Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “nearest neighbors”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Novel local symmetries and chiral-symmetry-broken phases in S = 1/2 triangular-lattice Heisenberg model

Using a nonmean-field approach the triangular-lattice S = 1/2 Heisenberg antiferromagnet with nearest- and next-nearest-neighbor couplings is shown undergo an Ising-type phase transition into a chiral-symmetry-broken phase (Kalmeyer-Laughlin-like state) at small T. Removal of next-nearest-neighbor coupling introduces a local Z2 symmetry, thereby suppressing any finite-T chiral order.

Baskaran, G.↗
DOE OSTI2020

An efficient random-sampling method for calculating double occupancy of Gutzwiller wave function in single-band 1D and 2D lattices

In this paper, we report a random sampling method for computing the expectation value of physical quantities based on the Gutzwiler variational wave function. As the first application, we calculated the double occupancy, which is a critical quantity for under- standing the correlation effects in many-body systems, for single-band 1D and 2D lattices. We demonstrated that the random sampling scheme is more efficient than an existing Metropolis Monte-Carlo algorithm. For the 1D Hubbard model with only nearest-neighbor hopping, our results are almost identical to the exact analytic solution. We have also studied systems to which analytic solutions are not available, including the 1D lattices with next-nearest-neighbor hopping and 2D lattices. In addition, constraints on real-space con gurations can be easily implemented in the current scheme to further improve the Gutzwiller wave function. As an example, we calculated the double occupancy for 1D Hubbard model by applying the constraint that all double-occupied sites are paired with an empty site. With enhanced correlation between double-occupied and empty sites, the constraint results in much improved ground-state energy for 1D Hubbard model with strong on-site repulsion.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1993

The small scale environment of low surface brightness disk galaxies

We use a sample of about 340 low surface brightness (LSB) disk galaxies with measured redshifts in combination with the Center for Astrophysics redshift survey to test the hypothesis that LSB galaxies have a deficit of nearby companion galaxies compared to high surface brightness (HSB) disk galaxies. We find a very strong statistical deficit of galaxies located within a projected radius of 0.5 Mpc and within a velocity of 500 km/s around LSB disk galaxies compared to HSB ones. Further, comparing LSB and HSB disk galaxies which are located in the same portion of the sky indicates that the average distance to the nearest neighbor is 1.7 times farther for LSB disk galaxies. A Komologorov-Smirnoff test rules out, at greater than the 99 percent confidence level, the hypothesis that the distribution of nearest-neighbor distances is the same for HSB and LSB disk galaxies. We speculate that LSB disk galaxies have relatively long formation time scales and therefore must form in relative isolation. In addition, the lack of tidal interactions over a Hubble time serves to suppress the overall star-formation rate as no external trigger is available to help clump the gas. The observed low surface densities of H I in combination with the low probability of tidal interactions effectively prevents these disk galaxies from evolving very rapidly.

Bothun, Gregory D.↗
DOE OSTI2022

Chemical and Structural Alterations in the Amorphous Structure of Obsidian due to Nanolites

Obsidian is volcanic glass that results from the rapid cooling of silica-rich melt. Nanoscale crystallites precipitate out of the melt prior to solidification and remain embedded in the amorphous matrix. These crystallites provide information on the flow kinetics and composition of the melt. Due to the sparsity and size of nanolites, studies often focus on supramicron crystallites. This research takes advantage of the conchoidal fracture of obsidian by knapping samples with nanometer-thin edges for transmission electron microscopy characterization. Nanolites in the amorphous matrix are studied using energy-dispersive spectroscopy (EDS) and electron diffraction. Certain alkali and alkaline-earth cations exhibit patterns of depletion near Fe-oxide nanolites. EDS is used to identify nanolites and variations in the composition of the matrix. Parallel beam diffraction and radial distribution function analysis of nearest-neighbor distances determine average bond lengths in the matrix near nanolites, showing that nanolites influence the nearby short-range ordering and atomic character of the matrix. Analysis reveals decreased mean nearest-neighbor distances in the matrix adjacent to nanolites compared to the bulk. Our methods exhibit the required sensitivity to detect variations in the composition and structure near nanolites, and our findings indicate that obsidian nanolites contribute to quantifiable localized changes in the amorphous structure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dynamics of a fractal set of first-order magnetic phase transitions in frustrated Lu 2 CoMnO 6

