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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.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Causal interaction in high frequency turbulence at the biosphere–atmosphere interface: Structure–function coupling

At the biosphere–atmosphere interface, nonlinear interdependencies among components of an ecohydrological complex system can be inferred using multivariate high frequency time series observations. Information flow among these interacting variables allows us to represent the causal dependencies in the form of a directed acyclic graph (DAG). Here, we use high frequency multivariate data at 10 Hz from an eddy covariance instrument located at 25 m above agricultural land in the Midwestern US to quantify the evolutionary dynamics of this complex system using a sequence of DAGs by examining the structural dependency of information flow and the associated functional response. We investigate whether functional differences correspond to structural differences or if there are no functional variations despite the structural differences. We base our analysis on the hypothesis that causal dependencies are instigated through information flow, and the resulting interactions sustain the dynamics and its functionality. To test our hypothesis, we build upon causal structure analysis in the companion paper to characterize the information flow in similarly clustered DAGs from 3-min non-overlapping contiguous windows in the observational data. We characterize functionality as the nature of interactions as discerned through redundant, unique, and synergistic components of information flow. Through this analysis, we find that in turbulence at the biosphere–atmosphere interface, the variables that control the dynamic character of the atmosphere as well as the thermodynamics are driven by non-local conditions, while the scalar transport associated with CO and H 2 O is mainly driven by short-term local conditions.

58 GEOSCIENCES↗
DOE OSTI2026

Solvent effects on triplet yields in BODIPY-based photosensitizers

Here, we employ molecular dynamics simulations and quantum rate theories to elucidate the complex condensed-phase dynamics underpinning triplet-state formation in organic photosensitizers. Using models informed by first-principles calculations complete with a molecular representation of solvents of different polarities, we elucidate the interplay of the internal and environmental interactions underlying triplet yield. We find that triplet yields depend sensitively on the dielectric stabilization of the charge transfer intermediate that facilitates a transition into the triplet manifold. Our results illustrate the importance of molecularly detailed models in understanding the excited-state internal charge-transfer dynamics of photochemically relevant organic molecules.

Coello Escalante, Leonardo [University of Californ↗
DOE OSTI2026

Constant Overhead Entanglement Distillation via Scrambling

High-fidelity quantum entanglement enables key quantum networking capabilities such as secure communication and distributed quantum computing, but long-distance entanglement distribution is limited by noise and loss. Entanglement distillation protocols address this problem by extracting high-fidelity Bell pairs from multiple noisy ones. The primary objective is minimizing the resource overhead: the number of noisy input pairs needed to distill each high-fidelity output pair. While protocols achieving optimal overhead are known in theory, they often require complex decoding operations that make practical implementation challenging. We circumvent this challenge by introducing protocols that use quantum scrambling—the spreading of quantum information under chaotic dynamics—through random Clifford operations. Based on this scrambling mechanism, our protocol maintains asymptotically constant overhead, independent of the desired output error rate $\bar{𝜖}$ , and can be implemented with shallow quantum circuits of depth 𝑂⁡(poly log log⁡ $\bar{𝜖}$ −1 ) and memory 𝑂⁡(poly log⁡ $\bar{𝜖}$ −1 ). Our protocol remains effective even with noisy quantum gates. By incorporating error correction, our protocol achieves state-of-the-art performance: starting with pairs of 10% initial infidelity, we require only seven noisy inputs per output pair to distill a single Bell pair with infidelity $\bar{𝜖}$ =10 −12 , substantially outperforming existing schemes. We demonstrate the utility of our protocols for quantum repeater networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Reduced-basis method for few-body bound-state emulation

Recent advances in both theoretical and computational methods have enabled large-scale, precision calculations of the properties of atomic nuclei. With the growing complexity of modern nuclear theory, however, also comes the need for novel methods to perform systematic studies and quantify the uncertainties of models when confronted with experimental data. Here, this study presents an application of such an approach, the reduced basis method, to substantially lower computational costs by constructing a significantly smaller Hamiltonian subspace informed by previous solutions. Our method shows comparable efficiency and accuracy to other dimensionality reduction techniques on an artificial three-body bound system while providing a richer representation of physical information in its projection and training subspace. This methodological advancement can be applied in other contexts and has the potential to greatly improve our ability to systematically explore theoretical models and thus enhance our understanding of the fundamental properties of nuclear systems.

cluster models↗
DOE OSTI2022

Residual Stress Modeling and Advanced Diffraction Measurements of 347H Steel Weldments

