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Results for “POTENTIALS”
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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Rare Earth Selectivity and Electric Potentials at Mica Interfaces
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Low-adiabat rugby hohlraum experiments on the National Ignition Facility: Comparison with high-flux modeling and the potential for gas-wall interpenetration
Rugby-shaped gold hohlraums driven by a nominal low-adiabat laser pulse shape have been tested on the National Ignition Facility. The rugby affords a higher coupling efficiency than a comparably sized cylinder hohlraum or, alternatively, improved drive symmetry and laser beam clearances for a larger hohlraum with similar cylinder wall area and laser energy. A first (large rugby hohlraum) shot at low energy (0.75 MJ) to test laser backscatter resulted in a moderately oblate CH capsule implosion, followed by a high energy shot (1.3 MJ) that gave a highly oblate compressed core according to both time-integrated and –resolved x-ray images. These implosions used low wavelength separation (1.0 Å) between the outer and inner cones to provide an alternative platform free of significant cross-beam energy transfer for simplified hohlraum dynamics. Post-shot 2- and 3-D radiation-hydrodynamic simulations using the high-flux model [M. D. Rosen et al., High Energy Density Phys. 7, 180 (2011)], however, give nearly round implosions for both shots, in striking contrast with observations. An analytic assessment of Rayleigh-Taylor hydrodynamic instability growth on the gold–helium gas-fill interface shows the potential for significant linear growth, saturation and transition to a highly nonlinear state. Candidate seeds for instability growth include laser speckle during the early-time laser picket episode in the presence of only partial temporal beam smoothing (1-D smoothing by spectral dispersion and polarization smoothing) and intensity modulations from quad-to-quad and beam overlap. Radiation-hydrodynamic 2-D simulations adapted to include a dynamic fall-line mix model across the unstable Au-He interface show good agreement with the observed implosion symmetry for both shots using an interface-to-fall-line penetration fraction of 100%. Physically, the potential development of an instability layer in a rugby hohlraum is tantamount to an enhanced wall motion leading to hindered inner-beam propagation, due largely to the confluence of rugby shape and low ray angles relative to the hohlraum symmetry axis. A significant inward pointing shift of 500 μm in the outer cones for the third (full energy) shot of the series was used to improve the inner-beam propagation, resulting in a nearly symmetric x-ray self-emission image of the compressed core and reduced sensitivity to mix. Comparatively low time-dependent symmetry swings were also measured, and a significantly lower hot electron fraction was measured for potentially favorable fuel adiabat control. The outer cone stimulated Brillouin scatter levels jumped significantly, but remedial measures such as the use of a boron dopant in the Au wall are planned. A continuing trend of delayed implosion times is found in rugby hohlraums, suggesting levels of unaccounted hohlraum energy (∼150–200 kJ) similar to what is inferred in cylinder hohlraums. A mix-based physical scenario is described, based on suppressed channel heat flux to the dense gold wall from a temperature-gradient reversal induced by a multispecies plasma lapse rate [P. Amendt, C. Bellei, and S. C. Wilks, Phys. Rev. Lett. 109, 075002 (2012)].
Local random potentials of high differentiability to model the Landscape
We generate random functions locally via a novel generalization of Dyson Brownian motion, such that the functions are in a desired differentiability class C{sup k}, while ensuring that the Hessian is a member of the Gaussian orthogonal ensemble (other ensembles might be chosen if desired). Potentials in such higher differentiability classes (k≥2) are required/desirable to model string theoretical landscapes, for instance to compute cosmological perturbations (e.g., k=2 for the power-spectrum) or to search for minima (e.g., suitable de Sitter vacua for our universe). Since potentials are created locally, numerical studies become feasible even if the dimension of field space is large (D∼100). In addition to the theoretical prescription, we provide some numerical examples to highlight properties of such potentials; concrete cosmological applications will be discussed in companion publications.
DFT Virtual Screening Identifies Rhodium-Amidinate Complexes as Potential Homogeneous Catalysts for Methane-to-Methanol Oxidation
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Structural Origins of Potential Dependent Hysteresis at the Electrified Graphene/Ionic Liquid Interface
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Built-in Potential and Charge Distribution within Single Heterostructured Nanorods Measured by Scanning Kelvin Probe Microscopy
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Assessing Capability of Semiconductors to Split Water Using Ionization Potentials and Electron Affinities Only
Abstract not provided
Potential Revenue from Electrical Energy Storage in ERCOT: The Impact of Location and Recent Trends.
