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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 37 records · Page 2

How the Bioinspired Fe 2 Mo 6 S 8 Chevrel Breaks Electrocatalytic Nitrogen Reduction Scaling Relations

The nitrogen reduction reaction (NRR) is a renewable alternative to the energy- and CO 2 -intensive Haber–Bosch NH 3 synthesis process but is severely limited by the low activity and selectivity of studied electrocatalysts. The Chevrel phase Fe 2 Mo 6 S 8 has a surface Fe–S–Mo coordination environment that mimics the nitrogenase FeMo-cofactor and was recently shown to provide state-of-the-art activity and selectivity for NRR. Here, we elucidate the previously unknown NRR mechanism on Fe 2 Mo 6 S 8 via grand-canonical density functional theory (GC-DFT) that realistically models solvated and biased surfaces. Fe sites of Fe 2 Mo 6 S 8 selectively stabilize the key *NNH intermediate via a narrow band of free-atom-like surface d-states that selectively hybridize with p-states of *NNH, which results in Fe sites breaking NRR scaling relationships. These sharp d-states arise from an Fe–S bond dissociation during N 2 adsorption that mimics the mechanism of the nitrogenase FeMo-cofactor. Furthermore, we developed a new GC-DFT-based approach for calculating transition states as a function of bias (GC-NEB) and applied it to produce a microkinetic model for NRR at Fe 2 Mo 6 S 8 that predicts high activity and selectivity, in close agreement with experiments. Furthermore, our results suggest new design principles that may identify effective NRR electrocatalysts that minimize the barriers for *N 2 protonation and *NH 3 desorption and that may be broadly applied to the rational discovery of stable, multinary electrocatalysts for other reactions where narrow bands of surface d-states can be tuned to selectively stabilize key reaction intermediates and guide selectivity toward a target product. Furthermore, our results highlight the importance of using GC-DFT and GC-NEB to accurately model electrocatalytic reactions.

10 SYNTHETIC FUELS↗

Triggering typical nemaline myopathy with compound heterozygous nebulin mutations reveals myofilament structural changes as pathomechanism

Nebulin is a giant protein that winds around the actin filaments in the skeletal muscle sarcomere. Compound-heterozygous mutations in the nebulin gene (NEB) cause typical nemaline myopathy (NM), a muscle disorder characterized by muscle weakness with limited treatment options. We created a mouse model with a missense mutation p.Ser6366Ile and a deletion of NEB exon 55, the Compound-Het model that resembles typical NM. We show that Compound-Het mice are growth-retarded and have muscle weakness. Muscles have a reduced myofibrillar fractional-area and sarcomeres are disorganized, contain rod bodies, and have longer thin filaments. In contrast to nebulin-based severe NM where haplo-insufficiency is the disease driver, Compound-Het mice express normal amounts of nebulin. X-ray diffraction revealed that the actin filament is twisted with a larger radius, that tropomyosin and troponin behavior is altered, and that the myofilament spacing is increased. The unique disease mechanism of nebulin-based typical NM reveals novel therapeutic targets.

59 BASIC BIOLOGICAL SCIENCES↗

Revealing short- and long-range Li-ion diffusion in Li 2 MnO 3 from finite-temperature dynamical mean field theory

Li 2 MnO 3 is a key component of Li-excess layered cathodes of the form (1 − x), LiMO 2 + x, Li 2 MnO 3 (M = Mn, Ni, Co, …), yet its role in setting Li-ion transport limitations remains under debate. Here, in this study, we combine DFT+U, finite-temperature DFT+DMFT with a continuous-time quantum Monte Carlo impurity solver, and nudged-elastic-band (NEB) calculations to study Li + migration in paramagnetic Li 2 MnO 3 in the presence of a single Li vacancy. Evaluating DMFT total energies along the DFT+U NEB geometries reveals that dynamical correlations strongly renormalize the lowest-barrier processes, reducing the activation energies to E a = 0.18 eV for the shortest-range hop and E a = 0.50 eV for the next-lowest (transport-controlling) step. The 0.18 eV barrier quantitatively reproduces the short-range activation energy from µ+SR, while the 0.50 eV barrier is consistent with the long-range transport scale extracted from ac-impedance measurements. This single-vacancy, paramagnetic DMFT description thus provides a unified interpretation of local and macroscopic probes without invoking clustered vacancy configurations or strong extrinsic disorder, consistent with nearly stoichiometric Li 2 MnO 3 powders. More broadly, our results highlight finite-temperature dynamical correlations as an essential ingredient for predicting ionic migration energetics in correlated oxide electrodes.

