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NASA NTRS1991

A tidal wind model for 85-120 km based on CIRA-86 - A feasibility study

The feasibility of deriving a climatology of the diurnal variations of the wind in the 85-120 km region from the tidal components of density, temperature and composition contained in the new COSPAR CIRA-86 is examined. The CIRA density and temperature model is employed to derive the eastward and northward pressure gradient forces that serve as the forcing functions in the coupled momentum equations. At midlatitudes, the model shows some of the general features observed in the radar tidal data, e.g., the dominant semidiurnal tide with increasing amplitude with height and clockwise (counterclockwise) rotation of the velocity vector seen in the Northern (Southern) Hemisphere.

Fleming, E. L.↗

DOE OSTI2021

Nuclear energy density functionals grounded in ab initio calculations

Here, we discuss the construction of a nuclear energy density functional (EDF) from ab initio computations and advocate the need for a methodical approach that is free from ad hoc assumptions. The equations of state (EoSs) of symmetric nuclear and pure neutron matter are computed using the chiral NNLO sat and the phenomenological AV4' + UIX c Hamiltonians as inputs to self-consistent Green's function (SCGF) and auxiliary field diffusion Monte Carlo (AFDMC) methods. We propose a convenient parametrization of the EoS as a function of the Fermi momentum and fit it on the SCGF and AFDMC calculations. We apply the ab initio based EDF to carry out an analysis of the binding energies and charge radii of different nuclei in the local density approximation. The NNLO sat -based EDF produces encouraging results, whereas the AV4' + UIX c -based one is farther from experiment. Possible explanations of these different behaviors are suggested, and the importance of gradient and spin-orbit terms is analyzed. Our paper paves the way for a practical and systematic way to merge ab initio nuclear theory and density functional theory, while shedding light on some critical aspects of this procedure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

An improved guess for the variational calculation of charge-transfer excitations in large systems

Ab initio quantum-chemical methods that perform well for computing the electronic ground state are not straightforwardly transferable to electronically excited states, particularly in large molecular systems. Wave function theory offers high accuracy, but is often prohibitively expensive. Methods based on time-dependent density functional theory (TD-DFT) are crucially sensitive to the chosen exchange-correlation functional (XCF) parameterization, and system-specific tuning protocols were therefore proposed to address the method's robustness. Methods based on the variational relaxation of the excited-state electron density showcased promising results for the calculation of charge-transfer excitations, but the complex shape of the electronic hypersurface makes convergence to a specific excited state much more difficult than for the ground state when standard variational techniques are applied. We address the latter aspect by providing suitable initial guesses, which we obtain by two separate constrained algorithms. Combined with the squared-gradient minimization algorithm for all-electrons relaxation in a freeze-and-release scheme (FRZ-SGM), we demonstrate that orbital-optimized density functional theory (OO-DFT) calculations can reliably converge to the charge-transfer states of interest even for large molecular systems. We test the FRZ-SGM method on a phenothiazine-anthraquinone CT excitation in a supramolecular Pd(II) coordination cage complex as a function of the cage conformation. This compound has been studied experimentally prior to our work. We compare this freeze-and-release scheme to two XCF reparameterizations, which were recently proposed as low-cost TD-DFT-based alternatives to variational methods. Two dye-semiconductor complexes, which were previously investigated in the context of photovoltaic applications, serve as a second example to investigate the convergence and stability of the FRZ-SGM approach. Our results demonstrate that FRZ-SGM provides reliable convergence for charge-transfer excited states and avoids variational collapse to lower-lying electronic states, whereas time-dependent DFT calculations with an adequate tuning procedure for the range-separation parameter provide a computationally efficient initial estimate of the corresponding energies, with a computational cost comparable to that of configuration-interaction singles (CIS) calculations.

