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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape: Modeling Archive

This modeling archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025). This archive contains model input files and outputs from landscape-scale simulations conducted using ELM, the land model component of the Department of Energy’s Energy Exascale Earth System Model (E3SM), at the Council NGEE Arctic field site (Council Road mile marker 71) on Alaska’s Seward Peninsula. Input data and model output from two sets of ELM simulations are provided. The first set of simulations were conducted with the two default ELM Arctic plant functional types (PFTs; broadleaf deciduous boreal shrub and a C3 grass) and the second set of simulations were conducted with a set of nine Arctic-specific PFTs including nonvascular mosses and lichens, graminoids, forbs, evergreen dwarf shrubs, three height classes of deciduous shrubs (dwarf, low, and low to tall), and deciduous alder shrubs (Sulman et al., 2021). Parameter names and major parameter changes in the Arctic-specific PFT configuration are described in Sulman et al. (2021) and archived in the Sulman et al. (2021) dataset (see below). Simulations were spatially explicit, covering an approximately 6.4X3.3 km domain at the Council site with a spatial resolution of 100 m for a total of 2,112 simulated grid cells under each ELM PFT configuration. The modeling archive contains meteorological forcing (seven *.nc files and one *.txt file), a domain definition file (one *.nc files), land surface configuration files (two *.nc files), parameter files (two *.nc files), annual ELM output files spanning 1980-2014 (68 *.nc files), and a User’s Guide (*pdf file). Additional information on the provided files is in the “Modeling Archive Contents” section of the User’s Guide. Model outputs are aggregated to the column scale (i.e. PFT-specific outputs are not provided here).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
DOE OSTI2021

PyCCE: A python package for custer correlation expansion simulations of spin qubit dynamics.

PyCCE, an open-source Python library for simulating the dynamics of spin qubits in a spin bath, is presented using the cluster-correlation expansion (CCE) method. PyCCE includes modules to generate realistic spin baths, employing coupling parameters computed from first principles with electronic structure codes, and enables the user to run simulations with either the conventional or generalized CCE method. Three use cases of the Python library are illustrated: the calculation of the Hahn-echo coherence time of the nitrogen-vacancy in diamond; the calculation of the coherence time of the basal divacancy in silicon carbide at avoided crossings; and the calculation for magnetic field orientation-dependent dynamics of a shallow donor in silicon. The complete documentation, downloadable tutorials, and installation instructions are available at https://pycce.readthedocs.io/en/latest/.

coherence↗
DOE OSTI2016

Nanoconfinement Inside Molecular Metal Oxide Clusters: Dynamics and Modified Encapsulation Behavior

Abstract Encapsulation behavior, as well as the presence of internal catalytically active sites, has been spurring the applications of a 3 nm hollow spherical metal oxide cluster {Mo 132 } as an encapsulation host and a nanoreactor. Due to its well‐defined and tunable cluster structures, and nanoscaled internal void space comparable to the volumes of small molecules, this cluster provides a good model to study the dynamics of materials under nanoconfinement. Neutron scattering studies suggest that bulky internal ligands inside the cluster show slower and limited dynamics compared to their counterparts in the bulk state, revealing the rigid nature of the skeleton of the internal ligands. NMR studies indicate that the rigid internal ligands that partially cover the interfacial pore on the molybdenum oxide shells are able to block some large guest molecules from going inside the capsule cluster, which provides a convincing protocol for size‐selective encapsulation and separation.

