, where the interparticle distance is tuned by the sequence of the DNA ‘bridge’ used to link the particles. Crystallinity analysis performed on the resulting simulations, optimized to match SAXS observations, suggest that particle clusters display increased crystallinity in the center of the clusters, but their maximum size remains relatively small (sub-micron) before settling occurs, which limits the extent of crystallization.

Chiang, Huat Thart [Univ. of Washington, Seattle, ↗
DOE OSTI2021

Simulation of decelerating streamers in inhomogeneous atmosphere with implications for runaway electron generation

The dynamics of positive and negative streamers is numerically simulated in atmospheric pressure air in the range of parameters corresponding to the streamer deceleration and termination in the middle of the discharge gap. A detailed comparison with experiments in air at constant and variable density demonstrates good agreement between the 2D simulation results and the observations. It is shown that positive and negative streamers behave in radically different ways when decelerating and stopping. When the head potential drops, the negative streamer transits to the mode in which the propagation is due to the forward electron drift. In this case, the radius of the ionization wave front increases, whereas the electric field at the streamer head decreases further and the streamer stops. Its head diameter continues to increase due to the slow drift of free electrons in the residual under-breakdown field. On the contrary, the only advancement mechanism for a positive streamer with a decreasing head potential is a decrease in the effective radius of the ionization wave, leading to a local increase in the electric field. This mechanism makes it possible to compensate for the reduction in the efficiency of gas photoionization at small head diameters. A qualitative 1D model is suggested to describe streamer deceleration and stopping for different discharge polarities. Estimates show that, during positive streamer stopping, the local electric field at the streamer head can exceed the threshold corresponding to the transition of electrons to the runaway mode when the head potential (relative to the surrounding space) decreases to~1.2 kV in atmospheric pressure air. In this case, pulsed generation of a beam of runaway electrons directed into the channel of a stopping positive streamer can occur. The energy of the formed pulsed electron beam depends on the intensity of photoionization in front of the streamer head. This energy can vary from 700 V (when increasing the photoionization rate by a factor of 10 with respect to the value in atmospheric pressure air) to 2.6 kV (when decreasing the photoionization rate by a factor of 1000). It is possible that this behavior of decelerating positive streamers can explain the observed bursts of x-ray radiation during the streamer propagation in long air gaps.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Cold-atom quantum simulator for string and hadron dynamics in non-Abelian lattice gauge theory

We propose an analog quantum simulator for simulating real-time dynamics of (1+1)-dimensional non-Abelian gauge theory well within the existing capacity of ultracold-atom experiments. The scheme calls for the realization of a two-state ultracold fermionic system in a one-dimensional bipartite lattice, and the observation of subsequent tunneling dynamics. Being based on the loop string hadron formalism of SU(2) lattice gauge theory, this simulation technique is completely SU(2) invariant and simulates accurate dynamics of physical phenomena such as string breaking and/or pair production. The scheme is scalable and particularly effective in simulating the theory in the weak-coupling regime, and also a bulk limit of the theory in the strong-coupling regime up to certain approximations. This paper also presents a numerical benchmark comparison of the exact spectrum and real-time dynamics of lattice gauge theory to that of the atomic Hamiltonian with an experimentally realizable range of parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