The axial next-nearest-neighbor Ising model predicts a fractal (infinite) set of phases with incommensurate wave vectors that are separated by first-order phase boundaries. This complexity results from a simple frustration condition between nearest- and next-nearest-neighbor interactions along a chain of Ising spins. Using x-ray photon correlation spectroscopy (XPCS), we investigate the surprising antiferromagnetic dynamics that emerge from such a complex phase diagram over a wide range of temperatures. In this work, we present XPCS measurements of the frustrated magnetic chain compound Lu 2 CoMnO 6 and Monte Carlo simulations. Incommensurate magnetic Bragg peaks slide towards commensurate “up-up-down-down” spin order with decreasing temperature and increasing time. Both simulation and experiment support a counterintuitive “upside-down” temperature dependence of the magnetic dynamics: at higher temperatures in the region of first-order phase boundaries, slower dynamics are observed where the speckle maintains its coherence. At the lowest temperatures, where part of the sample adopts commensurate order, the dynamics speed up and result in fast decoherence.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Global phase diagram of D-wave superconductivity in the square-lattice t-J model

The Hubbard and closely related t-J models are exciting platforms for unconventional superconductivity (SC). Through state-of-the-art density matrix renormalization group calculations using the grand canonical ensemble, we address open issues regarding the ground-state phase diagram of the extended t-J model on a square lattice in the parameter regime relevant to cuprate superconductors. On large 8-leg cylinders, we demonstrate that the pure t-J model with only nearest-neighbor hoppings and superexchange interactions, for a wide range of doping ( δ = 0.1 to 0.2 ), hosts robust d-wave superconductivity possibly coexisting with weak unidirectional pair density wave. Furthermore, a small next nearest neighbor hopping t 2 suppresses pair and charge density waves, resulting in a uniform d-wave SC phase in both electron- and hole-doped cuprate model systems. Our work validates the t-J model as a proper minimum model for the emergence of superconductivity in cuprate superconductors.

Chen, Feng (ORCID:000000018196030X)↗
NASA NTRS2011

Kinetic Monte Carlo Investigation of the Effects of Vacancy Pairing on Oxygen Diffusivity in Yttria-Stabilized Zirconia

Yttria-stabilized zirconia s high oxygen diffusivity and corresponding high ionic conductivity, and its structural stability over a broad range of temperatures, have made the material of interest for use in a number of applications, for example, as solid electrolytes in fuel cells. At low concentrations, the stabilizing yttria also serves to increase the oxygen diffusivity through the presence of corresponding oxygen vacancies, needed to maintain charge neutrality. At higher yttria concentration, however, diffusivity is impeded by the larger number of relatively high energy migration barriers associated with yttrium cations. In addition, there is evidence that oxygen vacancies preferentially occupy nearest-neighbor sites around either dopant or Zr cations, further affecting vacancy diffusion. We present the results of ab initio calculations that indicate that it is energetically favorable for oxygen vacancies to occupy nearest-neighbor sites adjacent to Y ions, and that the presence of vacancies near either species of cation lowers the migration barriers. Kinetic Monte Carlo results from simulations incorporating this effect are presented and compared with results from simulations in which the effect is not present.

Good, Brian S.↗
DOE OSTI2021

Exact bounds for dynamical critical exponents of transverse-field Ising chains with a correlated disorder

Highlights: • Analytic results in disordered quantum systems are obtained. • Correlated disorder changes the universality class of quantum phase transitions. • The lower and upper bounds of the dynamical critical exponent are obtained. This study investigates the dynamical critical exponent of disordered Ising chains under transverse fields to examine the effect of a correlated disorder on quantum phase transitions. The correlated disorder, where the on-site transverse field depends on the nearest-neighbor coupling strengths connecting the site, gives a qualitatively different result from the uncorrelated disorder. In the uncorrelated disorder cases where the transverse field is either homogeneous over sites or random independently of the nearest-neighbor coupling strengths, the dynamical critical exponent is infinite. In contrast, in the presence of the correlated disorder, we analytically show that the dynamical critical exponent is finite. We also show that the dynamical critical exponent depends on the tuning process of the transverse field strengths.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1990