Wang, Zhe↗
DOE OSTI2017

Different dynamics and pathway of disulfide bonds reduction of two human defensins, a molecular dynamics simulation study

Human defensins are a class of antimicrobial peptides that are crucial components of the innate immune system. Both human α defensin type 5 (HD5) and human β defensin type 3 (hBD-3) have 6 cysteine residues which form 3 pairs of disulfide bonds in oxidizing condition. Disulfide bond linking is important to the protein structure stabilization, and the disulfide bond linking and breaking order have been shown to influence protein function. In this project, microsecond long molecular dynamics simulations were performed to study the structure and dynamics of HD5 and hBD-3 wildtype and analogs which have all 3 disulfide bonds released in reducing condition. The structure of hBD-3 was found to be more dynamic and flexible than HD5, based on RMSD, RMSF, and radius of gyration calculations. The disulfide bridge breaking order of HD5 and hBD-3 in reducing condition was predicted by two kinds of methods, which gave consistent results. It was found that the disulfide bonds breaking pathways for HD5 and hBD-3 are very different. The breaking of disulfide bonds can influence the dimer interface by making the dimer structure less stable for both kinds of defensin. In order to understand the difference in dynamics and disulfide bond breaking pathway, hydrophilic and hydrophobic accessible surface areas (ASA), buried surface area between cysteine pairs, entropy of cysteine pairs, and internal energy were calculated. Comparing to the wildtype, hBD-3 analog is more hydrophobic, while HD5 is more hydrophilic. For hBD-3, the disulfide breaking is mainly entropy driven, while other factors such as the solvation effects may take the major role in controlling HD5 disulfide breaking pathway. Proteins 2017; 85:665–681. © 2016 Wiley Periodicals, Inc.

Biochemistry & Molecular Biology↗
DOE OSTI2016

A Comparison of Reduced Order Modeling Techniques Used in Dynamic Substructuring [PowerPoint]

Experimental dynamic substructuring is a means whereby a mathematical model for a substructure can be obtained experimentally and then coupled to a model for the rest of the assembly to predict the response. Recently, various methods have been proposed that use a transmission simulator to overcome sensitivity to measurement errors and to exercise the interface between the substructures; including the Craig-Bampton, Dual Craig-Bampton, and Craig-Mayes methods. This work compares the advantages and disadvantages of these reduced order modeling strategies for two dynamic substructuring problems. The methods are first used on an analytical beam model to validate the methodologies. Then they are used to obtain an experimental model for structure consisting of a cylinder with several components inside connected to the outside case by foam with uncertain properties. This represents an exceedingly difficult structure to model and so experimental substructuring could be an attractive way to obtain a model of the system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

High-order fully implicit solver for all-speed fluid dynamics: AUSM ride from nearly incompressible variable-density flows to shock dynamics

We introduce a novel Newton–Krylov (NK)-based fully implicit algorithm for solving fluid flows in a wide range of flow conditions—from variable density nearly incompressible to supersonic shock dynamics. The key enabling feature of our all-speed solver is the ability to efficiently solve conservation laws by choosing a set of independent variables that produce a well-conditioned Jacobian matrix for the linear iterations of the global nonlinear iterative solver. In particular, instead of choosing to discretize the conservative variables (density, momentum, total energy), which is traditionally used in Eulerian high-speed compressible fluid dynamics, we demonstrate superior performance by discretizing the primitive variables—pressure–velocity–temperature in the very low-Mach flow limits or density–velocity–temperature/entropy in the shock dynamics range. Moreover, our method allows us to avoid direct inversion of the mass matrix in discrete time derivatives, which is usually an additional source for stiffness, especially pronounced when going to very high-order schemes with non-orthogonal basis functions. Here, we show robust solutions obtained for discontinuous finite element discretization up to seventh-order accuracy. Another important aspect of the solution algorithm is the Advection Upstream Splitting Method (AUSM), adopted to compute numerical fluxes within our reconstructed discontinuous Galerkin (rDG) spatial discretization scheme. The use of the low-Mach modification of the hyperbolic flux operator is found to be necessary for enabling robust simulations of very stiff liquids and metals for Mach numbers below M=10 -5 , which is well known to be very computationally challenging for compressible solvers. We demonstrate that our fully implicit rDG-NK solver with the AUSM + -up flux treatment produces efficient and high-resolution numerical solutions at all speeds, ranging from vanishing Mach numbers to transonic and supersonic, without substantial modifications of the solution procedures. (At high speed, we add limiting and use a simpler preconditioning of the Krylov solver.) Numerical examples include nearly incompressible constant-property flow past a backward-facing step with heat transfer, low-Mach variable-property channel flow of water at supercritical state, phase change and melt pool dynamics for laser spot welding and selective laser melting in additive manufacturing, and Mach 3 flow in a wind tunnel with a step.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Virtual diffraction simulations using the quasi-coarse-grained dynamics method to understand and interpret plasticity contributions during in situ shock experiments

