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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Chromium segregation at phase boundaries in Cr-doped WC-Co cemented carbides

Highlights: • Experimental evidence of a mixed (W,Cr) carbide layer on WC grain surfaces • Evidence of Cr segregation in the Co-rich binder phase in front of WC grain surfaces • Temperature dependent equilibrium segregation of Cr estimated from atom probe data • Experimental observations supported by predictions from thermodynamic modelling - Abstract: Atom probe tomography has shown (Cr,W)C to be present as a thin WC grain surface layer in an as-sintered Cr-doped WC-Co cemented carbide microstructure slowly cooled from the sintering temperature. The Co-rich binder phase contained a segregation of Cr in front of this surface layer. The mixed carbide layer was not observed when the as-sintered material had been heat treated at 1000 °C for 3000 s and then quickly cooled. A reduced amount of segregated Cr was, however, still present in the binder phase in front of the WC grain surface. These observations are supported by predictions from thermodynamic modelling; (Cr,W)C becomes stable at temperatures below 940 °C in the absence of other secondary carbides. The equilibrium segregation of Cr in the binder phase was estimated to 0.8 and 0.4 monolayer in the as-sintered and heat treated materials, respectively. The energy of segregation was calculated to 0.22 eV/Cr atom from the atom probe data. This value would result in a Cr segregation of 0.3 monolayer at the sintering temperature 1410 °C, provided that the energy of segregation in the Co-rich liquid phase sintering medium is the same as in the Co-rich binder phase. This Cr segregation may explain the WC grain growth inhibiting effect of Cr additions to WC-Co cemented carbide materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The GMRT archive atomic gas survey – II. Mass modelling and dark matter halo properties across late-type spirals

Studying the kinematics and mass modelling of galaxies from H i 21 cm data provides valuable insights into the properties of both the baryonic components and the dark matter halo in nearby galaxies. Despite many observational studies, mass modelling of galaxies remains challenging due to different limitations. For example, most of the previous studies involving mass modelling are based on rotation curves derived from 2D velocity fields from H i or H α spectroscopic observation which are often affected by beam smearing and projection effect. However, kinematic modelling done by fitting the ‘Tilted ring model’ to 3D data cube is not affected by these issues. In this study, we present and compare 3D kinematic modelling of a pilot sample of 11 galaxies from the GMRT archive atomic gas survey (GARCIA) using two different publicly available pipelines. We model the observed H i rotation curve using 3.6-μm infrared data and SDSS r-band data for stellar contribution, H i surface density profile for gas, and Navarro–Frenk–White profile for dark matter halo; and employ the Markov chain Monte Carlo optimization method for parameter estimation. Further, to validate our analysis, we revisit important scaling relations, e.g. the M gas –M star relation, M star –M halo relation, M gas –M halo relation and Baryonic Tully–Fisher relation. Here, the scaling relations from our analysis are broadly consistent with that reported in the literature. A larger sample of galaxies from GARCIA in the near future will allow studying these scaling relations in greater details.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Probing the Kitaev honeycomb model on a neutral-atom quantum computer

Quantum simulations of many-body systems are among the most promising applications of quantum computers. In particular, models based on strongly correlated fermions are central to our understanding of quantum chemistry and materials problems, and can lead to exotic, topological phases of matter. However, owing to the non-local nature of fermions, such models are challenging to simulate with qubit devices. Here we realize a digital quantum simulation architecture for two-dimensional fermionic systems based on reconfigurable atom arrays. We utilize a fermion-to-qubit mapping based on Kitaev’s model on a honeycomb lattice, in which fermionic statistics are encoded using long-range entangled states. We prepare these states efficiently using measurement and feedforward, realize subsequent fermionic evolution through Floquet engineering with tunable entangling gates interspersed with atom rearrangement, and improve results with built-in error detection. Leveraging this fermion description of the Kitaev spin model, we efficiently prepare topological states across its complex phase diagram and verify the non-Abelian spin-liquid phase by evaluating an odd Chern number. We further explore this two-dimensional fermion system by realizing tunable dynamics and directly probing fermion exchange statistics. Finally, we simulate strong interactions and study the dynamics of the Fermi–Hubbard model on a square lattice. These results pave the way for digital quantum simulations of complex fermionic systems for materials science, chemistry and high-energy physics.