Distributed memory approaches for robotic neural controllers

The suitability is explored of two varieties of distributed memory neutral networks as trainable controllers for a simulated robotics task. The task requires that two cameras observe an arbitrary target point in space. Coordinates of the target on the camera image planes are passed to a neural controller which must learn to solve the inverse kinematics of a manipulator with one revolute and two prismatic joints. Two new network designs are evaluated. The first, radial basis sparse distributed memory (RBSDM), approximates functional mappings as sums of multivariate gaussians centered around previously learned patterns. The second network types involved variations of Adaptive Vector Quantizers or Self Organizing Maps. In these networks, random N dimensional points are given local connectivities. They are then exposed to training patterns and readjust their locations based on a nearest neighbor rule. Both approaches are tested based on their ability to interpolate manipulator joint coordinates for simulated arm movement while simultaneously performing stereo fusion of the camera data. Comparisons are made with classical k-nearest neighbor pattern recognition techniques.

Jorgensen, Charles C.↗
DOE OSTI2025

Two transitions in complex eigenvalue statistics: Hermiticity and integrability breaking

Open quantum systems have complex energy eigenvalues which are expected to follow non-Hermitian random matrix statistics, when chaotic, or two-dimensional (2d) Poisson statistics, when integrable. We investigate the spectral properties of a many-body quantum spin chain, i.e., the Hermitian Heisenberg model with imaginary disorder. Its rich complex eigenvalue statistics is found to separately break both Hermiticity and integrability at different scales of the disorder strength. With no disorder, the system is integrable and Hermitian, with spectral statistics corresponding to the 1d Poisson point process. At very small disorder, we find a transition from 1d Poisson statistics to an effective D -dimensional Poisson point process, showing Hermiticity breaking. At intermediate disorder, we find integrability breaking, as inferred from the statistics matching that of non-Hermitian complex symmetric random matrices in class AI † . For large disorder, as the spins align, we recover the expected integrability (now in the non-Hermitian setup), indicated by 2d Poisson statistics. These conclusions are based on fitting the spin-chain data of numerically generated nearest- and next-to-nearest-neighbor spacing distributions to an effective 2d Coulomb gas description at inverse temperature β . We confirm that such an effective description of random matrices also applies in classes AI † and AII † up to next-to-nearest-neighbor spacings. Published by the American Physical Society 2025

Akemann, Gernot (ORCID:0000000217104258)↗
DOE OSTI2021

Deterministic Fast Scrambling with Neutral Atom Arrays

Fast scramblers are dynamical quantum systems that produce many-body entanglement on a timescale that grows logarithmically with the system size N. Here, we propose and investigate a family of deterministic, fast scrambling quantum circuits realizable in near-term experiments with arrays of neutral atoms. We show that three experimental tools—nearest-neighbor Rydberg interactions, global single-qubit rotations, and shuffling operations facilitated by an auxiliary tweezer array—are sufficient to generate nonlocal interaction graphs capable of scrambling quantum information using only O(logN) parallel applications of nearest-neighbor gates. These tools enable direct experimental access to fast scrambling dynamics in a highly controlled and programmable way and can be harnessed to produce highly entangled states with varied applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1988

Spatial Distribution of Lightning Strikes to Ground During Small Thunderstorms in Florida

The spatial patterns of the strike points produced by cloud-to-ground lightning under three small thunderstorms have been analyzed to determine the area flash density as a function of radius from the storm center, the distribution of the nearest-neighbor distances, and the distribution of the horizontal distances between successive flashes. The storm average flash densities range from about 0.8 to 1.6 Fl/km squared, and the average lightning fluxes range from 0.03 to 0.05 Fl/km squared/min. The mean nearest-neighbor distances are about 0.7 km and smaller, but are still in good agreement with a theory that assumes an infinite and uniform flash density. The mean distance between successive flashes ranges from 3.2 to 4.2 km, and a sizable fraction of this variation could be due to channel geometry.

