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At least 271 records · Page 15

Study of Radiative Heat Transfer and Flow Physics from Medium-scale Methanol Pool Fire Simulations [Slides]

Analysis of methanol pool fire conducted as part of validation study for SIERRA/Fuego. Radiation model was effectively calibrated by modifying radiation model parameters for methanol. Computing integrated buoyancy flux, entrainment rate, and turbulent kinetic energy allowed for evaluation of less typical quantities in this validation study. Quantities were compared with experimental data or correlations and generally showed agreement. TKE needed fine mesh to be computed accurately. Predicted flame height less sensitive to variations in mixture fraction than temperature. Mixture fraction is a preferable threshold variable for this application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sitewise manipulations and Mott insulator-superfluid transition of interacting photons using superconducting circuit simulators

We report that the Bose Hubbard model (BHM) of interacting bosons in a lattice has been a paradigm in many-body physics, and it exhibits a Mott insulator (MI)-superfluid (SF) transition at integer filling. Here a quantum simulator of the BHM using a superconducting circuit is proposed. Specifically, a superconducting transmission line resonator supporting microwave photons is coupled to a charge qubit to form one site of the BHM, and adjacent sites are connected by a tunable coupler. To obtain a mapping from the superconducting circuit to the BHM, we focus on the dispersive regime where the excitations remain photonlike. Standard perturbation theory is implemented to locate the parameter range where the MI-SF transition may be simulated. This simulator allows single-site manipulations and we illustrate this feature by considering two scenarios where a single-site manipulation can drive a MI-SF transition. The transition can be analyzed by mean-field analyses, and the exact diagonalization was implemented to provide accurate results. The variance of the photon density and the fidelity metric clearly show signatures of the transition. Lastly, experimental realizations and other possible applications of this simulator are also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Magnetic order-disorder transitions on a one-third-depleted square lattice

Quantum Monte Carlo simulations are used to study the magnetic and transport properties of the Hubbard Model, and its strong coupling Heisenberg limit, on a one-third depleted square lattice. This is the geometry occupied, after charge ordering, by the spin-$\frac{1}{2}$ Ni 1+ atoms in a single layer of the nickelate materials La 4 Ni 3 O 8 and (predicted) La 3 Ni 2 O 6 . Our model is also a description of strained graphene, where a honeycomb lattice has bond strengths which are inequivalent. For the Heisenberg case, we determine the location of the quantum critical point (QCP) where there is an onset of long range antiferromagnetic order (LRAFO), and the magnitude of the order parameter, and then compare with results of spin wave theory. An ordered phase also exists when electrons are itinerant. Finally, in this case, the growth in the antiferromagnetic structure factor coincides with the transition from band insulator to metal in the absence of interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Programmable Phase Selection between Altermagnetic and Noncentrosymmetric Polymorphs of MnTe on InP via Molecular Beam Epitaxy

This dataset contains DFT input and output files supporting the theoretical modeling in the associated publication (ACS Appl. Mater. Interfaces 2026, 18, 15654-15664). The calculations model the interfacial energetics of two MnTe polymorphs — NiAs-MnTe (hexagonal, alpha phase) and ZnS-MnTe (cubic, gamma phase) — on InP(111) substrates with two surface terminations: In-terminated InP(111)A and P-terminated InP(111)B. This gives four interface configurations: NiAs on In-terminated (experimentally observed), NiAs on P-terminated (computed for comparison), ZnS on In-terminated (computed for comparison), and ZnS on P-terminated (experimentally observed). The dataset is organized into four calculation types, each covering all four polymorph/termination combinations: (i) Slabs: Pristine MnTe/InP heterostructure slabs used to compute total energies and interface energy densities (Eint) for all four configurations, as reported in Fig. 6 of the main text. (ii) Disorder: Same slab geometries with a P_Te + Te_P antisite defect pair introduced near the interface, used to assess chemical intermixing effects on interface stability (Fig. S8, SI). (iii) Strain: Pristine slab calculations with in-plane lattice parameters strained by -1% and +1% relative to the InP lattice constant, used to evaluate strain-dependent interface energetics (Fig. S9, SI). (iv) Charge_Density: Single-point calculations on the full heterostructure, the isolated InP slab, and the isolated MnTe slab at fixed geometry, used to compute differential charge density plots showing interfacial charge accumulation and depletion as a function of surface termination (Fig. S10, SI). Each calculation folder contains INCAR, KPOINTS, POSCAR, CONTCAR, OUTCAR, and POTCAR_info.txt (PAW potential information, excluding the full POTCAR due to VASP licensing restrictions). The calculations were performed using VASP 6.4.3 with PBE exchange-correlation, PAW potentials, a Hubbard correction of Ueff = 5 eV on Mn d-states, and A-type AFM spin initialization.