The dynamic deformation response of metallic materials has contributions from dislocations, deformation twinning, and plastic deformation. The current state-of-art techniques can detail the complex mechanistic history of deformation modes under shock loading in real-time using in situ X-ray diffraction (XRD). However, the capability of these experiments to unravel plasticity contributions is challenging due to limitations in interpreting results and the lack of validation from atomistic simulations. Molecular dynamics (MD) simulations can successfully capture various deformation modes in metals and complement experiments using simulated diffractograms at various stages of evolution. However, the difference in length and time scales of MD simulations and experiments is a substantial obstacle in completing and interpreting in situ diffractograms. Therefore, the existing modeling methods require various approximations to model defect evolution and interaction at the mesoscales. However, while using approximations to correlate the peak broadening behavior to the density of dislocations or the shifts/splitting due to the presence of twins, the interpretations of the plasticity contributions from diffractograms are non-trivial, especially when multiple modes of deformation may be operating. This viewpoint discusses combining a mesoscale modeling method called quasi-coarse-grained dynamics and virtual XRD to characterize the plasticity contributions in BCC metals from slip, twinning, and phase transformation behavior. Furthermore, the combined approach shows promise in bridging the mesoscale gap between the capabilities of atomic-scale simulations and in situ experiments to characterize the dynamic deformation of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Nonequilibrium Dynamical Mean-Field Theory for the Charge-Density-Wave Phase of the Falicov-Kimball Model

Nonequilibrium dynamical mean-field theory (DMFT) is developed for the case of the charge-density-wave ordered phase. We consider the spinless Falicov-Kimball model which can be solved exactly. This strongly correlated system is then placed in an uniform external dc electric field. We present a complete derivation for nonequilibrium dynamical mean-field theory Green’s functions defined on the Keldysh-Schwinger time contour. Here, we also discuss numerical issues involved in solving the coupled equations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

A holographic model for pseudogap in BCS–BEC crossover (I): Pairing fluctuations, double-trace deformation and dynamics of bulk bosonic fluid

We build a holographic model for the pairing fluctuation pseudogap phase in fermionic high temperature superconductivity/superfluidity based on the BCS–BEC crossover scenario. The pseudogap originates from incoherent Cooper pairing and has been observed in recent cold atom experiments. The strength of Cooper pairing and hence the BCS–BEC crossover is controlled by an effective 4-Fermi interaction and we argue that the double-trace deformation for charged scalar operator is a close analog in large N field theories. We employ the double-trace deformed Abelian Higgs model of holographic superconductors and propose that the incoherent fluctuations of the charged scalar in the bulk is the holographic dual of the fluctuating Cooper pairs. Using a Madelung transformation and the velocity-potential formalism, we develop a quantum fluid dynamics as an effective theory for these bulk fluctuations. The new fluid dynamics takes care of the boundary conditions required by AdS/CFT and encodes the vacuum polarization effect in curved spacetime. The pseudogap in conductivity can be related to the plasma oscillation of this bulk fluid.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Characterizing Dynamics of Anion/Pi Interactions through Molecular Dynamics Simulations