Krider, E. Philip↗
DOE OSTI2021

Canted antiferromagnetic order and spin dynamics in the honeycomb-lattice compound Tb 2 Ir 3 Ga 9

Here, single-crystal neutron diffraction, inelastic neutron scattering, bulk magnetization measurements, and first-principles calculations are used to investigate the magnetic properties of the honeycomb lattice Tb 2 Ir 3 Ga 9 . While the R ln 2 magnetic contribution to the low-temperature entropy indicates a J eff = 1 / 2 moment for the lowest-energy crystal-field doublet, the Tb 3 + ions form a canted antiferromagnetic structure below 12.5 K. Due to the Dzyaloshinskii-Moriya interactions, the Tb moments in the a b plane are slightly canted towards b with a canted moment of 1.22 μ B per formula unit. A minimal x x z spin Hamiltonian is used to simultaneously fit the spin-wave frequencies along the high-symmetry directions and the field dependence of the magnetization along the three crystallographic axes. Long-range magnetic interactions for both in-plane and out-of-plane couplings up to the second nearest neighbors are needed to account for the observed static and dynamic properties. The z component of the exchange interactions between Tb moments is larger than the x and y components. This compound also exhibits bond-dependent exchange with negligible nearest-neighbor exchange coupling between moments parallel and perpendicular to the 4 f orbitals. Despite the J eff = 1 / 2 moments, the spin Hamiltonian is denominated by a large in-plane anisotropy K z ~ – 1 meV . DFT calculations confirm the antiferromagnetic ground state and the substantial interplane coupling at larger Tb-Tb distances.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1993

Rectangular Array Of Digital Processors For Planning Paths

Prototype 24 x 25 rectangular array of asynchronous parallel digital processors rapidly finds best path across two-dimensional field, which could be patch of terrain traversed by robotic or military vehicle. Implemented as single-chip very-large-scale integrated circuit. Excepting processors on edges, each processor communicates with four nearest neighbors along paths representing travel to north, south, east, and west. Each processor contains delay generator in form of 8-bit ripple counter, preset to 1 of 256 possible values. Operation begins with choice of processor representing starting point. Transmits signals to nearest neighbor processors, which retransmits to other neighboring processors, and process repeats until signals propagated across entire field.

Kemeny, Sabrina E.↗
NASA NTRS2016

Primary Dendrite Arm Spacing and Trunk Diameter in Al-7-Weight-Percentage Si Alloy Directionally Solidified Aboard the International Space Station

Under a NASA-ESA collaborative research project, three Al-7-weight-percentage Si samples (MICAST-6, MICAST-7 and MICAST 2-12) were directionally solidified aboard the International Space Station to determine the effect of mitigating convection on the primary dendrite array. The samples were approximately 25 centimeters in length with a diameter of 7.8 millimeter-diameter cylinders that were machined from [100] oriented terrestrially grown dendritic Al-7Si samples and inserted into alumina ampoules within the Sample Cartridge Assembly (SCA) inserts of the Low Gradient Furnace (LGF). The feed rods were partially remelted in space and directionally solidified to effect the [100] dendrite-orientation. MICAST-6 was grown at 5 microns per second for 3.75 centimeters and then at 50 microns per second for its remaining 11.2 centimeters of its length. MICAST-7 was grown at 20 microns per second for 8.5 centimeters and then at 10 microns per second for 9 centimeters of its remaining length. MICAST2-12 was grown at 40 microns per second for 11 centimeters. The thermal gradient at the liquidus temperature varied from 22 to 14 degrees Kelvin per centimeter during growth of MICAST-6, from 26 to 24 degrees Kelvin per centimeter for MICAST-7 and from 33 to 31 degrees Kelvin per centimeter for MICAST2-12. Microstructures on the transverse sections along the sample length were analyzed to determine nearest-neighbor spacing of the primary dendrite arms and trunk diameters of the primary dendrite-arrays. This was done along the lengths where steady-state growth prevailed and also during the transients associated with the speed-changes. The observed nearest-neighbor spacings during steady-state growth of the MICAST samples show a very good agreement with predictions from the Hunt-Lu primary spacing model for diffusion controlled growth. The observed primary dendrite trunk diameters during steady-state growth of these samples also agree with predictions from a coarsening-based model. The radial macrosegregation and "steepling" caused by thermosolutal convection during terrestrial growth of the Al-7Si was not observed in the space-grown MICAST samples.