36 MATERIALS SCIENCE↗

Ultrafast evolution and transient phases of a prototype out-of-equilibrium Mott–Hubbard material

Photoexcited strongly correlated materials is attracting growing interest since their rich phase diagram often translates into an equally rich out-of-equilibrium behavior, including non-thermal phases and photoinduced phase transitions. With femtosecond optical pulses, electronic and lattice degrees of freedom can be transiently decoupled, giving the opportunity of stabilizing new states of matter inaccessible by quasi-adiabatic pathways. We present a study of the ultrafast non-equilibrium evolution of the prototype Mott-Hubbard material V 2 O 3 , which presents a transient non-thermal phase developing immediately after photoexcitation and lasting few picoseconds. For both the insulating and the metallic phase, the formation of the transient configuration is triggered by the excitation of electrons into the bonding a 1 g orbital, and is then stabilized by a lattice distortion characterized by a marked hardening of the A 1g coherent phonon. Furthermore, this configuration is in stark contrast with the thermally accessible ones - the A 1g phonon frequency actually softens when heating the material. Our results show the importance of selective electron-lattice interplay for the ultrafast control of material parameters, and are of particular relevance for the optical manipulation of strongly correlated systems, whose electronic and structural properties are often strongly intertwinned.

36 MATERIALS SCIENCE↗

Magnetic and f-electron effects in LaNiO2 and NdNiO2 nickelates with cuprate-like $$3{d}_{{x}^{2}-{y}^{2}}$$ band

Recent discovery of superconductivity in the doped infinite-layer nickelates has renewed interest in understanding the nature of high-temperature superconductivity more generally. The low-energy electronic structure of the parent compound NdNiO 2 , the role of electronic correlations in driving superconductivity, and the possible relationship between the cuprates and the nickelates are still open questions. Here, by comparing LaNiO 2 and NdNiO 2 systematically within a parameter-free, all-electron first-principles density-functional theory framework, we reveal the role of Nd 4 f electrons in shaping the ground state of pristine NdNiO 2 . Strong similarities are found between the electronic structures of LaNiO 2 and NdNiO 2 , except for the effects of the 4 f electrons. Hybridization between the Nd 4 f and Ni 3 d orbitals is shown to significantly modify the Fermi surfaces of various magnetic states. In contrast, the competition between the magnetically ordered phases depends mainly on the gaps in the Ni \(3{d}_{{x}^{2}-{y}^{2}}\) band. Our estimated value of the on-site Hubbard U in the nickelates is similar to that in the cuprates, but the value of the Hund’s coupling J H is found to be sensitive to the Nd magnetic moment. In contrast with the cuprates, NdNiO 2 presents 3D magnetism with competing antiferromagnetic and (interlayer) ferromagnetic exchange, which may explain why the T c is lower in the nickelates.

36 MATERIALS SCIENCE↗

Effects of strong interactions in a half-metallic magnet: A determinant quantum Monte Carlo study

Understanding the effects of electron-electron interactions in half-metallic magnets (HMs), which have band structures with one gapped spin channel and one metallic channel, poses fundamental theoretical issues as well as having importance for their potential applications. Here we use determinant quantum Monte Carlo to study the impacts of an on-site Hubbard interaction U, finite temperature, and an external (Zeeman) magnetic field on a bilayer tight-binding model which is a half-metal in the absence of interactions, by calculating the spectral density, conductivity, spin polarization of carriers, and local magnetic properties. We quantify the effect of U on the degree of thermal depolarization, and follow relative band shifts and monitor when significant gap states appear, each of which can degrade the HM character. For this model, Zeeman coupling induces, at fixed particle number, two successive transitions: compensated half-metal with spin-down band gap → metallic ferromagnet → saturated ferromagnetic insulator. However, over much of the more relevant parameter regime, the half-metallic properties are rather robust to U.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

On parameterization of the inverse problem for estimating aquifer properties using tracer data