atomic and molecular physics↗
DOE OSTI2020

Hierarchical, rotation‐equivariant neural networks to select structural models of protein complexes

Abstract Predicting the structure of multi‐protein complexes is a grand challenge in biochemistry, with major implications for basic science and drug discovery. Computational structure prediction methods generally leverage predefined structural features to distinguish accurate structural models from less accurate ones. This raises the question of whether it is possible to learn characteristics of accurate models directly from atomic coordinates of protein complexes, with no prior assumptions. Here we introduce a machine learning method that learns directly from the 3D positions of all atoms to identify accurate models of protein complexes, without using any precomputed physics‐inspired or statistical terms. Our neural network architecture combines multiple ingredients that together enable end‐to‐end learning from molecular structures containing tens of thousands of atoms: a point‐based representation of atoms, equivariance with respect to rotation and translation, local convolutions, and hierarchical subsampling operations. When used in combination with previously developed scoring functions, our network substantially improves the identification of accurate structural models among a large set of possible models. Our network can also be used to predict the accuracy of a given structural model in absolute terms. The architecture we present is readily applicable to other tasks involving learning on 3D structures of large atomic systems.

Eismann, Stephan↗
DOE OSTI2013

A cluster expansion model for predicting activation barrier of atomic processes

We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEB results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Solvent organization in the ultrahigh-resolution crystal structure of crambin at room temperature

Ultrahigh-resolution structures provide unprecedented details about protein dynamics, hydrogen bonding and solvent networks. The reported 0.70 Å, room-temperature crystal structure of crambin is the highest-resolution ambient-temperature structure of a protein achieved to date. Sufficient data were collected to enable unrestrained refinement of the protein and associated solvent networks using SHELXL . Dynamic solvent networks resulting from alternative side-chain conformations and shifts in water positions are revealed, demonstrating that polypeptide flexibility and formation of clathrate-type structures at hydrophobic surfaces are the key features endowing crambin crystals with extraordinary diffraction power.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

Images of the earth's aurora and geocorona from the Dynamics Explorer mission

Several series of auroral and geocoronal images from th Dynamics Explorer Mission are presented and analyzed. It is found that the motion of the transpolar arc of a theta aurora is correlated with the y-component of the IMF; the arc motion is in the general direction of the y-component. In addition, a sequence of global images of a small auroral substorm shows the initial development of intense luminosities in a relatively small spatial region or 'bright spot' in the premidnight sector of the auroral oval and a subsequent appearance of an expanding area of lesser intensities at low latitudes and contiguous to the midnight boundary of the bright spot. Finally, a series of images of the geocorona in scattered solar Ly-alpha emissions is used to obtain a best-fit spherical model of atomic hydrogen densities in the earth's exosphere; a Chamberlain model provides an adequate fit to radial distances of 4.5 earth-radii, beyond which an exponential fit is used. The geocoronal tail is detected as an asymmetric increase in scattered Ly-alpha intensities in the antisolar direction.

Frank, L. A.↗
DOE OSTI2020

Model for the electrical conductivity in dense plasma mixtures

A new density functional theory, average atom based model for the electrical conductivity of dense plasmas with a mixture of ion species, containing no adjustable parameters, is presented herein. The model takes the temperature, mass density and relative abundances of the species as input. It takes into account partial ionization, ionic structure, and core-valence orthogonality, and uses quantum mechanical calculations of cross sections. Comparison to an existing high fidelity but computationally expensive method reveals good agreement. The new model is computationally efficient and can reach high temperatures. A new mixing rule is also presented that gives reasonably accurate conductivities for high temperature plasma mixtures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2012

Kuang's Semi-Classical Formalism for Electron Capture Cross-Sections in Ion-Ion Collisions at few MeV's/nucleon: Application to ENA Modeling

Accurate estimates of electron-capture cross sections at energies relevant to energetic neutral atom (ENA) modeling (approx few MeV per nucleon) and for multi-electron ions must rely on first-principles approaches and/or detailed quantum-mechanical simulation of the collision process. Kuang's semi-classical approach offers a middle-ground, elegant and efficient way to arrive at these estimates. We shall present a sample application and current progress in applying and extending Kuang's formalism to ENA modeling.