Ghods, M.↗
NASA NTRS1960

Vacancy Relaxation in Cubic Crystals

The configuration of the atoms surrounding a vacancy in four face-centered cubic and three body-centered cubic metals has been computed, using a pairwise, central-force model in which the energy of interaction between two atoms was taken to have the form of a Morse function. Only radial relaxations were considered. The first and second nearest-neighbor relaxations for the face-centered systems were found to be: Pb (1.42,−0.43), Ni (2.14,−0.39), Cu(2.24,−0.40) and Ca (2.73,−0.41, expressed in percentages of normal distances. For the body-centered systems the relaxations out to the fourth nearest neighbors to the vacancy were: Fe (6.07,−2.12, −0.25, −), Ba (7.85, −2.70, 0.70, −0.33) and Na (10.80, −3.14, 3.43, −0.20). The positive signs indicate relaxation toward the vacancy and the negative signs indicate relaxation away from the vacancy. The energies of relaxation (eV) are: Pb (0.162), Ni (0.626), Cu (0.560), Ca (0.400), Fe (1.410), Ba (0.950) and Na (0.172).

Girifalco, L. A.↗
DOE OSTI2023

Aggregation of Size-Selected Oxide Clusters Deposited onto Au(111)

Kinetic Monte Carlo (kMC) simulations along with density functional theory (DFT) calculations were used to investigate the aggregation of size-selected Nb 3 O y (y = 5, 6, 7) clusters deposited onto the Au(111) surface. Recent STM experiments showed that the cluster binding sites and sizes of the cluster assemblies on the Nb 3 O y /Au(111) surfaces strongly depend on the stoichiometry of the clusters, i.e., the oxygen-to-niobium ratio. To better understand the origins of these differences, kMC simulations of the nucleation and growth of cluster assemblies were performed using energy barriers for diffusion and intercluster interactions estimated from DFT calculations of cluster binding and dimerization energies, respectively. Comparisons of the kMC simulations with STM images of the as-deposited Nb 3 O y /Au(111) surfaces at RT and after high temperature annealing were used to further optimize the energetics and gauge the importance of nearest neighbor interactions. The kMC simulations demonstrate that the assembly of Nb 3 O y clusters on Au(111) are largely controlled by the magnitude of the barriers for diffusion and interparticle-bond formation, while changes at higher temperatures are sensitive to the binding energies between nearest neighbors. Simulations for the Nb 3 O 5 and Nb 3 O 6 clusters, which exhibit smaller cluster assembly sizes in STM, required larger diffusion barriers as well as different barriers for interparticle binding, which reflected differences in DFT calculated dimerization energies. Furthermore, the results demonstrate the effectiveness of combined DFT and kMC calculations for understanding how the stoichiometry affects the aggregation of small oxide clusters on a metal surface.

36 MATERIALS SCIENCE↗
NASA NTRS2024

Interpretable Machine Learning for Molecular Biosignatures: a Novel Single-Sample Feature Importance Method That Is Sensitive To Statistical Interactions

Isotope ratio mass spectrometry (IRMS) of volatiles (e.g., CO 2 ) promises to be a powerful tool for potential biosignature detection for future missions to ocean worlds (OW) such as Europa and Enceladus. Machine learning (ML) methods for IRMS data could enable science autonomy by onboard prediction of seawater chemistry and biosignature presence. However, ML models are likely to be complex and involve statistical interactions between features (variables), which can make predictions seem opaque and enigmatic. For ML predictions as significant as extraterrestrial biosignatures, we must place extraordinary confidence in models. It is therefore essential that these models make interpretable predictions (i.e., human-understandable) and include false-prediction diagnostics. We achieve high accuracy and interpretability in ML biosignature and seawater chemistry models for OW through a nearest-neighbors feature selection tool that detects statistical interactions between predictors, constructs interaction networks for visualization of selected features working together to make a prediction, and reports single-sample feature importance scores for false-detection diagnostics. Here we develop a novel single-sample nearest-neighbors projected distance regression(ssNPDR) feature selection method that improves upon existing single-sample algorithms through the inclusion of statistical interactions while providing false-prediction diagnostics for ML models.

geochemistry↗