Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “potential theory”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Comparison of theory and in situ observations for electron and ion distributions in the near wake of the Explorer 31 and AE-C satellites

Measurements of electron density, plasma potential, and mean ion mass from the Explorer 31 satellite, and measurements of ion current, plasma potential, and ion composition from the Atmosphere Explorer C satellite were used in a comparative study with Parker's theory regarding the charged particle distribution in the near wake of an ionospheric satellite (1976). It is shown that theory and experiment agree fairly well in the angle-of-attack range between 90 and 135 deg. In the maximum rarefaction zone (between 145 and 180 deg), however, the theoretical model overestimates the measured ion depletion by several orders of magnitude. A comparison between theory and the Explorer 31 electron measurements shows that the theory again overestimates the electron depletion. These discrepancies are mainly due to the use of a steady-state theory and a single ion equation (using a mean ion mass). Improved agreement between theory and experiment can be obtained by the use of the time-dependent Vlasov-Poisson equations with separate equations for the various ion species.

Samir, U.↗
DOE OSTI2024

Analytic Nuclear Gradients for Complete Active Space Linearized Pair-Density Functional Theory

Accurately modeling photochemical reactions is difficult due to the presence of conical intersections and locally avoided crossings, as well as the inherently multiconfigurational character of excited states. As such, one needs a multistate method that incorporates state interaction in order to accurately model the potential energy surface at all nuclear coordinates. The recently developed linearized pair-density functional theory (L-PDFT) is a multistate extension of multiconfiguration PDFT, and it has been shown to be a cost-effective post-MCSCF method (as compared to more traditional and expensive multireference many-body perturbation methods or multireference configuration interaction methods) that can accurately model potential energy surfaces in regions of strong nuclear–electronic coupling in addition to accurately predicting Franck–Condon vertical excitations. Here, in this paper, we report the derivation of analytic gradients for L-PDFT and their implementation in the PySCF-forge software, and we illustrate the utility of these gradients for predicting ground- and excited-state equilibrium geometries and adiabatic excitation energies for formaldehyde, s-trans-butadiene, phenol, and cytosine.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Developing reliable machine learning interatomic potential for Fe–Cr–Ni austenitic alloys

Gaining atomistic understanding of mechanical behavior of heat-resistant structural materials such as Fe–Cr–Ni-based alloys requires an approach with an accuracy close to density functional theory (DFT) that considers the intrinsic properties of the bulk lattice and important defects such as stacking faults, grain boundaries, and surfaces. This work aims to develop reliable machine learning interatomic potential (MLIAP) at cross-scale for Fe–Cr–Ni ternary alloys with a focus on the face-centered-cubic (fcc) solid solution structure. Leveraging the advantages of moment tensor potentials, which typically necessitate a relatively small training dataset and enable rapid calculations using the large-scale atomic/molecular massively parallel simulator package, we ensure the stability and accuracy of the trained potentials. Important defects such as stacking faults, grain boundaries, and surfaces for wide-range compositions are investigated. Structural, thermal, elastic, and defect properties are determined from molecular dynamics simulations comprising several thousand atoms, generated via canonical Monte Carlo simulations guided by the trained potential. The trained potential allows efficient atomic simulations of structural, thermal, and mechanical properties of fcc Fe–Cr–Ni solid solution alloys as a function of composition and temperature. Therefore, the MLIAP approach represents a major advancement from DFT calculations that are limited to small simulation sizes and traditional molecular dynamics simulations using relatively low accuracy potentials. Furthermore, this work outlines a practical foundation for further investigating the structural evolution and mechanical behavior of austenitic stainless steel and nickel-based alloys in a wide array of applications in extreme environments.