Bogo, Nicola↗

DOE OSTI2021

Leaf turgor loss point shapes local and regional distributions of evergreen but not deciduous tropical trees

Summary The effects of climate change on tropical forests will depend on how diverse tropical tree species respond to drought. Current distributions of evergreen and deciduous tree species across local and regional moisture gradients reflect their ability to tolerate drought stress, and might be explained by functional traits. We measured leaf water potential at turgor loss (i.e. ‘wilting point’; π tlp ), wood density (WD) and leaf mass per area (LMA) on 50 of the most abundant tree species in central Panama. We then tested their ability to explain distributions of evergreen and deciduous species within a 50 ha plot on Barro Colorado Island and across a 70 km rainfall gradient spanning the Isthmus of Panama. Among evergreen trees, species with lower π tlp were associated with drier habitats, with π tlp explaining 28% and 32% of habitat association on local and regional scales, respectively, greatly exceeding the predictive power of WD and LMA. In contrast, π tlp did not predict habitat associations among deciduous species. Across spatial scales, π tlp is a useful indicator of habitat preference for tropical tree species that retain their leaves during periods of water stress, and holds the potential to predict vegetation responses to climate change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Modeling Liquid Water by Climbing up Jacob’s Ladder in Density Functional Theory Facilitated by Using Deep Neural Network Potentials

Within the framework of Kohn–Sham density functional theory (DFT), the ability to provide good predictions of water properties by employing a strongly constrained and appropriately normed (SCAN) functional has been extensively demonstrated in recent years. Here, we further advance the modeling of water by building a more accurate model on the fourth rung of Jacob’s ladder with the hybrid functional, SCAN0. In particular, we carry out both classical and Feynman path-integral molecular dynamics calculations of water with the SCAN0 functional and the isobaric–isothermal ensemble. To generate the equilibrated structure of water, a deep neural network potential is trained from the atomic potential energy surface based on ab initio data obtained from SCAN0 DFT calculations. For the electronic properties of water, a separate deep neural network potential is trained by using the Deep Wannier method based on the maximally localized Wannier functions of the equilibrated trajectory at the SCAN0 level. The structural, dynamic, and electric properties of water were analyzed. The hydrogen-bond structures, density, infrared spectra, diffusion coefficients, and dielectric constants of water, in the electronic ground state, are computed by using a large simulation box and long simulation time. For the properties involving electronic excitations, we apply the GW approximation within many-body perturbation theory to calculate the quasiparticle density of states and bandgap of water. Compared to the SCAN functional, mixing exact exchange mitigates the self-interaction error in the meta-generalized-gradient approximation and further softens liquid water toward the experimental direction. For most of the water properties, the SCAN0 functional shows a systematic improvement over the SCAN functional. However, some important discrepancies remain. The H-bond network predicted by the SCAN0 functional is still slightly overstructured compared to the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Analytical derivatives of the individual state energies in ensemble density functional theory. II. Implementation on graphical processing units (GPUs)

Conical intersections control excited state reactivity, and thus, elucidating and predicting their geometric and energetic characteristics are crucial for understanding photochemistry. Locating these intersections requires accurate and efficient electronic structure methods. Unfortunately, the most accurate methods (e.g., multireference perturbation theories such as XMS-CASPT2) are computationally challenging for large molecules. The state-interaction state-averaged restricted ensemble referenced Kohn–Sham (SI-SA-REKS) method is a computationally efficient alternative. The application of SI-SA-REKS to photochemistry was previously hampered by a lack of analytical nuclear gradients and nonadiabatic coupling matrix elements. We have recently derived analytical energy derivatives for the SI-SA-REKS method and implemented the method effectively on graphical processing units. We demonstrate that our implementation gives the correct conical intersection topography and energetics for several examples. Furthermore, our implementation of SI-SA-REKS is computationally efficient, with observed sub-quadratic scaling as a function of molecular size. This demonstrates the promise of SI-SA-REKS for excited state dynamics of large molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2009

Computer Code for Nanostructure Simulation

Due to their small size, nanostructures can have stress and thermal gradients that are larger than any macroscopic analogue. These gradients can lead to specific regions that are susceptible to failure via processes such as plastic deformation by dislocation emission, chemical debonding, and interfacial alloying. A program has been developed that rigorously simulates and predicts optoelectronic properties of nanostructures of virtually any geometrical complexity and material composition. It can be used in simulations of energy level structure, wave functions, density of states of spatially configured phonon-coupled electrons, excitons in quantum dots, quantum rings, quantum ring complexes, and more. The code can be used to calculate stress distributions and thermal transport properties for a variety of nanostructures and interfaces, transport and scattering at nanoscale interfaces and surfaces under various stress states, and alloy compositional gradients. The code allows users to perform modeling of charge transport processes through quantum-dot (QD) arrays as functions of inter-dot distance, array order versus disorder, QD orientation, shape, size, and chemical composition for applications in photovoltaics and physical properties of QD-based biochemical sensors. The code can be used to study the hot exciton formation/relation dynamics in arrays of QDs of different shapes and sizes at different temperatures. It also can be used to understand the relation among the deposition parameters and inherent stresses, strain deformation, heat flow, and failure of nanostructures.