Barghouty, A. F.↗
NASA NTRS2001

CFD Simulation of Liquid Rocket Engine Injectors

Detailed design issues associated with liquid rocket engine injectors and combustion chamber operation require CFD methodology which simulates highly three-dimensional, turbulent, vaporizing, and combusting flows. The primary utility of such simulations involves predicting multi-dimensional effects caused by specific injector configurations. SECA, Inc. and Engineering Sciences, Inc. have been developing appropriate computational methodology for NASA/MSFC for the past decade. CFD tools and computers have improved dramatically during this time period; however, the physical submodels used in these analyses must still remain relatively simple in order to produce useful results. Simulations of clustered coaxial and impinger injector elements for hydrogen and hydrocarbon fuels, which account for real fluid properties, is the immediate goal of this research. The spray combustion codes are based on the FDNS CFD code' and are structured to represent homogeneous and heterogeneous spray combustion. The homogeneous spray model treats the flow as a continuum of multi-phase, multicomponent fluids which move without thermal or velocity lags between the phases. Two heterogeneous models were developed: (1) a volume-of-fluid (VOF) model which represents the liquid core of coaxial or impinger jets and their atomization and vaporization, and (2) a Blob model which represents the injected streams as a cloud of droplets the size of the injector orifice which subsequently exhibit particle interaction, vaporization, and combustion. All of these spray models are computationally intensive, but this is unavoidable to accurately account for the complex physics and combustion which is to be predicted, Work is currently in progress to parallelize these codes to improve their computational efficiency. These spray combustion codes were used to simulate the three test cases which are the subject of the 2nd International Workshop on-Rocket Combustion Modeling. Such test cases are considered by these investigators to be very valuable for code validation because combustion kinetics, turbulence models and atomization models based on low pressure experiments of hydrogen air combustion do not adequately verify analytical or CFD submodels which are necessary to simulate rocket engine combustion. We wish to emphasize that the simulations which we prepared for this meeting are meant to test the accuracy of the approximations used in our general purpose spray combustion models, rather than represent a definitive analysis of each of the experiments which were conducted. Our goal is to accurately predict local temperatures and mixture ratios in rocket engines; hence predicting individual experiments is used only for code validation. To replace the conventional JANNAF standard axisymmetric finite-rate (TDK) computer code 2 for performance prediction with CFD cases, such codes must posses two features. Firstly, they must be as easy to use and of comparable run times for conventional performance predictions. Secondly, they must provide more detailed predictions of the flowfields near the injector face. Specifically, they must accurately predict the convective mixing of injected liquid propellants in terms of the injector element configurations.

Farmer, Richard↗
DOE OSTI2015

Negative hydrogen ion yields at plasma grid surface in a negative hydrogen ion source

Negative hydrogen (H{sup −}) ion yield from the plasma grid due to incident hydrogen ions and neutrals has been evaluated with the surface collision cascade model, ACAT (Atomic Collision in Amorphous Target) coupled to a negative surface ionization models. Dependence of negative ion fractions upon the velocity component normal to the surface largely affect the calculation results of the final energy and angular distributions of the H{sup −} ions. The influence is particularly large for H{sup −} ions desorbed from the surface due to less than several eV hydrogen particle implact. The present calculation predicts that H{sup −} ion yield can be maximized by setting the incident angle of hydrogen ions and neutrals to be 65 degree. The Cs thickness on the plasma grid should also affect the yields and mean energies of surface produced H{sup −} ions by back scattering and ion induced desorption processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Metabolic flux analysis reaching genome wide coverage: lessons learned and future perspectives