The 347H stainless steel is a primary high-temperature material for many energy and power generation industries. Stress relief cracking (SRC) has been a particular concern in welding of this material. The residual stress induced by welding and its evolution during post-welding heat treatment (PWHT) and subsequent operating and service conditions is one of the primary factors contributing to SRC. The lifetime of welded structure components is also controlled by the precipitation kinetics that accompanies PWHT, stress relaxation process, and long-term aging and complex synergistic factors. Various theories have been proposed in the past to explain SRC. However, a widely accepted approach to predicting the entire damage evolution and the resulting performance reduction is still lacking. This study is to demonstrate a reliable solution for two critical issues that affect the predictions. First, the residual stress distribution obtained from both simulation and neutron diffraction is compared, which increases the accuracy of mechanical analysis simulation model and therefore builds a solid basis for the lifetime prediction model. Second, the generation, evolution, and annihilation of precipitates are monitored by the synchrotron diffraction experiment. Preliminary results demonstrate the critical importance of precipitation kinetics on the residual stress distribution/redistribution during heat treatments.

Yang, Yi↗
DOE OSTI2024

Modeling Spatial Asymmetries in Teleconnected Extreme Temperatures

Abstract Combining strengths from deep learning and extreme value theory can help describe complex relationships between variables where extreme events have significant impacts (e.g., environmental or financial applications). Neural networks learn complicated nonlinear relationships from large datasets under limited parametric assumptions. By definition, the number of occurrences of extreme events is small, which limits the ability of the data-hungry, nonparametric neural network to describe rare events. Inspired by recent extreme cold winter weather events in North America caused by atmospheric blocking, we examine several probabilistic generative models for the entire multivariate probability distribution of daily boreal winter surface air temperature. We propose metrics to measure spatial asymmetries, such as long-range anticorrelated patterns that commonly appear in temperature fields during blocking events. Compared to vine copulas, the statistical standard for multivariate copula modeling, deep learning methods show improved ability to reproduce complicated asymmetries in the spatial distribution of ERA5 temperature reanalysis, including the spatial extent of in-sample extreme events.

Krock, Mitchell L.↗
DOE OSTI2023

A Novel Method for Diagnosing Land–Atmosphere Coupling Sensitivity in a Single-Column Model

The response of boundary layer properties and cloudiness to changes in surface evaporative fraction (EF) is investigated in a single-column model to quantify the locally coupled impact of subgrid surface variations on the atmosphere during summer. Sensitive coupling days are defined when the model atmosphere exhibits large variations across a range of EFs centered on the analyzed value. Coupling sensitivity exists as both positive feedback (cloudiness increases with EF) and negative feedback (clouds increase with decreasing EF) regimes. The positive regime manifests in shallow convection situations, which are capped by a strengthened inversion and subsidence, restricting the vertical extent of convection to just above the boundary layer. Surfaces with larger EF (greater surface latent heat flux) can inject more moisture into the vertically confined system, lowering the cloud base and an increasing cloud liquid water path (LWP). Negative feedback regimes tend to manifest when large-scale deep convection, such as from mesoscale convective systems and fronts, is advected through the domain, where convection strengthens over surfaces with a lower EF (greater surface sensible heat flux). The invigoration of these systems by the land surface leads to an increase in LWP through strengthened updrafts and stronger coupling between the boundary layer and the free atmosphere. These results apply in the absence of heterogeneity-induced mesoscale circulations, providing a one-dimensional dynamical perspective on the effect of surface heterogeneity. Finally, this study provides a framework of intermediate complexity, lying between parcel theory and high-resolution coupled land–atmosphere modeling, and therefore isolates the relevant first-order processes in land–atmosphere interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Zentropy Theory for Transformative Functionalities of Magnetic and Superconducting Materials

The proposed research developed the zentropy theory through applications to complex magnetic materials and superconductors under the hypothesis that the emergent properties of complex magnetic materials and superconductors can be predicted by statistical mechanics of ergodic microstates with their partition functions computed from DFT-predicted free energies. The key objective is to develop approaches to systematically determine the types and number of microstates and the supercell size in DFT-based calculations through convergency of macroscopic functionalities, with the incorporation of our mixed-space approach accounting for the interactions between periodic supercells. In addition to use scientific intuitions to guide the design of important microstates, the key innovation of the proposed research is to integrate the domain knowledge and the material-property-descriptor database (MPDD) with 4 million microstates, which is supported by our deep neural network machine learning models (SIPFENN: structure-informed prediction of formation energy using neural networks) and integrated with our high throughput DFT Tool Kit (DFTTK). For complex magnetic materials, one of the objectives is to develop approaches to calculate short-range ordering from the statistical distribution of each microstate. For superconductors, the divergency of quasiparticle effective mass at a quantum critical point will be investigated, and the superconducting and non-superconducting microstates will be delineated through analysis of electronic band structure, density of states, charge density, and Fermi surface.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Many-Body Effects in FeN4 Center Embedded in Graphene