Abstract not provided.
Estimating Potential Revenue from Electrical Energy Storage in PJM.
Abstract not provided.
Complete Genome Sequence of Micromonospora Strain L5, a Potential Plant-Growth-Regulating Actinomycete, Originally Isolated from Casuarina equisetifolia Root Nodules
Micromonospora species live in diverse environments and exhibit a broad range of functions, including antibiotic production, biocontrol, and degradation of complex polysaccharides. To learn more about these versatile actinomycetes, we sequenced the genome of strain L5, originally isolated from root nodules of an actinorhizal plant growing in Mexico.
Potential Adoption and Benefits of Co-Optimized Multimode Engines and Fuels for U.S. Light-Duty Vehicles
Exploring a diverse portfolio of technologies for decarbonization is crucial to understanding the potential impacts of different technological solutions and their associated environmental implications. Using high-octane, high-sensitivity biofuel blends in co-optimized multimode engines can increase engine efficiency and reduce vehicle emissions. Here, the multimode engine research focuses on the benefits of light-duty vehicle engines, which can operate in multiple modes depending on the vehicle's load. Low-temperature combustion can improve efficiency and reduce emissions (such as those from oxides of nitrogen and particulate matter) during low-load operation, while spark ignition performance is maintained in high-load operation. These advanced engines can be optimized to run on blends of biobased fuels. This analysis models scenarios for potential market adoption of co-optimized multimode vehicles fueled by three different bioblendstocks: ethanol, isopropanol, and isobutanol. An integrated modeling approach is used to forecast the energy and environmental impacts of the deployment of co-optimized multimode vehicles and fuels in the light-duty sector over the 2020-to-2050 time horizon. The multidisciplinary approach combines vehicle sales modeling, system dynamics modeling of the biorefining industry, and life cycle assessment to estimate the emissions and energy benefits. The models consider market forces such as consumer preferences for vehicle attributes, biofuel supply and demand dynamics subject to biorefinery capacity build-out and bioresource constraints, and forecasted changes to the U.S. bulk energy system over time. Market adoption of co-optimized vehicles is evaluated across a wide parameter space for incremental vehicle cost and engine efficiency improvement. This analysis reveals that the deployment of co-optimized multimode fuels and vehicles results in up to a 5% reduction in annual sector-wide life cycle greenhouse gas (GHG) emissions by 2050, relative to a business-as-usual scenario, but is also indicates environmental trade-offs, such as higher life cycle water-use. Emission benefits could potentially increase beyond 2050, as the new technologies penetrate the market and gain a foothold. Results also show that, under certain circumstances, vehicles with engines co-optimized for use with high-octane, high-sensitivity biofuel blends can be cost-competitive with conventional gasoline, while reducing GHG emissions. Our modeling results indicate that co-optimized multimode fuels and engines can be strategically leveraged in tandem with electrification to decarbonize the light-duty sector. Co-optimized vehicles could play a role in the early years of the time horizon, while electric vehicles (EVs) could become more competitive in the later years, highlighting the complementary benefits of these technologies for GHG reductions.
Machine Learning Classical Interatomic Potentials for Molecular Dynamics from First-Principles Training Data
The ever-increasing power of modern super-computers, along with the availability of highly scalable atomistic simulation codes, has begun to revolutionize predictive modeling of materials. In particular, molecular dynamics (MD) has led to breakthrough advances in diverse fields, including tribology, catalysis, sensing, and nanoparticle self-assembly. Furthermore, recent integration of MD simulations with X-ray characterization has demonstrated promise in real-time 3-D characterization of materials on the atomic scale. The popularity of MD is driven by its applicability at disparate length/time scales, ranging from ab initio MD (hundreds of atoms and tens of picoseconds) to all-atom classical MD (millions of atoms over microseconds), and coarse-grained (CG) models (micrometers and tens of microseconds). Nevertheless, a substantial gap persists between AIMD, which is highly accurate but restricted to extremely small sizes, and those based on classical force fields (atomistic and CG) with limited accuracy but access to larger length/time scales. The accuracy and predictive power of classical MD simulations is dictated by the empirical force fields, and their capability to capture the relevant physics. Here, we discuss some of our recent work on the use of machine learning (ML) to combine the accuracy and flexibility of electronic structure calculations with the speed of classical potentials. Our ML framework attempts to bridge the significant gulf that exists between the handful of research groups that develop new interatomic potential models (often requiring several years of effort), and the increasingly large user community from academia and industry that applies these models. Our data-driven approach represents significant departure from the status quo and involves several steps including generation and manipulation of extensive training data sets through electronic structure calculations, defining novel potential functional forms, employing state-of-the-art ML algorithms to formulate highly optimized training procedures, and subsequently developing user-friendly workflow tools integrating these algorithms on high-performance computers (HPCs). Our ML approach shows marked success in developing force fields for a wide range of materials from metals, oxides, nitrides, and heterointerfaces to two-dimensional (2D) materials.