Proteins are not static structures, but undergo dynamical variations at room temperature that can lead to changes in the number and strength of different non-covalent interactions. The negatively charged (Asp/Glu) and aromatic (Phe/Trp/Tyr) amino acid groups in proteins can form anion/pi interactions, that have been shown to have a distance and angle dependency. This study characterizes the dynamic stability of these interactions in RmlC (PDB-1EP0), a homodimeric epimerase showing a cluster of six anion/pi pairs in crystal structure, as a function of time using Molecular Dynamics (MD) simulations. The dynamic variations found in these interactions correspond to a potential of mean force (PMF) that exhibits a relatively wide range of distances (~4.5 to~8.5Å) and angles (0 to~45deg) sampled by these anion/pi pairs. The corresponding PMF indicates an associated free energy change that can be more stabilizing (up to -5kcal/mol) than the ab initio-calculated interaction energy for the pairs in the crystal structure (-2.2kcal/mol). Possible anion/pi pairs and triplets (anion/anion/pi or anion/pi/pi) not seen in the crystal structure are also observed in other conformations sampled by the protein- both at the dimer interface and active site of the protein, forming an extensive network of anion/pi interactions covering most of the protein structure. Initial site-directed mutagenesis (SDM) experiments targeting one of these pairs, Asp84-Phe112, show that the single Phe/Met mutation decreases the stability of the protein compared to the wild type. Together these results suggest that anion-pi interactions can play an important role in maintaining both the structural stability and function of the proteins.

Kapoor, Karan↗
DOE OSTI2018

Importance of filter’s microstructure in dynamic filtration modeling of gasoline particulate filters (GPFs): Inhomogeneous porosity and pore size distribution

The state-of-the-art multiscale modeling of GPFs including channel scale, wall scale, and pore scale is described. The microstructures of two GPFs were experimentally characterized. The pore size distributions of the GPFs were determined by mercury porosimetry. The porosity was measured by X-ray computed tomography (CT) and found to be inhomogeneous across the substrate wall. The significance of pore size distribution with respect to filtration performance was analyzed. The predictions of filtration efficiency were improved by including the pore size distribution in the filtration model. A dynamic heterogeneous multiscale filtration (HMF) model was utilized to simulate particulate filtration on a single channel particulate filter with realistic particulate emissions from a spark-ignition direct-injection (SIDI) gasoline engine. The dynamic evolution of filter’s microstructure and macroscopic filtration characteristics including mass- and number-based filtration efficiencies and pressure drop were predicted and discussed. The microstructure of the GPF substrate including inhomogeneous porosity and pore size distribution is found to significantly influence local particulate deposition inside the substrate and macroscopic filtration performance and is recommended to be resolved in the filtration model to simulate and evaluate the filtration performance of GPFs.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2021

Data-Driven Distributed Algorithms for Estimating Eigenvalues and Eigenvectors of Interconnected Dynamical Systems

Here, the paper presents data-driven algorithms to estimate in a distributed manner the eigenvalues, right and left eigenvectors of an unknown linear (or linearized) interconnected dynamic system. In particular, the proposed algorithms do not require the identification of the system model in advance before performing the estimation. As a first step, we consider interconnected dynamical system with distinct eigenvalues. The proposed strategy first estimates the eigenvalues using the well-known Prony method. The right and left eigenvectors are then estimated by solving distributively a set of linear equations. One important feature of the proposed algorithms is that the topology of communication network used to perform the distributed estimation can be chosen arbitrarily, given that it is connected, and is also independent of the structure or sparsity of the system (state) matrix. The proposed distributed algorithms are demonstrated via a numerical example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Dynamic Succession of Groundwater Sulfate-Reducing Communities during Prolonged Reduction of Uranium in a Contaminated Aquifer