We introduce a computational approach to study porphyrin-like transition metal complexes, bridging density functional theory and exact many-body techniques, such as the density matrix renormalization group (DMRG). We first derive a multi-orbital Anderson impurity Hamiltonian starting from first principles considerations that qualitatively reproduce generalized gradient approximation (GGA)+U results when ignoring inter-orbital Coulomb repulsion U ′ and Hund exchange J. An exact canonical transformation is used to reduce the dimensionality of the problem and make it amenable to DMRG calculations, including all many-body terms (both intra- and inter-orbital), which are treated in a numerically exact way. We apply this technique to FeN 4 centers in graphene and show that the inclusion of these terms has dramatic effects: as the iron orbitals become single occupied due to the Coulomb repulsion, the inter-orbital interaction further reduces the occupation, yielding a non-monotonic behavior of the magnetic moment as a function of the interactions, with maximum polarization only in a small window at intermediate values of the parameters. Furthermore, U ′ changes the relative position of the peaks in the density of states, particularly on the iron d z 2 orbital, which is expected to affect the binding of ligands greatly.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantum Simulation of an Open System: A Dissipative 1+1D Ising Model

The 1+1D Ising model is an ideal benchmark for quantum algorithms, as it is very well understood theoretically. This is true even when expanding the model to include complex coupling constants. In this work, we implement quantum algorithms designed for the simulation of open or complex coupling quantum field theories on IBM devices with a focus on the measurement of the Lee-Yang edge singularity. This feature corresponds (at large volumes) to a phase transition, and our successful reproduction of the transition represents a non-trivial test for current hardware and its ability to distinguish features of interest in quantum field theories.

Gustafson, Erik↗
DOE OSTI2023

First-Principles Understanding of Optical Excitations within Low-Dimensional Materials

The objective of this project is to utilize first-principles computational approaches to understand optical excitations within two-dimensional monolayers and heterostructures, with the ultimate goal of designing new materials by modifying the chemical and physical structure on the nanoscale. In 2D heterostructures, the nature and movement of the exciton is determined to a large extent by the electron-electron and electron-phonon strengths within individual monolayers, as well as the coupling between layers, all of which in turn depend on chemistry, solid-state screening properties, and quantum confinement. Controlling the nature and migration properties of excitons requires an understanding of the complex relationship between electrons, phonons, defects, disorder, and dynamics. The aim of this project is to determine, by analysis of highly accurate density functional theory (DFT) and many-body perturbation theory (MBPT) calculations, how these complexities can be decomposed into simple, tunable parameters. The specific goals of this project are to 1) understand electron conductivity, absorption and transparency of monolayer semiconductors and metals; 2) develop a theory of excitons near defects in low dimensions; and 3) understand the influence of inter-layer interactions in heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Improved Methods for Modeling Functional Transition Metal Compounds in Complex Environments: Ground States, Excited States, and Spectroscopies

Rapid advances in energy applications require new theory and computational models to provide guidance for interpretation of experimental results and mechanistic understanding. New theory development is necessary to treat systems of increasing complexity, size, and relevance to real applications. Functional transition metal compounds, including molecules, clusters, nanoparticles, surfaces, and solids, provide particular promise for magnetic, optical, and catalytic applications. However, such systems can be exceptionally challenging to model. To make progress in understanding and designing transition metal compounds for energy applications, theory must be able to simulate such systems in complex environments, as well as simulate the spectra of such complex systems to provide direct connections with experiment. Leveraging the independent expertise of the team’s members, this project aimed to make inroads to the theoretical and computational challenges associated with studying transition metal compounds, their reaction chemistry, photophysics and photochemistry, and response to spectroscopic interrogation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Site Density Functional Theory and Structural Bioinformatics Analysis of the SARS-CoV Spike Protein and hACE2 Complex