13 C-MFA is currently the only technique capable of elucidating intracellular metabolic fluxes. Generally, in 13 C-MFA studies the reactions that can carry flux are mostly pre-specified by only considering canonical pathways and ignoring alternate ones. This may bias flux elucidation and cause labeling data to erroneously confirm implied assumptions. Here, by expanding the scope of the metabolic mapping models to match known genome-scale metabolism such estimation biases can be eliminated. However, this model expansion to genome-scale requires the construction of expanded atom mapping models, more efficient flux estimation algorithms, and formal estimation of confidence levels. Even though significant progress has been made in this direction, a number of challenges remain before widespread adoption by the community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Identifying the Interactions That Allow Separation of O 2 from N 2 on the Open Iron Sites of Fe 2 (dobdc)

The presence of open metal sites along with a high porosity makes the Fe 2 (dobdc) metal–organic framework, also called Fe-MOF-74, particularly well suited for separating gaseous mixtures. For instance, since Fe 2 (dobdc) adsorbs O 2 more strongly than N 2 , it can, in principle, be used to separate O 2 from air [Bloch et al., J. Am. Chem. Soc. 2011, 133, 14814]. Here, in the present work, we investigate the reversible differential adsorption of N 2 and O 2 on Fe 2 (dobdc) with Kohn-Sham density functional theory applied to an 88-atom cluster model of the MOF. The cluster is chosen such that it is large enough to allow an accurate description of the most important contributions to the binding enthalpies and small enough to perform high-level quantum mechanical calculations. For the quantum mechanical calculations, we use well-validated exchange–correlation functionals to study the ground-state structures of the Fe–N 2 and Fe–O 2 interacting systems. The calculations agree with experiment in that O 2 binds more strongly than N 2 , and they reveal that the ground-state structure of the Fe–O 2 subsystem has the dioxygen unit in a triplet spin state ferromagnetically coupled to the high-spin state (quintet state) of the iron center. Charge Model 5 (CM5) calculations have been performed to determine the partial atomic charges on the adsorbate molecules and the iron atom, and they show that charge transfer from the open iron(II) site is more important in the case of O 2 than in the case of N 2 . Furthermore, bond orders, vibrational frequencies, and orbital energies were calculated to rationalize the stronger binding of O 2 compared to N 2 on Fe 2 (dobdc).

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

Understanding the Connection between Nanoparticle Uptake and Cancer Treatment Efficacy using Mathematical Modeling

Nanoparticles have shown great promise in improving cancer treatment efficacy while reducing toxicity and treatment side effects. Predicting the treatment outcome for nanoparticle systems by measuring nanoparticle biodistribution has been challenging due to the commonly unmatched, heterogeneous distribution of nanoparticles relative to free drug distribution. We here present a proof-of-concept study that uses mathematical modeling together with experimentation to address this challenge. Individual mice with 4T1 breast cancer were treated with either nanoparticle-delivered or free doxorubicin, with results demonstrating improved cancer kill efficacy of doxorubicin loaded nanoparticles in comparison to free doxorubicin. We then developed a mathematical theory to render model predictions from measured nanoparticle biodistribution, as determined using graphite furnace atomic absorption. Model analysis finds that treatment efficacy increased exponentially with increased nanoparticle accumulation within the tumor, emphasizing the significance of developing new ways to optimize the delivery efficiency of nanoparticles to the tumor microenvironment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

A foundation model for atomistic materials chemistry

Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much of our understanding of chemistry and materials science. Over the last decade or so, machine-learned force fields have transformed atomistic modeling by enabling simulations of ab initio quality over unprecedented time and length scales. However, early machine-learning (ML) force fields have largely been limited by (i) the substantial computational and human effort required to develop and validate potentials for each particular system of interest and (ii) a general lack of transferability from one chemical system to the next. Here, we show that it is possible to create a general-purpose atomistic ML model, trained on a public dataset of moderate size, that is capable of running stable molecular dynamics for a wide range of molecules and materials. We demonstrate the power of the MACE-MP-0 model-and its qualitative and at times quantitative accuracy-on a diverse set of problems in the physical sciences, including properties of solids, liquids, gases, chemical reactions, interfaces, and even the dynamics of a small protein. The model can be applied out of the box as a starting or "foundation" model for any atomistic system of interest and, when desired, can be fine-tuned on just a handful of application-specific data points to reach ab initio accuracy. Establishing that a stable force-field model can cover almost all materials changes atomistic modeling in a fundamental way: experienced users obtain reliable results much faster, and beginners face a lower barrier to entry. Foundation models thus represent a step toward democratizing the revolution in atomic-scale modeling that has been brought about by ML force fields.