We consider a field-scale tracer experiment conducted in 2007 in a shallow uranium-contaminated aquifer at Rifle, Colorado. In developing a reliable approach for inferring hydrological properties at the site through inverse modeling of the tracer data, decisions made on how to parameterize heterogeneity (i.e., how to represent a heterogeneous distribution using a limited number of parameters that are amenable to estimation) are of paramount importance. We present an approach for hydrological inversion of the tracer data and explore, using a 2D synthetic example at first, how parameterization affects the solution, and how additional characterization data could be incorporated to reduce uncertainty. Specifically, we examine sensitivity of the results to the configuration of pilot points used in a geostatistical parameterization, and to the sampling frequency and measurement error of the concentration data. A reliable solution of the inverse problem is found when the pilot point configuration is carefully implemented. In addition, we examine the use of a zonation parameterization, in which the geometry of the geological facies is known (e.g., from geophysical data or core data), to reduce the non-uniqueness of the solution and the number of unknown parameters to be estimated. When zonation information is only available for a limited region, special treatment in the remainder of the model is necessary, such as using a geostatistical parameterization. Finally, inversion of the actual field data is performed using 2D and 3D models, and results are compared with slug test data.

54 ENVIRONMENTAL SCIENCES↗

Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics

Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data. We use machine learning to quantify the relationships between bedrock geophysical/hydrological properties and geomorphological/vegetation indices and show that machine learning relationships can estimate most of their covariability. Although we can predict the electrical resistivity variation across the watershed, regions of lower variability in the input parameters are shown to provide better estimates, indicating a limitation of commonly applied geomorphological models. Our results emphasize that such an integrated approach can be used to derive detailed bedrock characteristics, allowing for identification of small-scale variations across an entire watershed that may be critical to assess the impact of disturbances on hydrological systems.

58 GEOSCIENCES↗

A Predictive Model for Lake Chad Total Surface Water Area Using Remotely Sensed and Modeled Hydrological and Meteorological Parameters and Multivariate Regression Analysis

Lake Chad is an endorheic lake in the Sahel region of Africa at the southern edge of the Sahara Desert. The lake, which is well known for its dramatic decrease in surface area during the 1970s and 1980s, experiences an annual flood resulting in a maximum total surface water area generally during February or March, though sometimes earlier or later. People along the shores of Lake Chad make their living fishing, farming, and raising livestock and have a vested interest in knowing when and how extensive the annual flooding will be, particularly those practicing recession farming in which the fertile ground of previously flooded area is used for planting crops. In this study, the authors investigate the relationship between lake and basin parameters, including rainfall, basin evapotranspiration, lake evapotranspiration, lake elevation, total surface water area, and the previous year’s total surface water area, and develop equations for each dry season month (except November) linking total surface water area to the other parameters. The resulting equations allow the user to estimate the December average monthly total surface water area of the lake in late November, and to make the estimates for January to May in early December. Based on the results of a Leave One Out Cross Validation analysis, the equations for lake area are estimated to have an average absolute error ranging from 5.3 percent (for February estimates) to 7.6 percent (for May estimates).

Lake Chad↗

First-principles study of intrinsic point defects and Xe impurities in uranium monocarbide

Based on density functional theory (DFT) calculations, we perform an extensive investigation of intrinsic point defects and Xe impurities in uranium monocarbide (UC). The DFT calculations involve both the conventional generalized gradient approximation (GGA) and the GGA+U approach with the Hubbard parametric term (U), using up to 5×5×5 supercells. GGA calculations for the formation energy of intrinsic defects demonstrate the significant effect of using larger supercells than in previous studies. Results confirm that the ⟨111⟩ and ⟨100⟩ dumbbell interstitials are the most stable interstitial configurations for U and C, respectively. The interstitial mechanisms are favored for self-diffusion of both uranium and carbon and diffusion of Xe under equilibrium conditions. Calculations also reveal that the Xe substitutional defect at the C lattice site tends to adopt an off-site configuration, which can be interpreted as a Xe interstitial–C vacancy complex. We also utilize GGA+U to assess the impact of effective U parameter (Ueff) on the results. Moreover, we introduce a method to estimate the carbon chemical potential by fitting the phase diagram composition data and propose a selection Ueff=1.25 eV based on the experimental Xe diffusion activation energy. With this approach, GGA+U calculations reproduce the available experimental data for the formation energy of the carbon Frenkel pair and can explain the stepwise recovery of intrinsic properties and burst Xe release behavior in UC observed in annealing experiments.