The entry of the SARS-CoV-2, a causative agent of COVID-19, into human host cells is mediated by the SARS-CoV-2 spike (S) glycoprotein, which critically depends on the formation of complexes involving the spike protein receptor-binding domain (RBD) and the human cellular membrane receptor angiotensin-converting enzyme 2 (hACE2). Using classical site density functional theory (SDFT) and structural bioinformatics methods, we investigate binding and conformational properties of these complexes and study the overlooked role of water-mediated interactions. Analysis of the three-dimensional reference interaction site model (3DRISM) of SDFT indicates that water mediated interactions in the form of additional water bridges strongly increases the binding between SARS-CoV-2 spike protein and hACE2 compared to SARS-CoV-1-hACE2 complex. By analyzing structures of SARS-CoV-2 and SARS-CoV-1, we find that the homotrimer SARS-CoV-2 S receptor-binding domain (RBD) has expanded in size, indicating large conformational change relative to SARS-CoV-1 S protein. Protomer with the up-conformational form of RBD, which binds with hACE2, exhibits stronger intermolecular interactions at the RBD-ACE2 interface, with differential distributions and the inclusion of specific H-bonds in the CoV-2 complex. Further interface analysis has shown that interfacial water promotes and stabilizes the formation of CoV-2/hACE2 complex. This interaction causes a significant structural rigidification of the spike protein, favoring proteolytic processing of the S protein for the fusion of the viral and cellular membrane. Moreover, conformational dynamics simulations of RBD motions in SARS-CoV-2 and SARS-CoV-1 point to the role in modification of the RBD dynamics and their impact on infectivity.

3DRISM↗
DOE OSTI2025

Hydrogenation of ethylene over molybdenum–sulfur complexes supported on UiO-66

Development of supported single-site catalysts using small metal sulfide complexes could significantly help in the development of cost-effective catalytic materials to drive selective hydrogenation and hydrogenolysis. The goal of this study is to contribute to the development of metal sulfide catalysts by calculating the thermodynamics of a catalytic cyclic involving a metal organic framework functionalized by insertion of metal sulfide. Anchored metal sulfide complexes can potentially be designed with ligands with distinctly different electronic and catalytic properties for specific catalytic applications. Here we examine the hydrogenation of ethylene as a model. We use density functional theory to investigate molybdenum–sulfur complexes as active catalysts anchored on the metal–organic framework UiO-66 as a stable support. Our calculations show that the anchored complexes with more than two sulfur ligands are unfavorable for ethylene adsorption, so we study complexes with one or two sulfur ligands. Hydrogenation of the unsaturated carbon double bond requires the transfer of two hydrogen atoms, which can occur via heterolytic activation of hydrogen to form a Mo-hydride and a protonated sulfur – either by hydride transfer followed by proton transfer or via proton transfer followed by hydride transfer, and we find that both mechanisms proceed via two-state reactivity involving two spin states along the reaction path. Of the two catalysts studied in gas the phase, the MoS single-sulfur–ligand complex with lower oxidation states produces thermodynamically more favorable intermediates along the pathway for the first hydrogen transfer for both the hydride-first mechanism and the proton-first mechanism. As a result, the quantum mechanical calculations provide experimentally inaccessible partial atomic charges and geometries of the various intermediates encountered along the steps of the reaction mechanisms.

Kermani, Maryam Mansoori [University of Minnesota,↗
DOE OSTI2025

Gating Single Molecules with Counterions

We report atomic-scale gating and visualization of local charge distribution within individual rare-earth-based molecular complexes on a metallic surface. The complexes are formed by a positively charged lanthanum ion coordinated to a (pcam)3 molecule and a negatively charged counterion trapped underneath via electrostatic interactions on a Au(111) surface. Local gating is performed by adding an additional negatively charged counterion to one side of the complex, which results in the redistribution of charges within the complex and a positive shift of the frontier orbitals. This is caused by the internal Stark effect induced by the added counterion. This effect is directly captured using tunneling spectroscopy and spectroscopic mapping at 5 K substrate temperature. The polarizability of the complex is corroborated by density functional theory and analytical calculations based on experimental findings. Furthermore, the influence of charge polarization on nearby complexes is investigated in a cluster purposely assembled using three complexes, which reveals maintaining the charge states as in single complexes. These findings will enable the design of robust charged rare-earth complexes to be tailored for potential solid-state applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Reducing Operator Complexity of Galerkin Coarse-grid Operators with Machine Learning

Here, we propose a data-driven and machine-learning-based approach to compute non-Galerkin coarse-grid operators in multigrid (MG) methods, addressing the well-known issue of increasing operator complexity. Guided by the MG theory on spectrally equivalent coarse-grid operators, we have developed novel machine learning algorithms that utilize neural networks combined with smooth test vectors from multigrid eigenvalue problems. The proposed method demonstrates promise in reducing the complexity of coarse-grid operators while maintaining overall MG convergence for solving parametric partial differential equation problems. Numerical experiments on anisotropic rotated Laplacian and linear elasticity problems are provided to showcase the performance and comparison with existing methods for computing non-Galerkin coarse-grid operators.

97 MATHEMATICS AND COMPUTING↗