Batatia, Ilyes↗
NASA NTRS1995

Development of optical diagnostics for performance evaluation of arcjet thrusters

Laser and optical emission-based measurements have been developed and implemented for use on low-power hydrogen arcjet thrusters and xenon-propelled electric thrusters. In the case of low power hydrogen arcjets, these laser induce fluorescence measurements constitute the first complete set of data that characterize the velocity and temperature field of such a device. The research performed under the auspices of this NASA grant includes laser-based measurements of atomic hydrogen velocity and translational temperature, ultraviolet absorption measurements of ground state atomic hydrogen, Raman scattering measurements of the electronic ground state of molecular hydrogen, and optical emission based measurements of electronically excited atomic hydrogen, electron number density, and electron temperature. In addition, we have developed a collisional-radiative model of atomic hydrogen for use in conjunction with magnetohydrodynamic models to predict the plasma radiative spectrum, and near-electrode plasma models to better understand current transfer from the electrodes to the plasma. In the final year of the grant, a new program aimed at developing diagnostics for xenon plasma thrusters was initiated, and results on the use of diode lasers for interrogating Hall accelerator plasmas has been presented at recent conferences.

Cappelli, Mark A.↗
DOE OSTI2017

Dislocation and Structural Studies at Metal–Metallic Glass Interface at Low Temperature

In this paper, molecular dynamics (MD) simulation deformation studies on the Al (metal)–Cu{sub 50}Zr{sub 50} (metallic glass) model interface is carried out based on cohesive zone model. The interface is subjected to mode-I loading at a strain rate of 10{sup 9} s{sup −1} and temperature of 100 K. The dislocations reactions and evolution of dislocation densities during the deformation have been investigated. Atomic interactions between Al, Cu and Zr atoms are modeled using EAM (embedded atom method) potential, and a timestep of 0.002 ps is used for performing the MD simulations. A circular crack and rectangular notch are introduced at the interface to investigate the effect on the deformation behavior and fracture. Further, scale size effect is also investigated. The structural changes and evolution of dislocation density are also examined. It is found that the dominant deformation mechanism is by Shockley partial dislocation nucleation. Amorphization is observed in the Al regions close to the interface and occurs at a lower strain in the presence of a crack. The total dislocation density is found to be maximum after the first yield in both the perfect and defect interface models and is highest in the case of perfect interface with a density of 6.31 × 10{sup 17} m{sup −2}. In the perfect and circular crack defect interface models, it is observed that the fraction of Shockley partial dislocation density decreases, whereas that of strain rod dislocations increases with increase in strain.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Numerical and experimental study of atomic transport and Balmer line intensity in Linac4 negative ion source

Time structure of Balmer H{sub α} line intensity in Linac4 RF plasma has been analyzed by the combined simulation model of atomic transport and Collisional-Radiative models. As a preliminary result, time variation of the line intensity in the ignition phase of RF plasma is calculated and compared with the experimental results by photometry. For the comparison, spatial distribution of the local H{sub α} photon emission rate at each time is calculated from the numerical model. The contribution of the local photon emission rates to the observed line intensity via optical viewing port is also investigated by application of the mock-up of the optical viewing port and the known light source. It has been clarified from the analyses that the higher and the lower peaks of the H{sub α} line intensity observed during 1 RF cycle is mainly due to the different spatial distributions in the electron energy distribution function and the resultant local photon emission rate. These results support previous suggestion that the existence of the capacitive electric field in axial direction leads to the higher/lower peaks of the line intensity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