Lee, Alex Taekyung [University of Illinois, Chicag↗

Prediction of vacancy defect diffusion paths in high entropy alloys via machine learning on molecular dynamics data

Identifying the diffusion path of point defects is a critical step in understanding their evolution and the mechanisms of related phenomena. Defect diffusion occurs at small length and time scales, with impacts on material properties that may continue to evolve over ns to μs, ms, and the continuum scale (s, min, etc., and cm, m, etc.). The time scale accessible to molecular dynamics (MD) simulations is limited by small step sizes, typically in the fs range. Thus, surrogate models of MD simulations through machine learning (ML)-based algorithms are of great interest, especially for complex systems such as high entropy alloys (HEAs). In this work, dynamics governing vacancy migration in HEA were approximated with graph convolutional network (GCN) models as ansatzes for kinetic Monte Carlo (KMC) rate catalogs. Network design considered that diffusion in crystalline solids generally depends on interactions between defects and their immediate neighbor atoms. Graphs represented the vacancy surroundings, MD-generated trajectories provided training and comparison datasets, and unsupervised GCN models approximated interatomic dynamics governing vacancy migration in HEAs as ansatzes for KMC. A proof-of-concept model trained on MD data for the Fe, Ni, Cr, Co, and Cu HEA environment was used with two different neighbor interactions to assess the feasibility of training a GCN to predict vacancy defect transition rates in the HEA environment. The resulting setup rapidly generated MD-formatted synthetic trajectories based on dynamics learned from the MD training set, with a time acceleration of roughly two orders of magnitude and a similar diffusion coefficient to MD observations. Additionally, Nudged Elastic Band (NEB) calculations were performed on randomly generated FeNiCrCoCu HEA structures to determine vacancy migration barriers across nearest-neighbor sites. Transition probabilities for each jump, categorized by atomic type, were extracted from these calculations. NEB-based and GCN-based approaches led to similar outcomes.

Reimer, C↗

Lattice vacancy migration barriers in Fe-Ni alloys, and an indication as to why Ni atoms diffuse slowly: A first-principles study

Lattice vacancy migration barriers in ferromagnetic Fe 𝑥 ⁢Ni 1−𝑥 alloys (0.4 ≤ 𝑥 ≤ 0.6) are accurately quantified within the framework of ab initio electronic structure calculations using the nudged elastic band (NEB) method. Both the atomically disordered (A1) fcc phase, as well as the atomically ordered, tetragonal L⁢1 0 phase—which is under consideration as a material for a rare-earth-free gap magnet for advanced engineering applications—are investigated. Across an ensemble of NEB calculations performed on supercell configurations spanning a range of compositions and containing disordered, partially ordered, and fully ordered structures, we find that Ni-vacancy interchanges encounter significantly higher energetic barriers than do Fe-vacancy interchanges. We contend that this aspect is a key factor in determining the differences in mobility between Fe and Ni atoms in this ferromagnetic alloy. Moreover, we are able to interpret these findings in terms of the ferromagnetic alloy's underlying spin-polarized electronic structure. Specifically, we report a coupling between the size of local lattice distortions and the magnitude of the local electronic spin polarization around vacancies. This causes Fe atoms to relax into lattice vacancies, while Ni atoms remain rigidly fixed to their original lattice positions. These results give atomic-scale insight into the longstanding experimental observation that Ni exhibits remarkably slow atomic diffusion in Fe-Ni alloys.