To further understand the diversity and dynamics of SRB in response to substrate amendment, we sequenced genes coding for the dissimilatory sulfite reductase (dsrA) in groundwater samples collected after an emulsified vegetable oil (EVO) amendment, which sustained U(VI)-reducing conditions for one year in a fast-flowing aquifer. EVO amendment significantly altered the composition of groundwater SRB communities. Sequences having no closely related-described species dominated (80%) the indigenous SRB communities in nonamended wells. After EVO amendment, Desulfococcus , Desulfobacterium , and Desulfovibrio , known for long-chain-fatty-acid, short-chain-fatty-acid and H 2 oxidation and U(VI) reduction, became dominant accounting for 7 ± 2%, 21 ± 8%, and 55 ± 8% of the SRB communities, respectively. Succession of these SRB at different bioactivity stages based on redox substrates/products (acetate, SO 4 –2 , U(VI), NO 3 – , Fe(II), and Mn(II)) was observed. Desulfovibrio and Desulfococcus dominated SRB communities at 4–31 days, whereas Desulfobacterium became dominant at 80–140 days. By the end of the experiment (day 269), the abundance of these SRB decreased but the overall diversity of groundwater SRB was still higher than non-EVO controls. Up to 62% of the SRB community changes could be explained by groundwater geochemical variables, including those redox substrates/products. A significant ( P < 0.001) correlation was observed between groundwater U(VI) concentrations and Desulfovibrio abundance. Lastly, our results showed that the members of SRB and their dynamics were correlated significantly with slow EVO biodegradation, electron donor production and maintenance of U(VI)-reducing conditions in the aquifer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Methods to Calculate Electronic Excited-State Dynamics for Molecules on Large Metal Clusters with Many States: Ensuring Fast Overlap Calculations and a Robust Choice of Phase

Here, we present an efficient set of methods for propagating excited-state dynamics involving a large number of configuration interaction singles (CIS) or Tamm-Dancoff approximation (TDA) single-reference excited states. Specifically, (i) following Head-Gordon et al., we implement an exact evaluation of the overlap of singly-excited CIS/TDA electronic states at different nuclear geometries using a biorthogonal basis and (ii) we employ a unified protocol for choosing the correct phase for each adiabat at each geometry. For many-electron systems, the combination of these techniques significantly reduces the computational cost of integrating the electronic Schrodinger equation and imposes minimal overhead on top of the underlying electronic structure calculation. As a demonstration, we calculate the electronic excited-state dynamics for a hydrogen molecule scattering off a silver metal cluster, focusing on high-lying excited states, where many electrons can be excited collectively and crossings are plentiful. Interestingly, we find that the high-lying, plasmon-like collective excitation spectrum changes with nuclear dynamics, highlighting the need to simulate non-adiabatic nuclear dynamics and plasmonic excitations simultaneously. In the future, the combination of methods presented here should help theorists build a mechanistic understanding of plasmon-assisted charge transfer and excitation energy relaxation processes near a nanoparticle or metal surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Imidazole and 1-Methylimidazole Hydrogen Bonding and Nonhydrogen Bonding Liquid Dynamics: Ultrafast IR Experiments

Dynamics of imidazole (IM) and 1-methylimidazole (1-MeIM) in the liquid phase at 95 °C were studied by IR polarization selective pump-probe (PSPP) and two-dimensional IR (2D IR) spectroscopies. The two molecules are very similar structurally except that IM can be simultaneously a hydrogen bond donor and acceptor and therefore forms extended hydrogen bonded networks. The broader IR absorption spectrum and shorter vibrational lifetime of the vibrational probe, selenocyanate anion (SeCN – ), in IM vs. 1-MeIM indicate that stronger hydrogen bonding exists between SeCN – and IM. Molecular dynamics (MD) simulations support the strong hydrogen bond formation between SeCN – and IM via the HN moiety. SeCN – makes two H-bonds with IM; it is inserted in the IM H-bonded chains rather than being a chain terminator. The strong hydrogen bonding influenced the reorientation dynamics of SeCN – in IM, leading to more restricted short time angular sampling (wobbling-in-a-cone). The complete orientational diffusion time in IM is 1.7 times slower than in 1-MeIM, but the slowdown is less than expected, considering the 3-fold larger viscosity of IM. The jump reorientation mechanism accounts for the anomalously fast orientational relaxation in IM, and the MD simulations determined the average jump angle of the probe between hydrogen bonding sites. Spectral diffusion time constants obtained from the 2D IR experiments are only modestly slower in IM than in 1-MeIM in spite of the significant increase in viscosity. Here, the results indicate that the spectral diffusion sensed by the SeCN – has IM hydrogen bond dynamics contributions not present in 1-MeIM.

14 SOLAR ENERGY↗