Huang, Gui-Yang (ORCID:0000000301447376)↗

Designer quantum materials

Quantum materials have long promised to revolutionize everything from energy transmission (high temperature superconductors) to both quantum and classical information systems (topological materials). However, their discovery and application has proceeded in an Edisonian fashion due to both an incomplete theoretical understanding and the difficulty of growing and purifying new materials. This project leverages Sandia's unique atomic precision advanced manufacturing (APAM) capability to design small-scale tunable arrays (designer materials) made of donors in silicon. Their low-energy electronic behavior can mimic quantum materials, and can be tuned by changing the fabrication parameters for the array, thereby enabling the discovery of materials systems which can't yet be synthesized. In this report, we detail three key advances we have made towards development of designer quantum materials. First are advances both in APAM technique and underlying mechanisms required to realize high-yielding donor arrays. Second is the first-ever observation of distinct phases in this material system, manifest in disordered 2D sheets of donors. Finally are advances in modeling the electronic structure of donor clusters and regular structures incorporating them, critical to understanding whether an array is expected to show interesting physics. Combined, these establish the baseline knowledge required to manifest the strongly-correlated phases of the Mott-Hubbard model in donor arrays, the first step to deploying APAM donor arrays as analogues of quantum materials.

36 MATERIALS SCIENCE↗

Dependence of the critical temperature of high-temperature cuprate superconductors on hoppings and spin correlations between CuO{sub 2} planes

The influence of interlayer hoppings on the superconducting transition temperature (T{sub c}) in bilayer cuprates has been studied. The parameter of hopping between layers is expressed as t{sub Up-Tack }(k) = t{sub Up-Tack }(cos(k{sub x}) - cos(k{sub y})){sup 2} and treated as a small perturbation for the states of two CuO{sub 2} planes described by the t-t Prime -t Double-Prime -J* model. In the generalized mean field approximation for d{sub x}{sup 2} - y{sup 2} symmetry of the superconducting gap, neither the interlayer hopping or exchange interaction, nor the pair hopping between CuO{sub 2} layers provides an additional mechanism of Cooper pair formation or an increase in T{sub c}. In the concentration dependence of T{sub c}, the bilayer splitting of the upper Hubbard band of quasi-holes is manifested as two peaks with temperatures slightly lower than the maximum T{sub c} for a single-layer cuprate. Interlayer antiferromagnetic spin correlations suppress bilayer splitting.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Hybrid predictive modeling approach simulated evapotranspiration and ecosystem respiration data

This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study include: CA-OAS, CA-OBS, US-NR1, US-TON, US-VAR, US-SRM, US-WHS, US-WKG. Snotel sites Butte (ER-BT), Porphyry Creek (ER-PK) and Schofield Pass (ER-SP) are included as well 16 east river locations with different vegetation types denoted by evergreen forests (EF), deciduous forests (DF), riparian shrublands (RS) and meadow grassland (MS). This data package includes: 1) A summary spread sheet of the sites and acronyms for data variables. 2) Processed Fluxnet datasets that are obtained from Fluxnet.fluxdata.org with HPM estimated evapotranspiration (ET) and ecosystem respiration (RECO). Trained models and metrics for parameters for the Fluxnet sites were added in an update on November 2, 2020; 3) Processed SNOTEL datasets obtained from www.nrcs.usda.gov/snow/ and HPM estimated ET and RECO; 4) Weather data at east river locations obtained from DAYMET (daymet.ornl.gov) as well as HPM estimated ET and RECO. NDVI datasets are obtained from Landsat 5, 7 and 8 on Google Earth Engine platform. Detailed QA/QC and sampling methods of measured data are available at the original data source.

54 ENVIRONMENTAL SCIENCES↗

SU(N) magnetism in chains of ultracold alkaline-earth-metal atoms: Mott transitions and quantum correlations

We investigate one-dimensional SU(N) Hubbard chains at zero temperature, which can be emulated with ultracold alkaline-earth-metal atoms, by using the density matrix renormalization group (DMRG), Bethe ansatz (BA), and bosonization. We compute experimental observables and use the DMRG to benchmark the accuracy of the Bethe ansatz for N>2 where the BA is only approximate. In the worst case, we find a relative error {epsilon} < or approx. 4% in the BA ground-state energy for N{<=}4 at filling 1/N, which is due to the fact that BA improperly treats the triply and higher occupied states. Using the DMRG for N{<=}4 and the BA for large N, we determine the regimes of validity of strong- and weak-coupling perturbation theory for all values of N and, in particular, the parameter range in which the system is well described by a SU(N) Heisenberg model at filling 1/N. We find this depends only weakly on N. We investigate the Berezinskii-Kosterlitz-Thouless phase transition from a Luttinger liquid to a Mott insulator by computing the fidelity susceptibility and the Luttinger parameter K{sub {rho}} at 1/N filling. The numerical findings give strong evidence that the fidelity susceptibility develops a minimum at a critical interaction strength which is found to occur at a finite positive value for N>2.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Gauge-invariant implementation of the Abelian-Higgs model on optical lattices