A Comparison of Exact and Model Exchange–Correlation Potentials for Molecules
Accurate exchange–correlation (XC) potentials for three-dimensional systems–via solution of the inverse density functional theory (DFT) problem–are now available to test the quality of DFT approximations. Herein, the exact XC potential for seven molecules–dihydrogen at four different bond-lengths, lithium hydride, water, and ortho-benzyne–are computed from full configuration interaction reference densities. These are compared to model XC potentials from nonlocal (B3LYP, HSE06, SCAN0, and M08-HX) and semilocal/local (SCAN, PBE, and PW92) XC functionals. Whereas for most systems, relative errors in the ground-state densities are O(10 –3 –10 –2 ) , the model XC potentials have much higher errors of O(10 –1 –10 0 ) . Among the model XC functionals, SCAN0 offers the best agreement with the exact XC potential, underlining the significance of satisfying exact conditions as well as including nonlocal effects in XC functionals. This work indicates that tests against the exact XC potential will provide a promising new direction for building more accurate XC functionals for DFT.
Hierarchy of model Kohn–Sham potentials for orbital-dependent functionals: A practical alternative to the optimized effective potential method
We describe a method for constructing a hierarchy of model potentials approximating the functional derivative of a given orbital-dependent exchange-correlation functional with respect to electron density. Each model is derived by assuming a particular relationship between the self-consistent solutions of Kohn–Sham (KS) and generalized Kohn–Sham (GKS) equations for the same functional. In the KS scheme, the functional is differentiated with respect to density, in the GKS scheme—with respect to orbitals. The lowest-level approximation is the orbital-averaged effective potential (OAEP) built with the GKS orbitals. The second-level approximation, termed the orbital-consistent effective potential (OCEP), is based on the assumption that the KS and GKS orbitals are the same. It has the form of the OAEP plus a correction term. The highest-level approximation is the density-consistent effective potential (DCEP), derived under the assumption that the KS and GKS electron densities are equal. The analytic expression for a DCEP is the OCEP formula augmented with kinetic-energy-density-dependent terms. In the case of exact-exchange functional, the OAEP is the Slater potential, the OCEP is roughly equivalent to the localized Hartree–Fock approximation and related models, and the DCEP is practically indistinguishable from the true optimized effective potential for exact exchange. All three levels of the proposed hierarchy require solutions of the GKS equations as input and have the same affordable computational cost.
Floating potential of emitting surfaces in plasmas with respect to the space potential
The potential difference between a floating emitting surface and the plasma surrounding it has been described by several sheath models, including the space-charge-limited sheath, the electron sheath with high emission current, and the inverse sheath produced by charge-exchange ion trapping. Our measurements reveal that each of these models has its own regime of validity. We determine the potential of an emissive filament relative to the plasma potential, emphasizing variations in emitted current density and neutral particle density. The potential of a filament in a diffuse plasma is first shown to vanish, consistent with the electron sheath model and increasing electron emission. In a denser plasma with ample neutral pressure, the floating filament potential is positive, as predicted by a derived ion trapping condition. In conclusion, the filament floated negatively in a third plasma, where flowing ions and electrons and nonnegligible electric fields may have disrupted ion trapping. Depending on the regime chosen, emitting surfaces can float positively or negatively with respect to the plasma potential.
Peierls potential of screw dislocations in bcc transition metals: Predictions from density functional theory
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