Crystal structure↗
DOE OSTI2022

The theory of transport in helical spin-structure crystals

Abstract We study helical structures in spin-spiral single crystals. In the continuum approach for the helicity potential energy the simple electronic band splits into two non-parabolic bands. For low exchange integrals, the lower band is described by a surface with a saddle shape in the direction of the helicity axis. Using the Boltzmann equation with the relaxation due to acoustic phonons, we discover the dependence of the current on the angle between the electric field and helicity axis leading to the both parallel and perpendicular to the electric field components in the electroconductivity. The latter can be interpreted as a planar Hall effect. In addition, we find that the transition rates depend on an electron spin allowing the transition between the bands. The electric conductivities exhibit nonlinear behaviors with respect to chemical potential µ . We explain this effect as the interference of the band anisotropy, spin conservation, and interband transitions. The proposed theory with the spherical model in the effective mass approximation for conduction electrons can elucidate nonlinear dependencies that can be identified in experiments. We find the excellent agreement between the theoretical and experimental data for parallel resistivity depending on temperature at the phase transition from helical to ferromagnetic state in a M n P single crystal. In addition, we predict that the perpendicular resistivity abruptly drops to zero in the ferromagnetic phase.

Physics↗
DOE OSTI2024

Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces

Performing reliable computer simulations of elementary processes occurring at metal–water interfaces is pivotal for novel catalyst design in sustainable energy applications. Computational catalyst design hinges on the ability to reliably and efficiently compute the potential energy surface (PES) of the system. Here, due to the large system sizes needed for studying processes at liquid water–metal interfaces, these systems can currently not be described using density functional theory (DFT). In this work, we used a hybrid quantum mechanical, molecular mechanical, and machine learning potential for studying the adsorption behavior of phenol, atomic hydrogen, 2-butanol, and 2-butanone on the (0001) facet of Ru under reducing conditions when Ru is not oxidized. Specifically, we describe the adsorbate and the surrounding metal atoms at the DFT level of theory. Here, we also considered the electrostatic field effect of the water molecules on adsorbate–metal interactions. Next, for the water–water and water–adsorbate interactions, we used established classical force fields. Finally, for the water–Ru surface interaction, for which no reliable force fields have been published, we used Behler–Parrinello high-dimensional neural network potentials (HDNNPs). Employing this setup, we used our explicit solvation for metal surface (eSMS) approach to compute the aqueous-phase effect on the low-coverage adsorption of selected molecules and atoms on the (0001) facet of Ru. In agreement with previous experimental and computational studies of oxygenated molecules over transition metal facets, we found that liquid water destabilizes the tested adsorbates on Ru(0001). Interestingly, our findings indicate that adsorbates on Ru are less affected by the presence of an aqueous phase than on other transition metals (e.g., Pt), highlighting the necessity of experimental investigations of Ru-based catalytic systems in liquid water.

Adsorption↗
DOE OSTI2024

Energy momentum tensor on and off the light cone: exposition with scalar Yukawa theory

Abstract We compute the gravitational form factorsA i ,D i and$$ {\overline{c}}_i $$ c ¯ i of the scalar Yukawa theory using both the light-cone and covariant perturbation theory at the one-loop level. The light-cone formalism provides a potential approach to access these form factors beyond the perturbative regime. However, unlike the covariant formulation, the Poincaré symmetry on the light cone is not manifest. In this work, we use perturbation theory as a benchmark to extract the gravitational form factors from the light-front energy-momentum tensor. By comparing results on and off the light cone, we identifyT ++ ,T +a ,T +− ,T 12 as the “good currents” that are properly renormalized and can be used to extract the gravitational form factors.