Filikhin, Igor↗

DOE OSTI2024

Proximal Galerkin: A Structure-Preserving Finite Element Method for Pointwise Bound Constraints

The proximal Galerkin finite element method is a high-order, low iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of pointwise bound constraints in infinite-dimensional function spaces. This paper introduces the proximal Galerkin method and applies it to solve free boundary problems, enforce discrete maximum principles, and develop a scalable, mesh-independent algorithm for optimal design with pointwise bound constraints. This paper also introduces the latent variable proximal point (LVPP) algorithm, from which the proximal Galerkin method derives. When analyzing the classical obstacle problem, we discover that the underlying variational inequality can be replaced by a sequence of second-order partial differential equations (PDEs) that are readily discretized and solved with, e.g., the proximal Galerkin method. Throughout this work, we arrive at several contributions that may be of independent interest. These include (1) a semilinear PDE we refer to as the entropic Poisson equation; (2) an algebraic/geometric connection between high-order positivity-preserving discretizations and certain infinite-dimensional Lie groups; and (3) a gradient-based, bound-preserving algorithm for two-field, density-based topology optimization. The complete proximal Galerkin methodology combines ideas from nonlinear programming, functional analysis, tropical algebra, and differential geometry and can potentially lead to new synergies among these areas as well as within variational and numerical analysis. Open-source implementations of our methods accompany this work to facilitate reproduction and broader adoption.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Experimental and computational study of phase space dynamics in strongly coupled plasmas with steep density gradients

Understanding how plasmas thermalize when density gradients are steep remains a fundamental challenge in plasma physics, with direct implications for fusion experiments and astrophysical phenomena. Standard hydrodynamic models break down in these regimes, and kinetic theories make predictions that have never been directly tested. Here, we present the first detailed phase-space measurements of a strongly coupled plasma as it evolves from sharp density gradients to thermal equilibrium. Using laser-induced fluorescence imaging of an ultracold calcium plasma, we track the complete ion distribution function f(x,v,t). We discover that commonly used kinetic models (Bhatnagar–Gross–Krook and Lenard–Bernstein) overpredict thermalization rates, even while correctly capturing the initial counterstreaming plasma formation. Our measurements reveal that the initial ion acceleration response scales linearly with electron temperature, and that the simulations underpredict the initial ion response. In our geometry we demonstrate the formation of well-controlled counterpropagating plasma beams. This experimental platform enables precision tests of kinetic theories and opens new possibilities for studying plasma stopping power and flow-induced instabilities in strongly coupled systems.

Bergeson, Scott (ORCID:0000000231249226)↗

NASA NTRS1985

The cleft ion fountain - A two-dimensional kinetic model

The transport of ionospheric ions from a source in the polar cleft ionosphere through the polar magnetosphere is investigated using a two-dimensional, kinetic, trajectory-based code. The transport model includes the effects of gravitation, longitudinal magnetic gradient force, convection electric fields, and parallel electric fields. Individual ion trajectories as well as distribution functions and resulting bulk parameters of density, parallel average energy, and parallel flux for a presumed cleft ionosphere source distribution are presented for various conditions to illustrate parametrically the dependences on source energies, convection electric field strengths, ion masses, and parallel electric field strengths. The essential features of the model are consistent with the concept of a cleft-based ion fountain supplying ionospheric ions to the polar magnetosphere, and the resulting plasma distributions and parameters are in general agreement with recent low-energy ion measurements from the DE 1 satellite.

Horwitz, J. L.↗

NASA NTRS1996

Evaluation of a vortex-based subgrid stress model using DNS databases

The performance of a SubGrid Stress (SGS) model for Large-Eddy Simulation (LES) developed by Misra k Pullin (1996) is studied for forced and decaying isotropic turbulence on a 32(exp 3) grid. The physical viability of the model assumptions are tested using DNS databases. The results from LES of forced turbulence at Taylor Reynolds number R(sub (lambda)) approximately equals 90 are compared with filtered DNS fields. Probability density functions (pdfs) of the subgrid energy transfer, total dissipation, and the stretch of the subgrid vorticity by the resolved velocity-gradient tensor show reasonable agreement with the DNS data. The model is also tested in LES of decaying isotropic turbulence where it correctly predicts the decay rate and energy spectra measured by Comte-Bellot & Corrsin (1971).