density functional theory↗

Nudged elastic band approach to nuclear fission pathways

Here, we study the performance and precision of various methods to determine the minimum-action and minimum-energy fission trajectories in the collective space. To this end, we apply the nudged elastic band method (NEB), grid-based methods, and the Euler-Lagrange approach to the collective action minimization in two- and three-dimensional collective spaces.The NEB method is the tool of choice for finding the least-action and minimum-energy fission trajectories. It will be particularly useful in large-scale static fission calculations of superheavy nuclei and neutron-rich fissioning nuclei contributing to the astrophysical r-process recycling.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Near-infrared noise in intense electron beams

Requirements for the noise in electron beams (NEB) have recently approached the Shot-noise level in some new applications. The density fluctuations of intense beams in the near-infrared (NIR) region are being measured at the Fermilab Accelerator Science and Technology (FAST) facility. The main goal of the experiment is to accurately compare the Shot-noise model with the observations of optical transition radiation (OTR) generated by the gamma=63 electron beam transiting an Al metal surface. In addition, evidence for longitudinal-space-charge-induced microbunching for the chicane-compressed beam was obtained with coherent enhancements up to 100 in the various bandwidth-filtered NIR OTR photodiode signals. With micropulse charges up to 1 nC, the beam parameters are close to those proposed for a stage in an Electron-Ion Collider (EIC) with coherent electron cooling (CEC). In this paper we present the current progress of the NEB project and compare the low electron energy measurements with ImpactX simulations.

43 PARTICLE ACCELERATORS↗

Near-Infrared Noise in Intense Electron Beams

Requirements for the noise in electron beams (NEB) have recently approached the Shot-noise level in some new applications. The density fluctuations of intense beams in the near-infrared (NIR) region are being measured at the Fermilab Accelerator Science and Technology (FAST) facility. The main goal of the experiment is to accurately compare the Shot-noise model with the observations of optical transition radiation (OTR) generated by a relativistic electron beam ($\gamma \approx 63$), transiting an Aluminium metal surface. In addition, some evidence for longitudinal space-charge-induced microbunching for the chicane-compressed beam was obtained with coherent enhancements up to 100 in the various bandwidth-filtered NIR OTR photodiode signals. With micropulse charges up to 1 nC, the beam parameters are close to those proposed for a stage in an Electron-Ion Collider (EIC) with coherent electron cooling (CEC). In this paper we present the current progress of the NEB project and compare the low electron energy measurements with ImpactX simulations.

43 PARTICLE ACCELERATORS↗

Diffusion Behavior of Oversized Fission Products in bcc Fe Cladding: A First-Principles Study

Fuel-Cladding Chemical Interaction (FCCI) poses significant challenges in nuclear reactors, where fission products from nuclear fuel interact with Fe-based cladding materials, potentially compromising their structural integrity. This study investigates the diffusion behavior of oversized fission products, Pr, Nd, Ce, and La, within bcc Fe cladding using density functional theory (DFT), nudged elastic band (NEB) method, and self-consistent mean field (SCMF) theory. Our results reveal significant long-range vacancy binding energies, particularly up to the 6th nearest neighbor, with La exhibiting the strongest binding affinity, followed by Nd, Ce, and Pr. The NEB calculations indicate significant high barriers for the dissociation of 1nn vacancy-solute pairs for all fission products. The tracer diffusion coefficients of these fission products was derived in Arrhenius form. The significant trapping effect of vacancies by a very dilute amount of fission products reduces vacancy mobility, leading to an oversaturation of point defects, void nucleation, and swelling. These are critical issues for irradiated cladding materials. The tracer diffusion coefficients indicate that Nd diffuses the fastest, followed by La, Ce, and Pr. This study provides essential insights for developing advanced cladding materials and design strategies to mitigate FCCI, ultimately enhancing nuclear reactor safety and performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The abundance and distribution of water vapor in Jupiter's atmosphere