Physics↗
DOE OSTI2026

Ab initio thermodynamics of Ni and Co incorporation in Mg hydroxide, carbonate, and hydroxycarbonate minerals

Ni and Co are critical elements needed for modern technologies, and a better understanding of the ability of Mg-based minerals to incorporate these elements would benefit strategy development for Ni and Co recovery from mafic and ultramafic deposits. Here, in this work, we performed density functional theory (DFT) calculations of Ni and Co incorporation in six potential products of the carbonation of mafic and ultramafic silicates: brucite (Mg(OH) 2 ), magnesite (MgCO 3 ), nesquehonite (MgCO 3 ⸱3H 2 O), lansfordite (MgCO 3 ⸱5H 2 O), artinite (Mg 2 CO 3 (OH) 2 ⸱3H 2 O), and hydromagnesite (Mg 5 (CO 3 ) 4 (OH) 2 ⸱4H 2 O). The DFT results were used in an ab initio thermodynamics framework to explore the pH 2 O–pCO 2 conditions at which the Mg-based minerals were predicted to be thermodynamically stable and to quantify the Gibbs free energy of Ni and Co substitution at Mg sites. Among the six Mg-based minerals, brucite and magnesite were predicted to have the lowest Ni and Co substitution free energy. An analysis of the effect of temperature indicated that, at low temperature (<100 K), brucite more readily accommodated Ni and Co, while, at higher temperature (>335 K), magnesite more favorably incorporated Ni and Co. Between 100 K and 335 K, Ni was predicted to preferentially substitute for Mg in brucite and Co for Mg in magnesite, thus leading to a driving force for separating Ni and Co in conditions where brucite and magnesite both form. Insights gained in this work could therefore help select experimental conditions that either promote or inhibit incorporation of these critical elements into Mg-based mineral phases.

Critical elements↗
DOE OSTI2025

The hidden influence of terrestrial groundwater on salt marsh function and resilience

Salt marshes are hotspots of nutrient processing and carbon sequestration. So far, studies addressing spatiotemporal variability in and drivers of salt marsh biogeochemical function, carbon storage and resilience have focused on ocean-driven surface hydrologic influences, neglecting effects of terrestrial hydrology through subsurface connections. Here we evaluate drivers of salt marsh redox potential, a proxy for biogeochemical state, through wavelet analyses and information theory using data from seven marshes. The results point to terrestrial groundwater level as a dominant control on redox variability across all sites. Because redox is a key driver of biogeochemical processes, and specifically oxidation of organic matter that sequesters carbon and maintains marsh elevation, these terrestrial influences are critical to understanding marsh function and evolution. Further, the newly identified links between onshore groundwater levels and marsh redox conditions shift the traditional paradigm and suggest that terrestrial hydrology is a primary control on salt marsh carbon sequestration potential and resilience.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Calculations of rate constants for the three-body recombination of H2 in the presence of H2

A new global potential energy hypersurface for H2 + H2 is constructed and quasiclassical trajectory calculations performed using the resonance complex theory and energy transfer mechanism to estimate the rate of three body recombination over the temperature range 100 to 5000 K. The new potential is a faithful representation of ab initio electron structure calculations, is unchanged under the operation of exchanging H atoms, and reproduces the accurate H3 potential as one H atom is pulled away. Included in the fitting procedure are geometries expected to be important when one H2 is near or above the dissociation limit. The dynamics calculations explicitly include the motion of all four atoms and are performed efficiently using a vectorized variable-stepsize integrator. The predicted rate constants are approximately a factor of two smaller than experimental estimates over a broad temperature range.

Schwenke, David W.↗
NASA NTRS1988

Calculations of rate constants for the three-body recombination of H2 in the presence of H2

A new global potential energy hypersurface for H2 + H2 is constructed and quasiclassical trajectory calculations performed using the resonance complex theory and energy transfer mechanism to estimate the rate of three body recombination over the temperature range 100 to 5000 K. The new potential is a faithful representation of ab initio electron structure calculations, is unchanged under the operation of exchanging H atoms, and reproduces the accurate H3 potential as one H atom is pulled away. Included in the fitting procedure are geometries expected to be important when one H2 is near or above the dissociation limit. The dynamics calculations explicitly include the motion of all four atoms and are performed efficiently using a vectorized variable-stepsize integrator. The predicted rate constants are approximately a factor of two smaller than experimental estimates over a broad temperature range.