Misra, Ashish↗

NASA NTRS2002

Probing the Masses of the PSR JO621+1002 Binary System Through Relativistic Apsidal Motion

Orbital, spin and astrometric parameters of the millisecond pulsar PSR J0621+1002 have been determined through six years of timing observations at three radio telescopes. The chief result is a measurement of the rate of periastron advance, omega=0 deg.0116 +/-0 deg.0008/yr. Interpreted as a general relativistic effect, this implies the sum of the pulsar mass, m(1), and the companion mass, m(2), to be M=m(1)+m(2)= 2.81 +/-0.30 solar mass. The Keplerian parameters rule out certain combinations of m(1) and m(2), as does the non-detection of Shapiro delay in the pulse arrival times. These constraints, together with the assumption that the companion is a white dwarf, lead to the maximum likelihood values m(1)=1.69((sup +0.30)(sub -0.30)) solar mass and m(2)=0.98((sup +0.32)(sub -0.12) solar mass (68% confidence). The other major finding is that the pulsar experiences dramatic variability in its dispersion measure (DM), with gradients as steep as 0.013 pc/cu cm/yr. A structure function analysis of the DM variations uncovers spatial fluctuations in the interstellar electron density that cannot be fit to a single power law, unlike the Kolmogorov turbulent spectrum that has been seen in the direction of other pulsars. Other results from the timing analysis include the first measurements of the pulsar's proper motion, mu=3.5+/-0.3 mas/yr, and of its spin-down rate, dP/dt=4.7 x 10(exp -20), which, when corrected for kinematic biases and combined with the pulse period, P=28.8 ms, gives a characteristic age of 1.1 x 10(exp 10) yr and a surface magnetic field strength of 1.2 x 10 (exp 9) G.

Spaver, Eric M.↗

NASA NTRS1995

An extension of the Lighthill theory of jet noise to encompass refraction and shielding

A formalism for jet noise prediction is derived that includes the refractive 'cone of silence' and other effects; outside the cone it approximates the simple Lighthill format. A key step is deferral of the simplifying assumption of uniform density in the dominant 'source' term. The result is conversion to a convected wave equation retaining the basic Lighthill source term. The main effect is to amend the Lighthill solution to allow for refraction by mean flow gradients, achieved via a frequency-dependent directional factor. A general formula for power spectral density emitted from unit volume is developed as the Lighthill-based value multiplied by a squared 'normalized' Green's function (the directional factor), referred to a stationary point source. The convective motion of the sources, with its powerful amplifying effect, also directional, is already accounted for in the Lighthill format: wave convection and source convection are decoupled. The normalized Green's function appears to be near unity outside the refraction dominated 'cone of silence', this validates our long term practice of using Lighthill-based approaches outside the cone, with extension inside via the Green's function. The function is obtained either experimentally (injected 'point' source) or numerically (computational aeroacoustics). Approximation by unity seems adequate except near the cone and except when there are shrouding jets: in that case the difference from unity quantifies the shielding effect. Further extension yields dipole and monopole source terms (cf. Morfey, Mani, and others) when the mean flow possesses density gradients (e.g., hot jets).

Ribner, Herbert S.↗

DOE OSTI2020

Self-interaction error overbinds water clusters but cancels in structural energy differences

Here, we gauge the importance of self-interaction errors in density functional approximations (DFAs) for the case of water clusters. To this end, we used the Fermi–Löwdin orbital self-interaction correction method (FLOSIC) to calculate the binding energy of clusters of up to eight water molecules. Three representative DFAs of the local, generalized gradient, and metageneralized gradient families [i.e., local density approximation (LDA), Perdew–Burke–Ernzerhof (PBE), and strongly constrained and appropriately normed (SCAN)] were used. We find that the overbinding of the water clusters in these approximations is not a density-driven error. We show that, while removing self-interaction error does not alter the energetic ordering of the different water isomers with respect to the uncorrected DFAs, the resulting binding energies are corrected toward accurate reference values from higher-level calculations. In particular, self-interaction–corrected SCAN not only retains the correct energetic ordering for water hexamers but also reduces the mean error in the hexamer binding energies to less than 14 meV/ H 2 O from about 42 meV/ H 2 O for SCAN. By decomposing the total binding energy into many-body components, we find that large errors in the two-body interaction in SCAN are significantly reduced by self-interaction corrections. Higher-order many-body errors are small in both SCAN and self-interaction–corrected SCAN. These findings suggest that orbital-by-orbital removal of self-interaction combined with a proper DFA can lead to improved descriptions of water complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Improving gas adsorption modeling for MOFs by local calibration of Hubbard U parameters