We present a gauge-invariant effective action for the Abelian Higgs model (scalar electrodynamics) with a chemical potential $\mu$ on a 1+1 dimensional lattice. This formulation provides an expansion in the hopping parameter $\kappa$ which we test with Monte Carlo simulations for a broad range of the inverse gauge coupling $\beta_{pl}=1/g^2$ and small values of the scalar self-coupling $\lambda$. In the opposite limit of infinitely large $\lambda$, the partition function can be written as a traced product of local tensors which allows us to write exact blocking formulas. Gauss's law is automatically satisfied and the introduction of $\mu$ has consequences only if we have an external electric field, $g^2=0$ or an explicit gauge symmetry breaking. The time continuum limit of the blocked transfer matrix can be obtained numerically and, for $g^2=0$ and a spin-1 truncation, the small volume energy spectrum is identical to the low energy spectrum of a two-species Bose-Hubbard model in the limit of large on-site repulsion. We extend this procedure for finite $\beta_{pl}$ and derive a spin-1 approximation of the Hamiltonian. It involves new terms corresponding to transitions among the two species in the Bose-Hubbard model. Finally, we propose an optical lattice implementations involving a ladder structure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A hybrid data–model approach to map soil thickness in mountain hillslopes

Abstract. Soil thickness plays a central role in the interactions between vegetation, soils, and topography, where it controls the retention and release of water, carbon, nitrogen, and metals. However, mapping soil thickness, here defined as the mobile regolith layer, at high spatial resolution remains challenging. Here, we develop a hybrid model that combines a process-based model and empirical relationships to estimate the spatial heterogeneity of soil thickness with fine spatial resolution (0.5 m). We apply this model to two aspects of hillslopes (southwest- and northeast-facing, respectively) in the East River watershed in Colorado. Two independent measurement methods – auger and cone penetrometer – are used to sample soil thickness at 78 locations to calibrate the local value of unconstrained parameters within the hybrid model. Sensitivity analysis using the hybrid model reveals that the diffusion coefficient used in hillslope diffusion modeling has the largest sensitivity among all input parameters. In addition, our results from both sampling and modeling show that, in general, the northeast-facing hillslope has a deeper soil layer than the southwest-facing hillslope. By comparing the soil thickness estimated between a machine-learning approach and this hybrid model, the hybrid model provides higher accuracy and requires less sampling data. Modeling results further reveal that the southwest-facing hillslope has a slightly faster surface soil erosion rate and soil production rate than the northeast-facing hillslope, which suggests that the relatively less dense vegetation cover and drier surface soils on the southwest-facing slopes influence soil properties. With seven parameters in total for calibration, this hybrid model can provide a realistic soil thickness map with a relatively small amount of sampling dataset comparing to machine-learning approach. Integrating process-based modeling and statistical analysis not only provides a thorough understanding of the fundamental mechanisms for soil thickness prediction but also integrates the strengths of both statistical approaches and process-based modeling approaches.

58 GEOSCIENCES↗

Structure-property relationships and recyclability of natural fiber insulation

Thermal insulation can significantly decrease the energy required to maintain internal temperatures within buildings, saving money and decreasing environmental impacts. Many industrially available insulation options utilize petroleum-derived materials, such as polyurethane, fiberglass, and polystyrene, which can be detrimental to the environment by emitting greenhouse gases during production. A sustainable alternative to these synthetic insulations is the use of renewable feedstocks to produce comparable insulation products. In this work, natural fibers such as flax and banana were bound with an epoxy system to produce natural-fiber insulation. Key experimental parameters for this study included evaluating the fiber lengths and processing methods while varying the viscosity of the epoxy binder solvent dissolution. Insulation performance was determined by comparing density, thermal conductivity, resilience, and compressive strength; these parameters were tested to further understand and investigate the structure- property relationships within the system and to understand how these composites compare to current commercial materials. Furthermore, from this characterization and optimization, a natural fiber sample with an R/in. >5 was achieved, making these materials competitive with commercial alternatives.

Compressive strength↗