The atmospheric transmission window between 1800 and 2250 cm(-1) in Jupiter's atmosphere was observed from the Kuiper Airborne Observatory (KAO) and by the infrared spectrometer (IRIS) on Voyager. The vertical distribution of H2O was derived for the 1 to 6 bar portion of Jupiter's troposphere. The spatial variation of H2O was measured using IRIS spectra of the Hot Spots in the North and South Equatorial Belts, the Equatorial Zone, and for an average of the North and South Tropical Zones. The H2O column abundance above the 4 bar level is the same in the zones as in the SEB Hot Spots, about 20 cm-amagat. The NEB Hot Spots are desiccated by a factor of 3 with respect to the rest of Jupiter. For an average between -40 to 40 deg latitude, the H2O mole fraction, qH2O, is saturated for P less than 2 bars, qH2O = 4x10 to the -6 in the 2 to 4 bar range and it increases to 3x10 to the -5 at 6 bars. A similar vertical profile applies to the spatially resolved zone and belt spectra, except that H2O falls off more rapidly at P less than 4 bars in the NEB Hot Spots. The massive H2O cloud at 5 bars, T = 273 K, proposed in solar composition models, is inconsistent with the observations. Instead, a thin H2O ice cloud would form at 2 bars, T = 200 K. The O/H ratio in Jupiter, inferred from H2O measurements in both belts and zones at 6 bars, is depleted by a factor of 50 with respect to the Sun. The implications for the origin of Jupiter of globally depleted O/H, but enhanced C/H and N/H, are discussed.

Bjoraker, Gordon L.↗

Tropospheric gas composition and cloud structure of the Jovian North Equatorial Belt

Voyager IRIS observations of the NEB reveal longitudinal variability of 5-micron brightness temperatures of order 100 C. An anisotropic multiple scattering radiative transfer model is used to calculate synthetic spectra for comparison with the IRIS observations. Mie theory is used to model the spectral dependence of cloud extinction from 180 to 2300/cm. Cloud base locations within the model vary with assumed gas abundances according to thermochemical equilibrium. It is found that spatial variations in the abundance profiles of the condensible species, parahydrogen profiles and cloud optical depths can be used as tracers of the local and large-scale dynamics. The variation of cloud opacity is strongly correlated with the variation of relative humidity, which suggests that dynamic depletion of water vapor above the cloud forming level is the most plausible model to explain the spatial variation in the water profile within the NEB.

Carlson, Barbara E.↗

A change of upper cloud structure in Jupiter's South Equatorial Belt during the 1989-1990 event

We have analyzed two data sets of Jupiter's limb darkening taken before (March 1990) and after (March 1991) a South Equatorial Belt (SEB) disturbance. The vertical aerosol structure has been determined for the SEB, the Equatorial Zone (EZ), and the North Equatorial Belt (NEB). We find that all regions can be well represented with a two-cloud layer model, with slightly higher NH3-cloud top altitude in the EZ than in the two belts. The cloud single-scattering albedos tilda-omega(sub cl) (determined within plus or minus 0.003) show little difference in the EZ (from 0.9956 to 0.9952) and the NEB (from 0.9925 to 0.9926) during a 1-year period, while a relatively larger decrease is found in the SEB from 0.9975 to 0.9957, indicating the recovery of the belt through the disturbance. The NH3-cloud top altitude in the SEB shows the most prominent change, lower in 1990 and higher in 1991. We suggest that the brightening and the darkening of the SEB may originate not only from the changes of tilda-omega(sub cl) but also from changes of the ammonia condensation level in the atmosphere, probably due to a decrease of the tropospheric temperature and/or an increase of the ammonia vapor.