Schwenke, David W.↗
NASA NTRS2008

Signal Detection Theory Applied to Helicopter Transmission Diagnostic Thresholds

Helicopter Health Usage Monitoring Systems (HUMS) have potential for providing data to support increasing the service life of a dynamic mechanical component in the transmission of a helicopter. Data collected can demonstrate the HUMS condition indicator responds to a specific component fault with appropriate alert limits and minimal false alarms. Defining thresholds for specific faults requires a tradeoff between the sensitivity of the condition indicator (CI) limit to indicate damage and the number of false alarms. A method using Receiver Operating Characteristic (ROC) curves to assess CI performance was demonstrated using CI data collected from accelerometers installed on several UH60 Black Hawk and AH64 Apache helicopters and an AH64 helicopter component test stand. Results of the analysis indicate ROC curves can be used to reliably assess the performance of commercial HUMS condition indicators to detect damaged gears and bearings in a helicopter transmission.

Dempsey, Paula J.↗
NASA NTRS2009

Signal Detection Theory Applied to Helicopter Transmission Diagnostic Thresholds

Helicopter Health Usage Monitoring Systems (HUMS) have potential for providing data to support increasing the service life of a dynamic mechanical component in the transmission of a helicopter. Data collected can demonstrate the HUMS condition indicator responds to a specific component fault with appropriate alert limits and minimal false alarms. Defining thresholds for specific faults requires a tradeoff between the sensitivity of the condition indicator (CI) limit to indicate damage and the number of false alarms. A method using Receiver Operating Characteristic (ROC) curves to assess CI performance was demonstrated using CI data collected from accelerometers installed on several UH60 Black Hawk and AH64 Apache helicopters and an AH64 helicopter component test stand. Results of the analysis indicate ROC curves can be used to reliably assess the performance of commercial HUMS condition indicators to detect damaged gears and bearings in a helicopter transmission.

Dempsey, Paula J.↗
NASA NTRS1999

Recent Development on O(+) - O Collision Frequency and Ionosphere-Thermosphere Coupling

The collision frequency between an oxygen atom and its singly charged ion controls the momentum transfer between the ionosphere and the thermosphere. There has been a long standing discrepancy, extending over a decade, between the theoretical and empirical determination of this frequency: the empirical value of this frequency exceeded the theoretical value by a factor of 1.7. Recent improvements in theory were obtained by using accurate oxygen ion-oxygen atom potential energy curves, and partial wave quantum mechanical calculations. We now have applied three independent statistical methods to the observational data, obtained at the MIT/Millstone Hill Observatory, consisting of two sets A and B. These methods give results consistent with each other, and together with the recent theoretical improvements, bring the ratio close to unity, as it should be. The three statistical methods lead to an average for the ratio of the empirical to the theoretical values equal to 0.98, with an uncertainty of +/-8%, resolving the old discrepancy between theory and observation. The Hines statistics, and the lognormal distribution statistics, both give lower and upper bounds for the Set A equal to 0.89 and 1.02, respectively. The related bounds for the Set B are 1.06 and 1.17. The average values of these bounds thus bracket the ideal value of the ratio which should be equal to unity. The main source of uncertainties are errors in the profile of the oxygen atom density, which is of the order of 11%. An alternative method to find the oxygen atom density is being suggested.

Omidvar, K.↗
DOE OSTI2020

A Comparative Study of Redox Mediators for Improved Performance of Li-Oxygen Batteries.

Redox meditators (RMs) are soluble catalysts located in an electrolyte that can improve the energy efficiency (reduced overpotential) and cyclability of Li-oxygen (Li-O-2) batteries. In this work, 20 RMs within a Li-O-2 system with dimethyl sulfoxide and tetraethylene glycol dimethyl ether electrolytes are studied and their electrochemical features such as redox potential, the separation of cathodic and anodic peaks, and their current intensities are measured using cyclic voltammetry (CV) experiments. Six RMs are selected as "primary" choices based on their electrochemical performance, and stability tests are then performed to examine their electrochemical responses after consecutive cycles. Moreover, galvanostatic cycling tests are performed within a Li-O-2 battery system assembled with selected six RMs for real case consistency investigations. It is found that results from CV to galvanostatic cycling tests are consistent for halides and organometallic RMs, where the former exhibit much higher stability. However, the organic RMs show high reversibility in CV but low in battery cycling results. Density functional theory calculations are carried out to gain more understanding of the stability and redox potentials of the RMs. This study provides comparative information to select the most reliable RMs for Li-O-2 batteries along with new fundamental understanding of their electrochemical activity and stability.

