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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dynamic Mixing Behaviors of Ionically Tethered Polymer Canopy of Nanoscale Hybrid Materials in Fluids of Varying Physical and Chemical Properties

An emerging area of sustainable energy and environmental research is focused on the development of novel electrolytes that can increase the solubility of target species and improve subsequent reaction performance. Electrolytes with chemical and structural tunability have allowed for significant advancements in flow batteries and CO 2 conversion integrated with CO 2 capture. Liquid-like nanoparticle organic hybrid materials (NOHMs) are nanoscale fluids that are composed of inorganic nanocores and an ionically tethered polymeric canopy. NOHMs have been shown to exhibit enhanced conductivity making them promising for electrolyte applications, though they are often challenged by high viscosity in the neat state. In this study, a series of binary mixtures of NOHM-I-HPE with five different secondary fluids, water, chloroform, toluene, acetonitrile, and ethyl acetate, were prepared to reduce the fluid viscosity and investigate the effects of secondary fluid properties (e.g., hydrogen bonding ability, polarity, and molar volume) on their transport behaviors, including viscosity and diffusivity. We report our results revealed that the molecular ratio of secondary fluid to the ether groups of Jeffamine M2070 ($λ_{\text{SF}}$) was able to describe the effect that secondary fluid has on transport properties. Our findings also suggest that in solution, the Jeffamine M2070 molecules exist in different nanoscale environments, where some are more strongly associated with the nanoparticle surface than others, and the conformation of the polymer canopy was dependent on the secondary fluid. This understanding of the polymer conformation in NOHMs can allow for the better design of an electrolyte capable of capturing and releasing small gaseous or ionic species.

25 ENERGY STORAGE↗
DOE OSTI2022

Physically and chemically smooth cesium-antimonide photocathodes on single crystal strontium titanate substrates

The performance of x-ray free electron lasers and ultrafast electron diffraction experiments is largely dependent on the brightness of electron sources from photoinjectors. Here, the maximum brightness from photoinjectors at a particular accelerating gradient is limited by the mean transverse energy (MTE) of electrons emitted from photocathodes. For high quantum efficiency (QE) cathodes like alkali-antimonide thin films, which are essential to mitigate the effects of non-linear photoemission on MTE, the smallest possible MTE and, hence, the highest possible brightness are limited by the nanoscale surface roughness and chemical inhomogeneity. In this work, we show that high QE Cs 3 Sb films grown on lattice-matched strontium titanate (STO) substrates have a factor of 4 smoother, chemically uniform surfaces compared to those traditionally grown on disordered Si surfaces. We perform simulations to calculate roughness induced MTE based on measured topographical and surface-potential variations on the Cs 3 Sb films grown on STO and show that these variations are small enough to have no consequential impact on the MTE and, hence, the brightness.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Cosmogenic nuclide and solute flux data from central Cuban rivers emphasize the importance of both physical and chemical mass loss from tropical landscapes

We use 25 new measurements of in situ produced cosmogenic 26 Al and 10 Be in river sand, paired with estimates of dissolved load flux in river water, to characterize the processes and pace of landscape change in central Cuba. Long-term erosion rates inferred from 10 Be concentrations in quartz extracted from central Cuban river sand range from 3.4–189 Mg km –2 yr –1 (mean 59, median 45). Dissolved loads (10–176 Mg km –2 yr –1 ; mean 92, median 97), calculated from stream solute concentrations and modeled runoff, exceed measured cosmogenic- 10 Be-derived erosion rates in 18 of 23 basins. This disparity mandates that in this environment landscape-scale mass loss is not fully represented by the cosmogenic nuclide measurements. The 26 Al / 10 Be ratios are lower than expected for steadystate exposure or erosion in 16 of 24 samples. Depressed 26 Al/ 10 Be ratios occur in many of the basins that have the greatest disparity between dissolved loads (high) and erosion rates inferred from cosmogenic nuclide concentrations (low). Depressed 26 Al/ 10 Be ratios are consistent with the presence of a deep, mixed, regolith layer providing extended storage times on slopes and/or burial and extended storage during fluvial transport. River water chemical analyses indicate that many basins with lower 26 Al/ 10 Be ratios and high 10 Be concentrations are underlain at least in part by evaporitic rocks that rapidly dissolve. Our data show that when assessing mass loss in humid tropical landscapes, accounting for the contribution of rock dissolution at depth is particularly important. In such warm, wet climates, mineral dissolution can occur many meters below the surface, beyond the penetration depth of most cosmic rays and thus the production of most cosmogenic nuclides. Our data suggest the importance of estimating solute fluxes and measuring paired cosmogenic nuclides to better understand the processes and rates of mass transfer at a basin scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Soil moisture, physical and chemical properties coincident with airborne SAR data collections for 2017 and 2019, Seward Peninsula, Alaska