Satoh, Takehiko↗

Atmospheric Waves and Dynamics Beneath Jupiters Clouds from Radio Wavelength Observations

We observed Jupiter at wavelengths near 2 cm with the Karl G. Jansky Very Large Array (VLA) in February 2015. These frequencies are mostly sensitive to variations in ammonia abundance and probe between approx. 0.5- 2.0 bars of pressure in Jupiters atmosphere; within and below the visible cloud deck which has its base near 0.7 bars. The resultant observed data were projected into a cylindrical map of the planet with spatial resolution of approx. 1500 km at the equator. We have examined the data for atmospheric waves and observed a prominent bright belt of radio hotspot features near 10 N, likely connected to the same equatorial wave associated with the 5-m hotspots. We conducted a passive tracer power spectral wave analysis for the entire map and latitude regions corresponding to eastward and westward jets and compare our results to previous studies. The power spectra analysis revealed that the atmosphere sampled in our observation (excluding the NEB region) is in a 2-D turbulent regime and its dynamics are predominately governed by the shallow water equations. The Great Red Spot (GRS) is also very prominent and has a noticeable meridional asymmetry and we compare it, and nearby storms, with optical images. We find that the meridional radio profile has a global north-south hemisphere distinction and find correlations of it to optical intensity banding and to shear zones of the zonal wind profile over select regions of latitude. Amateur optical images taken before and after our observation complemented the radio wave- length map to investigate dynamics of the equatorial region in Jupiters atmosphere. We find that two radio hotspots at 2 cm are well correlated with optical plumes in the NEB, additionally revealing they are not the same 5 m hotspot features correlated with optical dark patches between adjacent plumes. This analysis exploits the VLAs upgraded sensitivity and explores the opportunities now possible when studying gas giants, especially atmospheric dynamics of layers beneath upper level clouds.

radio observations↗

Jupiters North Equatorial Belt Expansion and Thermal Wave Activity Ahead of Junos Arrival.

The dark colors of Jupiter's North Equatorial Belt (NEB, 7-17degN) appeared to expand northward into the neighboring one in 2015, consistent with a 35 year cycle. Inversions of thermal-IR imaging from the Very Large Telescope revealed a moderate warming and reduction of aerosol opacity at the cloud tops at 17-20degN, suggesting subsidence and drying in the expanded sector. Two new thermal waves were identified during this period: (i) an upper tropospheric thermal wave (wave number 16-17, amplitude 2.5 K at 170 mbar) in the mid-NEB that was anticorrelated with haze reflectivity; and (ii) a stratospheric wave (wave number 13-14, amplitude 7.3 K at 5 mbar) at 20-30degN. Both were quasi-stationary, confined to regions of eastward zonal flow, and are morphologically similar to waves observed during previous expansion events.

Jupiter↗

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles Using Python

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗

Lithium Diffusion in Silicon Encapsulated with Graphene

The model of a graphene (Gr) sheet putting on a silicon (Si) substrate is used to simulate the structures of Si microparticles wrapped up in a graphene cage, which may be the anode of lithium-ion batteries (LIBS) to improve the high-volume expansion of Si anode materials. The common low-energy defective graphene (d–Gr) structures of DV5–8–5, DV555–777 and SV are studied and compared with perfect graphene (p–Gr). First-principles calculations are performed to confirm the stable structures before and after Li penetrating through the Gr sheet or graphene/Si-substrate (Gr/Si) slab. The climbing image nudged elastic band (CI-NEB) method is performed to evaluate the diffusion barrier and seek the saddle point. The calculation results reveal that the d–Gr greatly reduces the energy barriers for Li diffusion in Gr or Gr/Si. The energy stability, structural configuration, bond length between the atoms and layer distances of these structures are also discussed in detail.

36 MATERIALS SCIENCE↗

GPR_calculator: An on-the-fly surrogate model to accelerate massive nudged elastic band calculations

We present GPR_calculator, a package based on Python and C++ programming languages to build an on-the-fly surrogate model using Gaussian Process Regression (GPR) to approximate computationally expensive electronic structure calculations. The key idea is to dynamically train a GPR model during the simulation that can accurately predict energies and forces with uncertainty quantification. When the uncertainty is high, the costly electronic structure calculation is performed to obtain the ground truth data, which is then used to update the GPR model. To illustrate the effectiveness of GPR_calculator, we demonstrate its application in Nudged Elastic Band (NEB) simulations of surface diffusion and reactions, achieving 3-10 times acceleration compared to pure ab initio calculations. The source code is available at https://github.com/MaterSim/GPR_calculator.

Gaussian process regression↗