cyclic voltammetry↗
DOE OSTI2022

Building surrogate models of nuclear density functional theory with Gaussian processes and autoencoders

From the lightest Hydrogen isotopes up to the recently synthesized Oganesson (Z = 118), it is estimated that as many as about 8,000 atomic nuclei could exist in nature. Most of these nuclei are too short-lived to be occurring on Earth, but they play an essential role in astrophysical events such as supernova explosions or neutron star mergers that are presumed to be at the origin of most heavy elements in the Universe. Understanding the structure, reactions, and decays of nuclei across the entire chart of nuclides is an enormous challenge because of the experimental difficulties in measuring properties of interest in such fleeting objects and the theoretical and computational issues of simulating strongly-interacting quantum many-body systems. Nuclear density functional theory (DFT) is a fully microscopic theoretical framework which has the potential of providing such a quantitatively accurate description of nuclear properties for every nucleus in the chart of nuclides. Thanks to high-performance computing facilities, it has already been successfully applied to predict nuclear masses, global patterns of radioactive decay like β or γ decay, and several aspects of the nuclear fission process such as, e.g., spontaneous fission half-lives. Yet, predictive simulations of nuclear spectroscopy—the low-lying excited states and transitions between them—or of nuclear fission, or the quantification of theoretical uncertainties and their propagation to basic or applied nuclear science applications, would require several orders of magnitude more calculations than currently possible. However, most of this computational effort would be spent into generating a suitable basis of DFT wavefunctions. Such a task could potentially be considerably accelerated by borrowing tools from the field of machine learning and artificial intelligence. In this paper, we review different approaches to applying supervised and unsupervised learning techniques to nuclear DFT.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Accurate and efficient interatomic potentials are essential for molecular dynamics (MD) simulations of radiation damage, gas diffusion, and phase stability in complex ceramics such as LiAlO 2 , especially under extreme conditions relevant to tritium production. Here, we evaluate the performance of six machine-learned interatomic potentials (MLIPs), moment tensor potential (MTP), Gaussian approximation potential, deep potential (DeePMD), atomic cluster expansion (ACE), message-passing ACE (multilayer atomic cluster expansion (MACE) pretrained) and MACE (trained from-scratch), all trained on the same density functional theory dataset with inclusion of tritium. The MLIPs are benchmarked against traditional Buckingham and ReaxFF potentials in terms of energy accuracy, density predictions, thermal equilibration behavior, threshold displacement energy (E d ), tritium diffusivity, and computational cost. Among the models, MTP shows the best overall balance between efficiency and accuracy, with low force and energy errors and realistic E d values for Li and Al. The ACE and MACE (pretrained and trained from scratch) models exhibit high E d (>200 eV) and unphysical pair interactions. DeePMD underestimates Ed due to overly repulsive behavior even at equilibrium distances. All models over-estimate tritium diffusion but the pretrained MACE model behaves well during tritium-diffusion simulations up to 500 K, maintaining diffusivities in the physically consistent 10 −11 m 2 /s range. Finally, we quantify the computational cost of each potential in large-scale atomic/molecular massively parallel simulator, finding that only MTP is more efficient than traditional empirical potentials, while others are significantly more expensive. These findings explain the trade-offs between accuracy and computational cost in MLIP development and provide essential guidance for use in high-throughput radiation damage and gas diffusion simulations in nuclear ceramics.

74 ATOMIC AND MOLECULAR PHYSICS↗