While computational screening with density functional theory (DFT) is frequently employed for the screening of metal–organic frameworks (MOFs) for gas separation and storage, commonly applied generalized gradient approximations (GGAs) exhibit self-interaction errors, which hinder the predictions of adsorption energies. We investigate the Hubbard U parameter to augment DFT calculations for full periodic MOFs, targeting a more precise modeling of gas molecule–MOF interactions, specifically for N2, CO2, and O2. We introduce a calibration scheme for the U parameter, which is tailored for each MOF, by leveraging higher-level calculations on the secondary building unit (SBU) of the MOF. When applied to the full periodic MOF, the U parameter calibrated against hybrid HSE06 calculations of SBUs successfully reproduces hybrid-quality calculations of the adsorption energy of the periodic MOF. The mean absolute deviation of adsorption energies reduces from 0.13 eV for a standard GGA treatment to 0.06 eV with the calibrated U, demonstrating the utility of the calibration procedure when applied to the full MOF structure. Furthermore, attempting to use coupled cluster singles and doubles with perturbative triples calculations of isolated SBUs for this calibration procedure shows varying degrees of success in predicting the experimental heat of adsorption. It improves accuracy for N2 adsorption for cases of overbinding, whereas its impact on CO2 is minimal, and ambiguities in spin state assignment hinder consistent improvements of O2 adsorption. Our findings emphasize the limitations of cluster models and advocate the use of full periodic MOF systems with a calibrated U parameter, providing a more comprehensive understanding of gas adsorption in MOFs.

Chemistry↗

NASA NTRS1962

Ionospheric Studies with the Differential Doppler Technique

This report is essentially a review of the measurements related to the ionosphere utilizing the differential Doppler technique. A brief study of the theory is presented, in which the error incurred in measurements of ionospheric electron content, caused by the assumption of common-path propagation, is shown as a function of the zenith angle of observation for different values of the critical frequency foF2. Some measurements of electron densities, electron content, horizontal gradients, irregularities, and magnetic-storm effects are discussed. Comments are also made about the method of combining the differential Doppler with the Faraday rotation measurements to establish a necessary constant of integration in the measurements made with satellites. It is concluded that the differential Doppler technique, with harmonically related frequencies transmitted to or from rockets or satellites, can provide accurate information about the electron density or electron content of the medium, and that the knowledge of these quantities is valuable in understanding the morphology of the ionospheric processes.

IONOSPHERE↗

NASA NTRS2010

Vertical Diffusivities of Active and Passive Tracers

The climate models that include a carbon-cycle need the vertical diffusivity of a passive tracer. Since an expression for the latter is not available, it has been common practice to identify it with that of salt. The identification is questionable since T, S are active, not passive tracers. We present the first derivation of the diffusivity of a passive tracer in terms of Ri (Richardson number) and Rq (density ratio, ratio of salinity over temperature z-gradients). The following results have emerged: (a) The passive tracer diffusivity is an algebraic function of Ri, Rq. (b) In doubly stable regimes (DS, partial derivative of T with respect to z > 0, partial derivative of S with respect to z < 0), the passive scalar diffusivity is nearly the same as that of salt/heat for any values of Rq < 0 and Ri > 0. (c) In DC regimes (diffusive convection, partial derivative of T with respect to z < 0, partial derivative of S with respect to z < 0, Rq > 1), the passive scalar diffusivity is larger than that of salt. At Ri = O(1), it can be more than twice as large. (d) In SF regimes (salt fingers, partial derivative of T with respect to z > 0, partial derivative of S with respect to z > 0, Rq < 1), the passive scalar diffusivity is smaller than that of salt. At Ri = O(1), it can be less than half of it. (e) The passive tracer diffusivity predicted at the location of NATRE (North Atlantic Tracer Release Experiment) is discussed. (f) Perhaps the most relevant conclusion is that the common identification of the tracer diffusivity with that of salt is valid only in DS regimes. In the Southern Ocean, where there is the largest CO2 absorption, the dominant regime is diffusive convection discussed in (c) above.

Canuto, V. M.↗

NASA NTRSDate not supplied

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