Soil samples were collected coincident with in-situ soil moisture and thaw depth measurements at NGEE Arctic study sites on the Seward Peninsula, Alaska in August 2017 and 2019 Field measurements and flights were conducted during both summers as a collaboration between the NASA ABoVE Project's Airborne SAR Campaign and the NGEE Arctic Project. Airborne overflights of L-band SAR instruments occurred during the soil sampling periods. Laboratory measurements of soil properties include bulk density, volumetric and gravimetric water content, carbon and nitrogen content, and particle size of mineral components. Soil samples processed and reported in this dataset were collected coincident with in situ measurements of soil moisture and thaw depth and airborne P-band and L-band SAR measurements as a collaboration between NGEE Arctic and NASA ABoVE. To learn more about how ABoVE protocols were applied for sampling site selection and making in situ measurements, see the following datasets: (2017: https://doi.org/10.5440/1423892 and 2019: https://doi.org/10.5440/1856042). Contained in this dataset are four .csv data files (including data dictionaries) and one zipped folder of *.pdf files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort (with some overlap with Covid-19 pandemic) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

MolSym : A Python package for handling symmetry in molecular quantum chemistry

A consideration of the point group symmetry of molecules is often advantageous from a computational efficiency standpoint and sometimes necessary for the correct treatment of chemical physics problems. Many modern electronic structure software packages include a treatment of symmetry, but these are sometimes incomplete or unusable outside of that program’s environment. Therefore, we have developed the MolSym package for handling molecular symmetry and its associated functionalities to provide a platform for including symmetry in the implementation and development of other methods. Features include point group detection, molecule symmetrization, arbitrary generation of symmetry element sets and character tables, and symmetry adapted linear combinations of real spherical harmonic basis functions, Cartesian displacement coordinates, and internal coordinates. We present some of the advantages of using molecular symmetry as achieved by MolSym, particularly with respect to Hartree–Fock theory, and the reduction of finite difference displacements in gradient/Hessian computations. Furthermore, this package is designed to be easily integrated into other software development efforts and may be extended to further symmetry applications.

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

Understanding the Applicability of Gas/Particle Partitioning Theory to SOA using Novel Chemically-Speciated Partitioning Measurements (Final Report)

The main objective of this research grant project was to investigate the physical-chemical processes and properties of particles and partitioning gases that influence gas/particle (G/P) partitioning and timescales for equilibration, to directly determine the conditions under which equilibrium G/P partitioning theory can be applied to secondary organic aerosol (SOA). SOA constitutes a major component of submicron particles in the atmosphere, which have important implications for air quality, human and ecosystem health, radiation balance, and climate; however SOA formation, evolution and losses are not well understood. Use of novel on-line measurements of chemically-speciated partitioning measurements of both gas-phase and particle-phase components was a central component to advancing these scientific goals. The key approach was to conduct environmental chamber studies with systems of increasing complexity to determine G/P partitioning rates and equilibrium states for chemically-speciated SOA components. The project builds on our previous work on gas-wall partitioning that must be understood in order to study G/P partitioning in chambers, and to help extrapolate the results to be atmospherically relevant. The goal was to employ measurements and modeling to systematically determine when G/P partitioning theory accurately describes the distribution of oxidized organic compounds in the gas and aerosol phases, and when and why it does not (e.g., aerosol phase-state kinetic limitations, non-ideal mixing, phase separation, oligomer formation,), for chemical and physical conditions typically found throughout the continental boundary layer.

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

State predictive information bottleneck

We report the ability to make sense of the massive amounts of high-dimensional data generated from molecular dynamics simulations is heavily dependent on the knowledge of a low-dimensional manifold (parameterized by a reaction coordinate or RC) that typically distinguishes between relevant metastable states, and which captures the relevant slow dynamics of interest. Methods based on machine learning and artificial intelligence have been proposed over the years to deal with learning such low-dimensional manifolds, but they are often criticized for a disconnect from more traditional and physically interpretable approaches. To deal with such concerns, in this work we propose a deep learning based state predictive information bottleneck approach to learn the RC from high-dimensional molecular simulation trajectories. We demonstrate analytically and numerically how the RC learnt in this approach is connected to the committor in chemical physics and can be used to accurately identify transition states. A crucial hyperparameter in this approach is the time delay or how far into the future the algorithm should make predictions about. Through careful comparisons for benchmark systems, we demonstrate that this hyperparameter choice gives useful control over how coarse-grained we want the metastable state classification of the system to be. We thus believe that this work represents a step forward in systematic application of deep learning based ideas to molecular simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